SYMBOL INDEX (5174 symbols across 449 files)

FILE: braincog/base/brainarea/BrainArea.py
  class BrainArea (line 19) | class BrainArea(nn.Module, abc.ABC):
    method __init__ (line 25) | def __init__(self):
    method forward (line 31) | def forward(self, x):
    method reset (line 39) | def reset(self):
  class ThreePointForward (line 48) | class ThreePointForward(BrainArea):
    method __init__ (line 53) | def __init__(self, w1, w2, w3):
    method forward (line 66) | def forward(self, x):
  class Feedback (line 78) | class Feedback(BrainArea):
    method __init__ (line 83) | def __init__(self, w1, w2, w3):
    method forward (line 96) | def forward(self, x):
    method reset (line 106) | def reset(self):
  class TwoInOneOut (line 110) | class TwoInOneOut(BrainArea):
    method __init__ (line 115) | def __init__(self, w1, w2):
    method forward (line 126) | def forward(self, x1, x2):
  class SelfConnectionArea (line 136) | class SelfConnectionArea(BrainArea):
    method __init__ (line 141) | def __init__(self, w1, w2 ):
    method forward (line 153) | def forward(self, x):
    method reset (line 163) | def reset(self):

FILE: braincog/base/brainarea/IPL.py
  class IPLNet (line 29) | class IPLNet(nn.Module):
    method __init__ (line 34) | def __init__(self, connection):
    method forward (line 52) | def forward(self, input1, input2):  # input from vPMC and STS
    method UpdateWeight (line 67) | def UpdateWeight(self, i, dw):
    method reset (line 76) | def reset(self):
    method getweight (line 86) | def getweight(self):

FILE: braincog/base/brainarea/Insula.py
  class InsulaNet (line 27) | class InsulaNet(nn.Module):
    method __init__ (line 31) | def __init__(self,connection):
    method forward (line 44) | def forward(self, input1, input2): # input from IPLv and STS
    method UpdateWeight (line 54) | def UpdateWeight(self,i,dw):
    method reset (line 63) | def reset(self):
    method getweight (line 73) | def getweight(self):

FILE: braincog/base/brainarea/PFC.py
  class PFC (line 7) | class PFC:
    method __init__ (line 11) | def __init__(self):
    method forward (line 16) | def forward(self, x):
    method reset (line 24) | def reset(self):
  class dlPFC (line 33) | class dlPFC(BaseModule, PFC):
    method __init__ (line 37) | def __init__(self,
    method _rest_c (line 52) | def _rest_c(self):
    method _create_fc (line 56) | def _create_fc(self):

FILE: braincog/base/brainarea/basalganglia.py
  class basalganglia (line 21) | class basalganglia(nn.Module):
    method __init__ (line 26) | def __init__(self, ns, na, we, wi, node_type):
    method forward (line 104) | def forward(self, input):
    method UpdateWeight (line 117) | def UpdateWeight(self, i, dw):
    method reset (line 127) | def reset(self):
    method getweight (line 137) | def getweight(self):
    method getmask (line 144) | def getmask(self):

FILE: braincog/base/brainarea/dACC.py
  class dACC (line 17) | class dACC(BaseModule):
    method __init__ (line 21) | def __init__(self,
    method _rest_c (line 42) | def _rest_c(self):
    method _create_fc (line 46) | def _create_fc(self):
    method update_c (line 55) | def update_c(self, c, STDP, tau_c=0.2):
    method forward (line 70) | def forward(self, inputs, epoch):

FILE: braincog/base/connection/CustomLinear.py
  class CustomLinear (line 11) | class CustomLinear(nn.Module):
    method __init__ (line 16) | def __init__(self, weight, mask=None):
    method forward (line 22) | def forward(self, x: torch.Tensor):
    method update (line 31) | def update(self, dw):

FILE: braincog/base/connection/layer.py
  class VotingLayer (line 13) | class VotingLayer(nn.Module):
    method __init__ (line 19) | def __init__(self, voter_num: int):
    method forward (line 23) | def forward(self, x: torch.Tensor):
  class WTALayer (line 29) | class WTALayer(nn.Module):
    method __init__ (line 34) | def __init__(self, k=1):
    method forward (line 38) | def forward(self, x: torch.Tensor):
  class NDropout (line 50) | class NDropout(nn.Module):
    method __init__ (line 55) | def __init__(self, p):
    method n_reset (line 60) | def n_reset(self):
    method create_mask (line 67) | def create_mask(self, x):
    method forward (line 75) | def forward(self, x):
  class WSConv2d (line 85) | class WSConv2d(nn.Conv2d):
    method __init__ (line 87) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 97) | def forward(self, x):
  class ThresholdDependentBatchNorm2d (line 108) | class ThresholdDependentBatchNorm2d(_BatchNorm):
    method __init__ (line 114) | def __init__(self, num_features, alpha: float, threshold: float = .5, ...
    method _check_input_dim (line 126) | def _check_input_dim(self, input):
    method forward (line 130) | def forward(self, input):
  class TEBN (line 136) | class TEBN(nn.Module):
    method __init__ (line 137) | def __init__(self, num_features,step, eps=1e-5, momentum=0.1,**kwargs):
    method forward (line 142) | def forward(self, input):
  class LayerNorm (line 153) | class LayerNorm(nn.Module):
    method __init__ (line 160) | def __init__(self, normalized_shape, eps=1e-6, data_format="channels_l...
    method forward (line 170) | def forward(self, x):
  class SMaxPool (line 181) | class SMaxPool(nn.Module):
    method __init__ (line 189) | def __init__(self, child):
    method forward (line 194) | def forward(self, x):
    method reset (line 201) | def reset(self):
  class LIPool (line 205) | class LIPool(nn.Module):
    method __init__ (line 213) | def __init__(self, child=None):
    method forward (line 221) | def forward(self, x):
    method reset (line 227) | def reset(self):
  class CustomLinear (line 231) | class CustomLinear(nn.Module):
    method __init__ (line 233) | def __init__(self, in_channels, out_channels, bias=True):
    method forward (line 253) | def forward(self, inputs):

FILE: braincog/base/conversion/convertor.py
  class HookScale (line 9) | class HookScale(nn.Module):
    method __init__ (line 16) | def __init__(self,
    method forward (line 31) | def forward(self, x):
  class Hookoutput (line 45) | class Hookoutput(nn.Module):
    method __init__ (line 50) | def __init__(self, module):
    method forward (line 55) | def forward(self, x):
  class Scale (line 61) | class Scale(nn.Module):
    method __init__ (line 66) | def __init__(self, scale: float = 1.0):
    method forward (line 70) | def forward(self, x):
  function reset (line 77) | def reset(self):
  class Convertor (line 90) | class Convertor(nn.Module):
    method __init__ (line 111) | def __init__(self,
    method forward (line 135) | def forward(self, model):
    method register_hook (line 145) | def register_hook(model, p=0.99, channelnorm=False, gamma=0.999):
    method get_percentile (line 160) | def get_percentile(model, dataloader, device, batch_num=1):
    method replace_for_spike (line 172) | def replace_for_spike(model, lipool=True, soft_mode=True, gamma=1, spi...
  class SNode (line 194) | class SNode(nn.Module):
    method __init__ (line 201) | def __init__(self, soft_mode=False, gamma=5):
    method forward (line 210) | def forward(self, x):
    method hard_reset (line 218) | def hard_reset(self):
    method soft_reset (line 224) | def soft_reset(self):
    method reset (line 230) | def reset(self):

FILE: braincog/base/conversion/merge.py
  function mergeConvBN (line 5) | def mergeConvBN(m):
  function merge (line 26) | def merge(conv, bn):

FILE: braincog/base/conversion/spicalib.py
  class SpiCalib (line 5) | class SpiCalib(nn.Module):
    method __init__ (line 6) | def __init__(self, allowance):
    method forward (line 12) | def forward(self, x):
    method reset (line 33) | def reset(self):

FILE: braincog/base/encoder/encoder.py
  class AutoEncoder (line 7) | class AutoEncoder(nn.Module):
    method __init__ (line 8) | def __init__(self, step, spike_output=True):
    method forward (line 21) | def forward(self, x):
  class Encoder (line 45) | class Encoder(nn.Module):
    method __init__ (line 56) | def __init__(self, step, encode_type='ttfs', *args, **kwargs):
    method forward (line 68) | def forward(self, inputs, deletion_prob=None, shift_var=None):
    method direct (line 97) | def direct(self, inputs):
    method auto (line 107) | def auto(self, inputs):
    method ttfs (line 115) | def ttfs(self, inputs):
    method rate (line 131) | def rate(self, inputs):
    method phase (line 141) | def phase(self, inputs):
    method delete (line 162) | def delete(self, inputs, prob):
    method shift (line 175) | def shift(self, inputs, var):

FILE: braincog/base/encoder/population_coding.py
  class PEncoder (line 5) | class PEncoder(nn.Module):
    method __init__ (line 11) | def __init__(self, step, encode_type):
    method forward (line 16) | def forward(self, inputs, num_popneurons, *args, **kwargs):
    method population_time (line 21) | def population_time(self, inputs, m):
    method population_voltage (line 62) | def population_voltage(self, inputs, m, VTH):

FILE: braincog/base/encoder/qs_coding.py
  class QSEncoder (line 8) | class QSEncoder:
    method __init__ (line 19) | def __init__(self,
    method __call__ (line 37) | def __call__(self, image, image_delta, image_ori, image_ori_delta):
    method shift_trans (line 56) | def shift_trans(self, image, image_delta, image_ori, image_ori_delta):
    method noise_trans (line 93) | def noise_trans(self, image, image_ori, image_ori_delta):
    method reverse_pixels (line 131) | def reverse_pixels(self, image, image_delta, noise_rate, flip_bits=None):

FILE: braincog/base/learningrule/BCM.py
  class BCM (line 20) | class BCM(nn.Module):
    method __init__ (line 25) | def __init__(self, node, connection, cfunc=None, weightdecay=0.99, tau...
    method forward (line 43) | def forward(self, *x):
    method cfunc (line 62) | def cfunc(self, s):
    method reset (line 67) | def reset(self):

FILE: braincog/base/learningrule/Hebb.py
  class Hebb (line 20) | class Hebb(nn.Module):
    method __init__ (line 25) | def __init__(self, node, connection):
    method forward (line 36) | def forward(self, *x):
    method reset (line 54) | def reset(self):

FILE: braincog/base/learningrule/RSTDP.py
  class RSTDP (line 20) | class RSTDP(nn.Module):
    method __init__ (line 24) | def __init__(self, node, connection, decay=0.99, reward_decay=0.5):
    method forward (line 40) | def forward(self, *x, r):
    method cal_trace (line 49) | def cal_trace(self, x):
    method reset (line 61) | def reset(self):

FILE: braincog/base/learningrule/STDP.py
  class STDP (line 20) | class STDP(nn.Module):
    method __init__ (line 25) | def __init__(self, node, connection, decay=0.99):
    method forward (line 37) | def forward(self, x):
    method cal_trace (line 55) | def cal_trace(self, x):
    method reset (line 66) | def reset(self):
  class MutliInputSTDP (line 73) | class MutliInputSTDP(nn.Module):
    method __init__ (line 78) | def __init__(self, node, connection, decay=0.99):
    method forward (line 90) | def forward(self, *x):
    method cal_trace (line 112) | def cal_trace(self, x):
    method reset (line 124) | def reset(self):
  class LTP (line 131) | class LTP(MutliInputSTDP):
  class LTD (line 138) | class LTD(nn.Module):
    method __init__ (line 143) | def __init__(self, node, connection, decay=0.99):
    method forward (line 155) | def forward(self, *x):
    method cal_trace (line 174) | def cal_trace(self, x):
    method reset (line 186) | def reset(self):
  class FullSTDP (line 193) | class FullSTDP(nn.Module):
    method __init__ (line 198) | def __init__(self, node, connection, decay=0.99, decay2=0.99):
    method forward (line 212) | def forward(self, *x):
    method cal_tracein (line 239) | def cal_tracein(self, x):
    method cal_traceout (line 251) | def cal_traceout(self, x):
    method reset (line 263) | def reset(self):

FILE: braincog/base/learningrule/STP.py
  class short_time (line 4) | class short_time():
    method __init__ (line 11) | def __init__(self, SizeHistOutput):
    method syndepr (line 16) | def syndepr(self, Syn=None, ISI=None, Nsp=None):
    method set_gsyn (line 31) | def set_gsyn(self, np=None, dt=None, v=None, NoiseSyn=None):
    method IDderiv (line 74) | def IDderiv(self, np=None, v=None, dt=None, dv=None, NoiseSyn=None, fl...
    method update (line 146) | def update(self, np=None, dt=None, NoiseSyn=None, flag_dv=None):

FILE: braincog/base/node/node.py
  class BaseNode (line 25) | class BaseNode(nn.Module, abc.ABC):
    method __init__ (line 42) | def __init__(self,
    method calc_spike (line 72) | def calc_spike(self):
    method integral (line 80) | def integral(self, inputs):
    method get_thres (line 90) | def get_thres(self):
    method rearrange2node (line 93) | def rearrange2node(self, inputs):
    method rearrange2op (line 118) | def rearrange2op(self, inputs):
    method forward (line 141) | def forward(self, inputs):
    method n_reset (line 199) | def n_reset(self):
    method get_n_attr (line 208) | def get_n_attr(self, attr):
    method set_n_warm_up (line 215) | def set_n_warm_up(self, flag):
    method set_n_threshold (line 223) | def set_n_threshold(self, thresh):
    method set_n_tau (line 231) | def set_n_tau(self, tau):
  class BaseMCNode (line 244) | class BaseMCNode(nn.Module, abc.ABC):
    method __init__ (line 251) | def __init__(self,
    method calc_spike (line 267) | def calc_spike(self):
    method integral (line 270) | def integral(self, inputs):
    method forward (line 273) | def forward(self, inputs: dict):
    method n_reset (line 285) | def n_reset(self):
    method get_n_fire_rate (line 290) | def get_n_fire_rate(self):
    method set_n_warm_up (line 295) | def set_n_warm_up(self, flag):
    method set_n_threshold (line 298) | def set_n_threshold(self, thresh):
  class ThreeCompNode (line 302) | class ThreeCompNode(BaseMCNode):
    method __init__ (line 313) | def __init__(self,
    method integral (line 329) | def integral(self, basal_inputs, apical_inputs):
    method calc_spike (line 341) | def calc_spike(self):
  class ReLUNode (line 351) | class ReLUNode(BaseNode):
    method __init__ (line 356) | def __init__(self,
    method forward (line 362) | def forward(self, x):
    method calc_spike (line 375) | def calc_spike(self):
  class BiasReLUNode (line 379) | class BiasReLUNode(BaseNode):
    method __init__ (line 384) | def __init__(self,
    method forward (line 390) | def forward(self, x):
    method calc_spike (line 396) | def calc_spike(self):
  class IFNode (line 402) | class IFNode(BaseNode):
    method __init__ (line 419) | def __init__(self, threshold=.5, act_fun=AtanGrad, *args, **kwargs):
    method integral (line 431) | def integral(self, inputs):
    method calc_spike (line 434) | def calc_spike(self):
  class LIFNode (line 439) | class LIFNode(BaseNode):
    method __init__ (line 457) | def __init__(self, threshold=0.5, tau=2., act_fun=QGateGrad, *args, **...
    method integral (line 467) | def integral(self, inputs):
    method calc_spike (line 470) | def calc_spike(self):
  class BurstLIFNode (line 475) | class BurstLIFNode(LIFNode):
    method __init__ (line 476) | def __init__(self, threshold=.5, tau=2., act_fun=RoundGrad, *args, **k...
    method calc_spike (line 480) | def calc_spike(self):
  class BackEINode (line 486) | class BackEINode(BaseNode):
    method __init__ (line 496) | def __init__(self, threshold=0.5, decay=0.2, act_fun=BackEIGateGrad, t...
    method integral (line 515) | def integral(self, inputs):
    method calc_spike (line 525) | def calc_spike(self):
    method n_reset (line 535) | def n_reset(self):
  class NoiseLIFNode (line 542) | class NoiseLIFNode(LIFNode):
    method __init__ (line 563) | def __init__(self,
    method integral (line 583) | def integral(self, inputs):  # b, c, w, h / b, c
  class BiasLIFNode (line 594) | class BiasLIFNode(BaseNode):
    method __init__ (line 614) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 621) | def integral(self, inputs):
    method calc_spike (line 624) | def calc_spike(self):
  class LIFSTDPNode (line 629) | class LIFSTDPNode(BaseNode):
    method __init__ (line 634) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 641) | def integral(self, inputs):
    method calc_spike (line 644) | def calc_spike(self):
    method requires_activation (line 649) | def requires_activation(self):
  class PLIFNode (line 653) | class PLIFNode(BaseNode):
    method __init__ (line 672) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 680) | def integral(self, inputs):
    method calc_spike (line 683) | def calc_spike(self):
  class PSU (line 688) | class PSU(BaseNode):
    method __init__ (line 689) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 703) | def integral(self, inputs):
    method calc_spike (line 707) | def calc_spike(self):
  class IPSU (line 711) | class IPSU(BaseNode):
    method masked_weight (line 712) | def masked_weight(self):
    method __init__ (line 715) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 736) | def integral(self, inputs):
    method calc_spike (line 740) | def calc_spike(self):
  class RPSU (line 744) | class RPSU(BaseNode):
    method masked_weight (line 745) | def masked_weight(self):
    method __init__ (line 748) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 769) | def integral(self, inputs):
    method calc_spike (line 774) | def calc_spike(self):
  class SPSN (line 778) | class SPSN(BaseNode):
    method __init__ (line 779) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 790) | def integral(self, inputs):
    method calc_spike (line 793) | def calc_spike(self):
  class NoisePLIFNode (line 797) | class NoisePLIFNode(PLIFNode):
    method __init__ (line 815) | def __init__(self,
    method integral (line 835) | def integral(self, inputs):  # b, c, w, h / b, c
  class BiasPLIFNode (line 845) | class BiasPLIFNode(BaseNode):
    method __init__ (line 863) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 871) | def integral(self, inputs):
    method calc_spike (line 874) | def calc_spike(self):
  class DoubleSidePLIFNode (line 879) | class DoubleSidePLIFNode(LIFNode):
    method __init__ (line 897) | def __init__(self,
    method calc_spike (line 908) | def calc_spike(self):
  class IzhNode (line 913) | class IzhNode(BaseNode):
    method __init__ (line 926) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 949) | def integral(self, inputs):
    method calc_spike (line 953) | def calc_spike(self):
    method n_reset (line 958) | def n_reset(self):
  class IzhNodeMU (line 964) | class IzhNodeMU(BaseNode):
    method __init__ (line 977) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 991) | def integral(self, inputs):
    method calc_spike (line 995) | def calc_spike(self):
    method n_reset (line 1000) | def n_reset(self):
    method requires_activation (line 1005) | def requires_activation(self):
  class DGLIFNode (line 1009) | class DGLIFNode(BaseNode):
    method __init__ (line 1016) | def __init__(self, threshold=.5, tau=2., *args, **kwargs):
    method integral (line 1021) | def integral(self, inputs):
    method calc_spike (line 1025) | def calc_spike(self):
  class HTDGLIFNode (line 1035) | class HTDGLIFNode(IFNode):
    method __init__ (line 1042) | def __init__(self, threshold=.5, tau=2., *args, **kwargs):
    method calc_spike (line 1046) | def calc_spike(self):
    method forward (line 1058) | def forward(self, inputs):
  class SimHHNode (line 1065) | class SimHHNode(BaseNode):
    method __init__ (line 1078) | def __init__(self, threshold=50., tau=2., act_fun=AtanGrad, *args, **k...
    method integral (line 1093) | def integral(self, inputs):
    method calc_spike (line 1116) | def calc_spike(self):
    method forward (line 1120) | def forward(self, inputs):
    method n_reset (line 1125) | def n_reset(self):
    method requires_activation (line 1130) | def requires_activation(self):
  class CTIzhNode (line 1134) | class CTIzhNode(IzhNode):
    method __init__ (line 1135) | def __init__(self, threshold=1., tau=2., act_fun=AtanGrad, *args, **kw...
    method integral (line 1163) | def integral(self, inputs):
    method calc_spike (line 1168) | def calc_spike(self):
    method spreadMarkPostNeurons (line 1175) | def spreadMarkPostNeurons(self):
  class adth (line 1183) | class adth(BaseNode):
    method __init__ (line 1190) | def __init__(self, *args, **kwargs):
    method adthNode (line 1193) | def adthNode(self, v, dt, c_m, g_m, alpha_w, ad, Ieff, Ichem, Igap, ta...
    method calc_spike (line 1207) | def calc_spike(self):
  class HHNode (line 1211) | class HHNode(BaseNode):
    method __init__ (line 1218) | def __init__(self, p, dt, device, act_fun=AtanGrad, *args, **kwargs):
    method integral (line 1251) | def integral(self, inputs):
    method calc_spike (line 1271) | def calc_spike(self):
    method forward (line 1274) | def forward(self, inputs):
    method requires_activation (line 1279) | def requires_activation(self):
  class aEIF (line 1283) | class aEIF(BaseNode):
    method __init__ (line 1291) | def __init__(self, p, dt, device, *args, **kwargs):
    method integral (line 1321) | def integral(self, inputs):
    method calc_spike (line 1331) | def calc_spike(self):
    method forward (line 1337) | def forward(self, inputs):
  class LIAFNode (line 1345) | class LIAFNode(BaseNode):
    method __init__ (line 1353) | def __init__(self, spike_act=BackEIGateGrad(), act_fun="SELU", thresho...
    method integral (line 1362) | def integral(self, inputs):
    method calc_spike (line 1365) | def calc_spike(self):
  class OnlineLIFNode (line 1376) | class OnlineLIFNode(BaseNode):
    method __init__ (line 1387) | def __init__(self, threshold=0.5, tau=2., act_fun=QGateGrad, init=Fals...
    method integral (line 1397) | def integral(self, inputs):
    method calc_spike (line 1403) | def calc_spike(self):
  class AdaptiveNode (line 1412) | class AdaptiveNode(LIFNode):
    method __init__ (line 1414) | def __init__(self, threshold=1., act_fun=QGateGrad, step=10, spike_out...
    method init_weight (line 1459) | def init_weight(self):
    method forward (line 1466) | def forward(self, inputs):  # (t b) c w h
    method n_reset (line 1500) | def n_reset(self):

FILE: braincog/base/strategy/LateralInhibition.py
  class LateralInhibition (line 7) | class LateralInhibition(nn.Module):
    method __init__ (line 11) | def __init__(self, node, inh, mode="constant"):
    method forward (line 17) | def forward(self, x: torch.Tensor, xori=None):

FILE: braincog/base/strategy/surrogate.py
  function heaviside (line 8) | def heaviside(x):
  class SurrogateFunctionBase (line 12) | class SurrogateFunctionBase(nn.Module):
    method __init__ (line 19) | def __init__(self, alpha, requires_grad=True):
    method act_fun (line 26) | def act_fun(x, alpha):
    method forward (line 34) | def forward(self, x):
  class sigmoid (line 47) | class sigmoid(torch.autograd.Function):
    method forward (line 62) | def forward(ctx, x, alpha):
    method backward (line 69) | def backward(ctx, grad_output):
  class SigmoidGrad (line 77) | class SigmoidGrad(SurrogateFunctionBase):
    method __init__ (line 78) | def __init__(self, alpha=1., requires_grad=False):
    method act_fun (line 82) | def act_fun(x, alpha):
  class atan (line 91) | class atan(torch.autograd.Function):
    method forward (line 106) | def forward(ctx, inputs, alpha):
    method backward (line 111) | def backward(ctx, grad_output):
  class AtanGrad (line 126) | class AtanGrad(SurrogateFunctionBase):
    method __init__ (line 127) | def __init__(self, alpha=2., requires_grad=True):
    method act_fun (line 131) | def act_fun(x, alpha):
  class gate (line 140) | class gate(torch.autograd.Function):
    method forward (line 155) | def forward(ctx, x, alpha):
    method backward (line 162) | def backward(ctx, grad_output):
  class GateGrad (line 169) | class GateGrad(SurrogateFunctionBase):
    method __init__ (line 170) | def __init__(self, alpha=2., requires_grad=False):
    method act_fun (line 174) | def act_fun(x, alpha):
  class quadratic_gate (line 183) | class quadratic_gate(torch.autograd.Function):
    method forward (line 208) | def forward(ctx, x, alpha):
    method backward (line 217) | def backward(ctx, grad_output):
  class QGateGrad (line 224) | class QGateGrad(SurrogateFunctionBase):
    method __init__ (line 225) | def __init__(self, alpha=2., requires_grad=False):
    method act_fun (line 229) | def act_fun(x, alpha):
  class relu_like (line 233) | class relu_like(torch.autograd.Function):
    method forward (line 235) | def forward(ctx, x, alpha):
    method backward (line 241) | def backward(ctx, grad_output):
  class RoundGrad (line 250) | class RoundGrad(nn.Module):
    method __init__ (line 251) | def __init__(self, **kwargs):
    method forward (line 255) | def forward(self, x):
  class ReLUGrad (line 259) | class ReLUGrad(SurrogateFunctionBase):
    method __init__ (line 264) | def __init__(self, alpha=2., requires_grad=False):
    method act_fun (line 268) | def act_fun(x, alpha):
  class straight_through_estimator (line 277) | class straight_through_estimator(torch.autograd.Function):
    method forward (line 284) | def forward(ctx, inputs):
    method backward (line 290) | def backward(ctx, grad_output):
  class stdp (line 297) | class stdp(torch.autograd.Function):
    method forward (line 299) | def forward(ctx, inputs):
    method backward (line 305) | def backward(ctx, grad_output):
  class STDPGrad (line 310) | class STDPGrad(SurrogateFunctionBase):
    method __init__ (line 311) | def __init__(self, alpha=2., requires_grad=False):
    method act_fun (line 315) | def act_fun(x, alpha):
  class backeigate (line 322) | class backeigate(torch.autograd.Function):
    method forward (line 324) | def forward(ctx, input):
    method backward (line 329) | def backward(ctx, grad_output):
  class BackEIGateGrad (line 336) | class BackEIGateGrad(SurrogateFunctionBase):
    method __init__ (line 337) | def __init__(self, alpha=2., requires_grad=False):
    method act_fun (line 341) | def act_fun(x, alpha):
  class ei (line 344) | class ei(torch.autograd.Function):
    method forward (line 346) | def forward(ctx, input):
    method backward (line 351) | def backward(ctx, grad_output):
  class EIGrad (line 358) | class EIGrad(SurrogateFunctionBase):
    method __init__ (line 359) | def __init__(self, alpha=2., requires_grad=False):
    method act_fun (line 363) | def act_fun(x, alpha):

FILE: braincog/base/utils/__init__.py
  function drop_path (line 12) | def drop_path(x, drop_prob):

FILE: braincog/base/utils/criterions.py
  class UnilateralMse (line 5) | class UnilateralMse(torch.nn.Module):
    method __init__ (line 10) | def __init__(self, thresh=1.):
    method forward (line 15) | def forward(self, x, target):
  class MixLoss (line 23) | class MixLoss(torch.nn.Module):
    method __init__ (line 28) | def __init__(self, ce_loss):
    method forward (line 33) | def forward(self, x, target):
  class TetLoss (line 37) | class TetLoss(torch.nn.Module):
    method __init__ (line 38) | def __init__(self, loss_fn):
    method forward (line 42) | def forward(self, x, target):
  class OnehotMse (line 50) | class OnehotMse(torch.nn.Module):
    method __init__ (line 54) | def __init__(self, num_class):
    method forward (line 59) | def forward(self, x, target):

FILE: braincog/base/utils/visualization.py
  function spike_rate_vis_1d (line 31) | def spike_rate_vis_1d(data, output_dir=''):
  function spike_rate_vis (line 46) | def spike_rate_vis(data, output_dir=''):
  function plot_mem_distribution (line 61) | def plot_mem_distribution(data,
  function plot_tsne (line 113) | def plot_tsne(x, colors,output_dir="", num_classes=None):
  function plot_tsne_3d (line 141) | def plot_tsne_3d(x, colors,output_dir="", num_classes=None):
  function plot_confusion_matrix (line 178) | def plot_confusion_matrix(logits, labels, output_dir):

FILE: braincog/datasets/CUB2002011.py
  class CUB2002011 (line 9) | class CUB2002011(VisionDataset):
    method __init__ (line 29) | def __init__(self, root, train=True, transform=None, target_transform=...
    method _load_metadata (line 40) | def _load_metadata(self):
    method _check_integrity (line 59) | def _check_integrity(self):
    method _download (line 72) | def _download(self):
    method __len__ (line 84) | def __len__(self):
    method __getitem__ (line 87) | def __getitem__(self, idx):

FILE: braincog/datasets/ESimagenet/ES_imagenet.py
  class ESImagenet_Dataset (line 13) | class ESImagenet_Dataset(data.Dataset):
    method __init__ (line 14) | def __init__(self, mode, data_set_path='/data/dvsimagenet/', transform...
    method __getitem__ (line 39) | def __getitem__(self, index):
    method __len__ (line 74) | def __len__(self):

FILE: braincog/datasets/ESimagenet/reconstructed_ES_imagenet.py
  class ESImagenet2D_Dataset (line 14) | class ESImagenet2D_Dataset(data.Dataset):
    method __init__ (line 15) | def __init__(self, mode, data_set_path='/data/ESimagenet-0.18/', trans...
    method __getitem__ (line 44) | def __getitem__(self, index):
    method __len__ (line 90) | def __len__(self):

FILE: braincog/datasets/NOmniglot/NOmniglot.py
  class NOmniglot (line 5) | class NOmniglot(Dataset):
    method __init__ (line 6) | def __init__(self, root='data/', frames_num=12, train=True, data_type=...
    method __len__ (line 40) | def __len__(self):
    method __getitem__ (line 43) | def __getitem__(self, index):
    method readimage (line 48) | def readimage(self, image, label):

FILE: braincog/datasets/NOmniglot/nomniglot_full.py
  class NOmniglotfull (line 6) | class NOmniglotfull(Dataset):
    method __init__ (line 12) | def __init__(self, root='data/', train=True, frames_num=4, data_type='...
    method __len__ (line 29) | def __len__(self):
    method __getitem__ (line 32) | def __getitem__(self, index):

FILE: braincog/datasets/NOmniglot/nomniglot_nw_ks.py
  class NOmniglotNWayKShot (line 8) | class NOmniglotNWayKShot(Dataset):
    method __init__ (line 15) | def __init__(self, root, n_way, k_shot, k_query, train=True, frames_nu...
    method load_data_cache (line 26) | def load_data_cache(self, data_dict, length):
    method __getitem__ (line 51) | def __getitem__(self, index):
    method reset (line 65) | def reset(self):
    method __len__ (line 68) | def __len__(self):

FILE: braincog/datasets/NOmniglot/nomniglot_pair.py
  class NOmniglotTrainSet (line 10) | class NOmniglotTrainSet(Dataset):
    method __init__ (line 16) | def __init__(self, root='data/', use_frame=True, frames_num=10, data_t...
    method __len__ (line 26) | def __len__(self):
    method __getitem__ (line 32) | def __getitem__(self, index):
  class NOmniglotTestSet (line 68) | class NOmniglotTestSet(Dataset):
    method __init__ (line 74) | def __init__(self, root='data/', time=1000, way=20, shot=1, query=1, u...
    method __len__ (line 93) | def __len__(self):
    method __getitem__ (line 100) | def __getitem__(self, index):

FILE: braincog/datasets/NOmniglot/utils.py
  class FunctionThread (line 9) | class FunctionThread(threading.Thread):
    method __init__ (line 10) | def __init__(self, f, *args, **kwargs):
    method run (line 16) | def run(self):
  function integrate_events_to_frames (line 20) | def integrate_events_to_frames(events, height, width, frames_num=10, dat...
  function normalize_frame (line 71) | def normalize_frame(frames: np.ndarray or torch.Tensor, normalization: s...
  function convert_events_dir_to_frames_dir (line 91) | def convert_events_dir_to_frames_dir(events_data_dir, frames_data_dir, s...
  function convert_aedat4_dir_to_events_dir (line 135) | def convert_aedat4_dir_to_events_dir(root, train):
  function num2str (line 178) | def num2str(idx):
  function list_all_files (line 184) | def list_all_files(root, suffix, getlen=False):
  function list_class_files (line 207) | def list_class_files(root, frames_kind_root, getlen=False, use_npz=False):

FILE: braincog/datasets/StanfordDogs.py
  class StanfordDogs (line 9) | class StanfordDogs(VisionDataset):
    method __init__ (line 25) | def __init__(self, root, train=True, transform=None, target_transform=...
    method __len__ (line 44) | def __len__(self):
    method __getitem__ (line 47) | def __getitem__(self, index):
    method download (line 58) | def download(self):
    method load_split (line 75) | def load_split(self):
    method stats (line 87) | def stats(self):

FILE: braincog/datasets/TinyImageNet.py
  class TinyImageNet (line 12) | class TinyImageNet(VisionDataset):
    method __init__ (line 30) | def __init__(self, root, split='train', transform=None, target_transfo...
    method _download (line 52) | def _download(self):
    method _check_integrity (line 58) | def _check_integrity(self):
    method __getitem__ (line 61) | def __getitem__(self, index):
    method __len__ (line 72) | def __len__(self):
  function find_classes (line 76) | def find_classes(class_file):
  function make_dataset (line 86) | def make_dataset(root, base_folder, dirname, class_to_idx):

FILE: braincog/datasets/__init__.py
  function is_dvs_data (line 33) | def is_dvs_data(dataset):

FILE: braincog/datasets/bullying10k/bullying10k.py
  class BULLYINGDVS (line 11) | class BULLYINGDVS(Dataset):
    method __init__ (line 20) | def __init__(self, save_to, transform=None, target_transform=None):
    method __getitem__ (line 40) | def __getitem__(self, index: int) -> Tuple[Any, Any]:
    method __len__ (line 67) | def __len__(self):
    method _check_exists (line 70) | def _check_exists(self):

FILE: braincog/datasets/cut_mix.py
  function event_difference (line 11) | def event_difference(x1, x2, kernel_size=3):
  function onehot (line 18) | def onehot(size, target):
  function rand_bbox_time (line 24) | def rand_bbox_time(size, rat):
  function rand_bbox (line 38) | def rand_bbox(size, rat):
  function calc_lam (line 61) | def calc_lam(x1, x2, bbt1, bbt2, bbx1, bbx2, bby1, bby2):
  function rand_bbox_st (line 72) | def rand_bbox_st(size, rat):
  function spatio_mask (line 80) | def spatio_mask(size, rat):
  function temporal_mask (line 94) | def temporal_mask(size, rat):
  function st_mask (line 101) | def st_mask(size, rat):
  function GMM_mask_clip (line 112) | def GMM_mask_clip(size, rat):
  function GMM_mask (line 123) | def GMM_mask(size, rat, n=None):
  function calc_masked_lam (line 188) | def calc_masked_lam(x1, x2, mask):
  function calc_masked_lam_with_difference (line 200) | def calc_masked_lam_with_difference(x1, x2, mix, kernel_size=3):
  class MixUp (line 206) | class MixUp(Dataset):
    method __init__ (line 207) | def __init__(self, dataset, num_class, num_mix=1, beta=1., prob=1.0, i...
    method __getitem__ (line 217) | def __getitem__(self, index):
    method __len__ (line 251) | def __len__(self):
  class CutMix (line 255) | class CutMix(Dataset):
    method __init__ (line 257) | def __init__(self, dataset, num_class, num_mix=1, beta=1., prob=1.0, i...
    method __getitem__ (line 267) | def __getitem__(self, index):
    method __len__ (line 333) | def __len__(self):
  class EventMix (line 337) | class EventMix(Dataset):
    method __init__ (line 339) | def __init__(self,
    method __getitem__ (line 361) | def __getitem__(self, index):
    method __len__ (line 420) | def __len__(self):
  function get_proj (line 430) | def get_proj(self):

FILE: braincog/datasets/datasets.py
  function unpack_mix_param (line 48) | def unpack_mix_param(args):
  function build_transform (line 61) | def build_transform(is_train, img_size):
  function build_dataset (line 105) | def build_dataset(is_train, img_size, dataset, path, same_da=False):
  class MNISTData (line 131) | class MNISTData(object):
    method __init__ (line 136) | def __init__(self,
    method get_data_loaders (line 153) | def get_data_loaders(self):
    method get_standard_data (line 167) | def get_standard_data(self):
  function get_mnist_data (line 178) | def get_mnist_data(batch_size, num_workers=8, same_da=False,root=DATA_DI...
  function get_fashion_data (line 225) | def get_fashion_data(batch_size, num_workers=8, same_da=False,root=DATA_...
  function get_cifar10_data (line 258) | def get_cifar10_data(batch_size, num_workers=8, same_da=False,root=DATA_...
  function get_cifar100_data (line 283) | def get_cifar100_data(batch_size, num_workers=8, same_data=False,root=DA...
  function get_TinyImageNet_data (line 305) | def get_TinyImageNet_data(batch_size, num_workers=8, same_da=False,root=...
  function get_imnet_data (line 338) | def get_imnet_data(args, _logger, data_config, num_aug_splits,root=DATA_...
  function get_dvsg_data (line 428) | def get_dvsg_data(batch_size, step,root=DATA_DIR, **kwargs):
  function get_bullyingdvs_data (line 528) | def get_bullyingdvs_data(batch_size, step, root=DATA_DIR, **kwargs):
  function get_dvsc10_data (line 634) | def get_dvsc10_data(batch_size, step, root=DATA_DIR, **kwargs):
  function get_NCALTECH101_data (line 755) | def get_NCALTECH101_data(batch_size, step,root=DATA_DIR, **kwargs):
  function get_NCARS_data (line 884) | def get_NCARS_data(batch_size, step,root=DATA_DIR, **kwargs):
  function get_nomni_data (line 982) | def get_nomni_data(batch_size, train_portion=1.,root=DATA_DIR, **kwargs):
  function get_esimnet_data (line 1045) | def get_esimnet_data(batch_size, step,root=DATA_DIR, **kwargs):
  function get_nmnist_data (line 1133) | def get_nmnist_data(batch_size, step, **kwargs):
  function get_ntidigits_data (line 1233) | def get_ntidigits_data(batch_size, step, **kwargs):
  function get_shd_data (line 1277) | def get_shd_data(batch_size, step, **kwargs):
  function get_CUB2002011_data (line 1333) | def get_CUB2002011_data(batch_size, num_workers=8, same_da=False,root=DA...
  function get_StanfordCars_data (line 1364) | def get_StanfordCars_data(batch_size, num_workers=8, same_da=False,root=...
  function get_StanfordDogs_data (line 1395) | def get_StanfordDogs_data(batch_size, num_workers=8, same_da=False,root=...
  function get_FGVCAircraft_data (line 1427) | def get_FGVCAircraft_data(batch_size, num_workers=8, same_da=False,root=...
  function get_Flowers102_data (line 1459) | def get_Flowers102_data(batch_size, num_workers=8, same_da=False,root=DA...
  function get_UCF101DVS_data (line 1491) | def get_UCF101DVS_data(batch_size, step, **kwargs):
  function get_HMDBDVS_data (line 1597) | def get_HMDBDVS_data(batch_size, step, **kwargs):

FILE: braincog/datasets/hmdb_dvs/hmdb_dvs.py
  class HMDBDVS (line 18) | class HMDBDVS(Dataset):
    method __init__ (line 40) | def __init__(self, save_to, transform=None, target_transform=None):
    method __getitem__ (line 69) | def __getitem__(self, index: int) -> Tuple[Any, Any]:
    method __len__ (line 90) | def __len__(self):
    method _check_exists (line 93) | def _check_exists(self):

FILE: braincog/datasets/ncaltech101/ncaltech101.py
  class NCALTECH101 (line 17) | class NCALTECH101(Dataset):
    method __init__ (line 60) | def __init__(self, save_to, transform=None, target_transform=None):
    method __getitem__ (line 187) | def __getitem__(self, index):
    method __len__ (line 202) | def __len__(self):
    method _check_exists (line 205) | def _check_exists(self):

FILE: braincog/datasets/rand_aug.py
  function ShearX (line 9) | def ShearX(x, v):  # [-0.3, 0.3]
  function ShearY (line 17) | def ShearY(x, v):  # [-0.3, 0.3]
  function TranslateX (line 25) | def TranslateX(x, v):
  function TranslateY (line 35) | def TranslateY(x, v):
  function Rotate (line 45) | def Rotate(x, v):  # [-30, 30]
  function CutoutAbs (line 53) | def CutoutAbs(x, v):  # [0, 60] => percentage: [0, 0.2]
  function CutoutTemporal (line 70) | def CutoutTemporal(x, v):
  function TemporalShift (line 81) | def TemporalShift(x, v):
  function SpatioShift (line 115) | def SpatioShift(x, v):
  function drop (line 133) | def drop(x, v):
  function GaussianBlur (line 147) | def GaussianBlur(x, v):
  function SaltAndPepperNoise (line 153) | def SaltAndPepperNoise(x, v):
  function Identity (line 161) | def Identity(x, v):
  class RandAugment (line 182) | class RandAugment:
    method __init__ (line 183) | def __init__(self, n, m):
    method __call__ (line 188) | def __call__(self, x):

FILE: braincog/datasets/ucf101_dvs/ucf101_dvs.py
  class UCF101DVS (line 27) | class UCF101DVS(Dataset):
    method __init__ (line 49) | def __init__(self, save_to, train=False, transform=None, target_transf...
    method __getitem__ (line 80) | def __getitem__(self, index: int) -> Tuple[Any, Any]:
    method __len__ (line 101) | def __len__(self):
    method _check_exists (line 104) | def _check_exists(self):

FILE: braincog/datasets/utils.py
  function rescale (line 6) | def rescale(x, factor=None):
  function dvs_channel_check_expend (line 20) | def dvs_channel_check_expend(x):

FILE: braincog/model_zoo/NeuEvo/__init__.py
  function parse (line 25) | def parse(weights, operation_set,
  function parse_genotype (line 142) | def parse_genotype(alphas, steps, multiplier, path=None,

FILE: braincog/model_zoo/NeuEvo/architect.py
  function normalize (line 9) | def normalize(x):
  function _concat (line 15) | def _concat(xs):
  class Architect (line 19) | class Architect(object):
    method __init__ (line 20) | def __init__(self, model, args):
    method step (line 33) | def step(self, input_valid, target_valid):
    method compute_Hw (line 43) | def compute_Hw(self, input_valid, target_valid):
    method zero_grads (line 52) | def zero_grads(self, parameters):
    method compute_eigenvalues (line 58) | def compute_eigenvalues(self):
    method _hessian (line 62) | def _hessian(self, outputs, inputs, out=None, allow_unused=False):

FILE: braincog/model_zoo/NeuEvo/model.py
  class MlpCell (line 13) | class MlpCell(BaseModule):
    method __init__ (line 14) | def __init__(
    method _compile (line 50) | def _compile(self, C, op_names, indices, concat):
    method _forward_once (line 81) | def _forward_once(self, s0, s1, drop_prob):
    method forward (line 111) | def forward(self, inputs):
  class Cell (line 126) | class Cell(nn.Module):
    method __init__ (line 127) | def __init__(self, genotype, C_prev_prev, C_prev, C, reduction, reduct...
    method _compile (line 151) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 183) | def forward(self, s0, s1, drop_prob):
  class DCOCell (line 216) | class DCOCell(nn.Module):
    method __init__ (line 217) | def __init__(self, genotype, C_prev_prev, C_prev, C, reduction, reduct...
    method _compile (line 233) | def _compile(self, C, op_names, tos, froms, reduction):
    method forward (line 252) | def forward(self, s0, s1, drop_prob):
  class AuxiliaryHeadCIFAR (line 280) | class AuxiliaryHeadCIFAR(nn.Module):
    method __init__ (line 281) | def __init__(self, C, num_classes, act_fun):
    method forward (line 301) | def forward(self, x):
  class AuxiliaryHeadImageNet (line 307) | class AuxiliaryHeadImageNet(nn.Module):
    method __init__ (line 309) | def __init__(self, C, num_classes):
    method forward (line 326) | def forward(self, x):
  class NetworkCIFAR (line 333) | class NetworkCIFAR(BaseModule):
    method __init__ (line 335) | def __init__(self,
    method forward (line 436) | def forward(self, inputs):
  class NetworkImageNet (line 474) | class NetworkImageNet(BaseModule):
    method __init__ (line 476) | def __init__(self,
    method forward (line 549) | def forward(self, inputs):

FILE: braincog/model_zoo/NeuEvo/model_search.py
  function calc_weight (line 15) | def calc_weight(x):
  function calc_loss (line 27) | def calc_loss(x):
  class darts_fun (line 39) | class darts_fun(torch.autograd.Function):
    method forward (line 41) | def forward(ctx, inputs, weights):  # feature map / arch weight
    method backward (line 47) | def backward(ctx, grad_output):  # error signal
  class MixedOp (line 64) | class MixedOp(nn.Module):
    method __init__ (line 65) | def __init__(self, C, stride, act_fun):
    method forward (line 76) | def forward(self, x, weights):
  class Cell (line 84) | class Cell(nn.Module):
    method __init__ (line 86) | def __init__(self, steps, multiplier, C_prev_prev, C_prev, C, reductio...
    method forward (line 121) | def forward(self, s0, s1, weights):
  class Network (line 153) | class Network(BaseModule):
    method __init__ (line 155) | def __init__(self, C, num_classes, layers, criterion, steps=4, multipl...
    method new (line 228) | def new(self):
    method forward (line 235) | def forward(self, inputs):
    method reset_fire_rate_record (line 261) | def reset_fire_rate_record(self):
    method get_fire_per_step (line 265) | def get_fire_per_step(self):
    method _loss (line 268) | def _loss(self, input1, target1, input2):
    method _initialize_alphas (line 275) | def _initialize_alphas(self):
    method arch_parameters (line 301) | def arch_parameters(self):
    method genotype (line 304) | def genotype(self):
    method states (line 317) | def states(self):
    method restore (line 324) | def restore(self, states):
    method update_history (line 328) | def update_history(self):

FILE: braincog/model_zoo/NeuEvo/operations.py
  function si_relu (line 15) | def si_relu(x, positive):
  class SiReLU (line 26) | class SiReLU(nn.Module):
    method __init__ (line 27) | def __init__(self, positive=0):
    method forward (line 31) | def forward(self, x):
  function weight_init (line 35) | def weight_init(m):
  class SiMLP (line 154) | class SiMLP(nn.Module):
    method __init__ (line 155) | def __init__(self, c_in, c_out, act_fun=nn.ReLU, positive=0, *args, **...
    method forward (line 163) | def forward(self, x):
  class ReLUConvBN (line 168) | class ReLUConvBN(nn.Module):
    method __init__ (line 173) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 186) | def forward(self, x):
  class DilConv (line 191) | class DilConv(nn.Module):
    method __init__ (line 196) | def __init__(self, C_in, C_out, kernel_size, stride, padding, dilation...
    method forward (line 210) | def forward(self, x):
  class SepConv (line 215) | class SepConv(nn.Module):
    method __init__ (line 217) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 236) | def forward(self, x):
  class Identity (line 241) | class Identity(nn.Module):
    method __init__ (line 243) | def __init__(self, positive=0):
    method forward (line 247) | def forward(self, x):
  class Zero (line 251) | class Zero(nn.Module):
    method __init__ (line 253) | def __init__(self, stride):
    method forward (line 257) | def forward(self, x):
  class FactorizedReduce (line 263) | class FactorizedReduce(nn.Module):
    method __init__ (line 265) | def __init__(self, C_in, C_out, affine=True, act_fun=nn.ReLU, positive...
    method forward (line 279) | def forward(self, x):
  class DeformConv (line 288) | class DeformConv(nn.Module):
    method __init__ (line 289) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 302) | def forward(self, x):
  class Attention (line 307) | class Attention(Module):
    method __init__ (line 312) | def __init__(self, dim, num_heads=4, attention_dropout=0.1, projection...
    method forward (line 323) | def forward(self, x):
  class TransformerEncoderLayer (line 339) | class TransformerEncoderLayer(Module):
    method __init__ (line 345) | def __init__(self, d_model, nhead=4, dim_feedforward=256, dropout=0.1,
    method forward (line 363) | def forward(self, src: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  function drop_path (line 376) | def drop_path(x, drop_prob: float = 0., training: bool = False):
  class DropPath (line 398) | class DropPath(Module):
    method __init__ (line 404) | def __init__(self, drop_prob=None):
    method forward (line 408) | def forward(self, x):

FILE: braincog/model_zoo/NeuEvo/others.py
  class CIFARNet_Wu (line 22) | class CIFARNet_Wu(BaseModule):
    method __init__ (line 24) | def __init__(
    method forward (line 67) | def forward(self, inputs):
  class CIFARNet_Fang (line 79) | class CIFARNet_Fang(BaseModule):
    method __init__ (line 81) | def __init__(
    method forward (line 119) | def forward(self, inputs):
  class DVS_CIFARNet_Fang (line 132) | class DVS_CIFARNet_Fang(BaseModule):
    method __init__ (line 134) | def __init__(
    method forward (line 172) | def forward(self, inputs):

FILE: braincog/model_zoo/backeinet.py
  class MNISTNet (line 8) | class MNISTNet(BaseModule):
    method __init__ (line 9) | def __init__(self, step=20, encode_type='rate', if_back=True, if_ei=Tr...
    method forward (line 39) | def forward(self, inputs):
  class CIFARNet (line 54) | class CIFARNet(BaseModule):
    method __init__ (line 55) | def __init__(self, step=20, encode_type='rate', if_back=True, if_ei=Tr...
    method forward (line 84) | def forward(self, inputs):

FILE: braincog/model_zoo/base_module.py
  class BaseLinearModule (line 8) | class BaseLinearModule(nn.Module):
    method __init__ (line 18) | def __init__(self,
    method forward (line 43) | def forward(self, x):
  class BaseConvModule (line 58) | class BaseConvModule(nn.Module):
    method __init__ (line 70) | def __init__(self,
    method forward (line 100) | def forward(self, x):
  class BaseModule (line 113) | class BaseModule(nn.Module, abc.ABC):
    method __init__ (line 123) | def __init__(self,
    method reset (line 151) | def reset(self):
    method set_attr (line 160) | def set_attr(self, attr, val):
    method get_threshold (line 174) | def get_threshold(self):
    method get_fp (line 186) | def get_fp(self, temporal_info=False):
    method get_mem (line 201) | def get_mem(self, temporal_info=False):
    method get_fire_rate (line 216) | def get_fire_rate(self, requires_grad=False):
    method get_tot_spike (line 235) | def get_tot_spike(self):
    method get_spike_info (line 250) | def get_spike_info(self):
    method set_requires_fp (line 276) | def set_requires_fp(self, flag):
    method set_requires_mem (line 281) | def set_requires_mem(self, flag):
    method get_attr (line 286) | def get_attr(self, attr):
    method forward (line 299) | def forward(self, inputs):
  class DeformConvPack (line 303) | class DeformConvPack(nn.Module):
    method __init__ (line 304) | def __init__(self,
    method init_weights (line 342) | def init_weights(self):
    method forward (line 347) | def forward(self, x):

FILE: braincog/model_zoo/bdmsnn.py
  class BDMSNN (line 17) | class BDMSNN(nn.Module):
    method __init__ (line 18) | def __init__(self, num_state, num_action, weight_exc, weight_inh, node...
    method forward (line 79) | def forward(self, input):
    method UpdateWeight (line 100) | def UpdateWeight(self, i, s, num_action, dw):
    method reset (line 124) | def reset(self):
    method getweight (line 134) | def getweight(self):

FILE: braincog/model_zoo/convnet.py
  class BaseConvNet (line 12) | class BaseConvNet(BaseModule, abc.ABC):
    method __init__ (line 13) | def __init__(self,
    method _create_feature (line 56) | def _create_feature(self):
    method _create_fc (line 60) | def _create_fc(self):
    method forward (line 63) | def forward(self, inputs):
  class MNISTConvNet (line 102) | class MNISTConvNet(BaseConvNet):
    method __init__ (line 103) | def __init__(self,
    method _create_feature (line 126) | def _create_feature(self):
    method _create_fc (line 153) | def _create_fc(self):
  class CifarConvNet (line 165) | class CifarConvNet(BaseConvNet):
    method __init__ (line 166) | def __init__(self,
    method _create_feature (line 188) | def _create_feature(self):
    method _create_fc (line 220) | def _create_fc(self):
  function mnist_convnet (line 230) | def mnist_convnet(step,
  function cifar_convnet (line 255) | def cifar_convnet(step,
  function dvs_convnet (line 283) | def dvs_convnet(step,

FILE: braincog/model_zoo/fc_snn.py
  class STSC_Attention (line 12) | class STSC_Attention(nn.Module):
    method __init__ (line 13) | def __init__(self, n_channel: int, dimension: int = 2, time_rf: int = ...
    method forward (line 34) | def forward(self, x_seq: torch.Tensor):
  class STSC_Temporal_Conv (line 58) | class STSC_Temporal_Conv(nn.Module):
    method __init__ (line 59) | def __init__(self, channels: int, dimension: int = 2, time_rf: int = 2):
    method forward (line 78) | def forward(self, x_seq: torch.Tensor):
  class STSC (line 93) | class STSC(nn.Module):
    method __init__ (line 94) | def __init__(self, in_channel: int, dimension: int = 2, time_rf_conv: ...
    method forward (line 115) | def forward(self, x_seq: torch.Tensor):
  class SHD_SNN (line 147) | class SHD_SNN(BaseModule):
    method __init__ (line 153) | def __init__(self,
    method forward (line 183) | def forward(self, inputs):

FILE: braincog/model_zoo/glsnn.py
  class BaseGLSNN (line 12) | class BaseGLSNN(BaseModule):
    method __init__ (line 20) | def __init__(self, input_size=784, hidden_sizes=[800] * 3, output_size...
    method forward (line 41) | def forward(self, x):
    method feedback (line 57) | def feedback(self, ff_value, y_label):
    method set_gradient (line 74) | def set_gradient(self, x, y):
    method forward_parameters (line 94) | def forward_parameters(self):
    method feedback_parameters (line 100) | def feedback_parameters(self):

FILE: braincog/model_zoo/linearNet.py
  class droDMTrainNet (line 8) | class droDMTrainNet(nn.Module):
    method __init__ (line 13) | def __init__(self, connection):
    method forward (line 33) | def forward(self, input):
    method UpdateWeight (line 44) | def UpdateWeight(self, i, dw):
    method reset (line 54) | def reset(self):
    method getweight (line 64) | def getweight(self):

FILE: braincog/model_zoo/nonlinearNet.py
  class droDMTestNet (line 8) | class droDMTestNet(nn.Module):
    method __init__ (line 13) | def __init__(self, connection):
    method forward (line 36) | def forward(self, input, input_da):
    method UpdateWeight (line 49) | def UpdateWeight(self, i, dw):
    method reset (line 59) | def reset(self):
    method getweight (line 69) | def getweight(self):

FILE: braincog/model_zoo/qsnn.py
  function sigma (line 34) | def sigma(x):
  function deriv_sigma (line 41) | def deriv_sigma(x):
  function kappa (line 52) | def kappa(x):
  function get_kappas (line 56) | def get_kappas(n):
  class Net (line 71) | class Net(nn.Module):
    method __init__ (line 75) | def __init__(self, net_size):
    method update_state (line 83) | def update_state(self, input_, label, test):
    method routine (line 95) | def routine(self,
    method update_weight (line 125) | def update_weight(self, lr, t, beta, eps):
    method predict (line 134) | def predict(self,
  class Hidden_layer (line 156) | class Hidden_layer(nn.Module):
    method __init__ (line 160) | def __init__(self, input_size, neu_num, fb_neus):
    method update_state (line 179) | def update_state(self, basal_input, apical_input, test):
    method update_weight (line 185) | def update_weight(self, delta_, lr, t, beta, eps):
  class Output_layer (line 205) | class Output_layer(nn.Module):
    method __init__ (line 209) | def __init__(self, input_size, neu_num):
    method update_state (line 229) | def update_state(self, basal_input, I, test):
    method update_weight (line 239) | def update_weight(self, lr, t, beta, eps):

FILE: braincog/model_zoo/resnet.py
  function conv3x3 (line 29) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 41) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 50) | class BasicBlock(nn.Module):
    method __init__ (line 66) | def __init__(self,
    method forward (line 97) | def forward(self, x):
  class Bottleneck (line 116) | class Bottleneck(nn.Module):
    method __init__ (line 132) | def __init__(self,
    method forward (line 163) | def forward(self, x):
  class ResNet (line 185) | class ResNet(BaseModule):
    method __init__ (line 203) | def __init__(self,
    method _make_layer (line 352) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False, n...
    method forward (line 389) | def forward(self, inputs):
  function _resnet (line 446) | def _resnet(arch, block, layers, pretrained=False, **kwargs):
  function resnet9 (line 456) | def resnet9(pretrained=False, **kwargs):
  function resnet18 (line 461) | def resnet18(pretrained=False, **kwargs):
  function resnet34_half (line 467) | def resnet34_half(pretrained=False, **kwargs):
  function resnet34 (line 474) | def resnet34(pretrained=False, **kwargs):
  function resnet50_half (line 479) | def resnet50_half(pretrained=False, **kwargs):
  function resnet50 (line 486) | def resnet50(pretrained=False, **kwargs):
  function resnet101 (line 491) | def resnet101(pretrained=False, **kwargs):
  function resnet152 (line 497) | def resnet152(pretrained=False, **kwargs):
  function resnext50_32x4d (line 503) | def resnext50_32x4d(pretrained=False, **kwargs):
  function resnext101_32x8d (line 511) | def resnext101_32x8d(pretrained=False, **kwargs):
  function wide_resnet50_2 (line 519) | def wide_resnet50_2(pretrained=False, **kwargs):
  function wide_resnet101_2 (line 526) | def wide_resnet101_2(pretrained=False, **kwargs):

FILE: braincog/model_zoo/resnet19_snn.py
  function conv3x3 (line 21) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 27) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 32) | class BasicBlock(nn.Module):
    method __init__ (line 35) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 54) | def forward(self, x):
  class ResNet (line 74) | class ResNet(BaseModule):
    method __init__ (line 75) | def __init__(self, block, layers, num_classes=10, zero_init_residual=F...
    method _make_layer (line 140) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method _forward_impl (line 168) | def _forward_impl(self, x):
    method forward (line 188) | def forward(self, inputs):
  function _resnet (line 195) | def _resnet(arch, block, layers, pretrained, progress, norm=ThresholdDep...
  function resnet19 (line 204) | def resnet19(pretrained=False, progress=True, norm=ThresholdDependentBat...

FILE: braincog/model_zoo/rsnn.py
  class RSNN (line 13) | class RSNN(nn.Module):
    method __init__ (line 14) | def __init__(self,num_state,num_action):
    method forward (line 36) | def forward(self, input):
    method UpdateWeight (line 42) | def UpdateWeight(self,reward):
    method reset (line 49) | def reset(self):
    method getweight (line 54) | def getweight(self):

FILE: braincog/model_zoo/sew_resnet.py
  function sew_function (line 31) | def sew_function(x: torch.Tensor, y: torch.Tensor, cnf:str):
  function conv3x3 (line 43) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 49) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 54) | class BasicBlock(nn.Module):
    method __init__ (line 57) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 79) | def forward(self, x):
    method extra_repr (line 97) | def extra_repr(self) -> str:
  class Bottleneck (line 100) | class Bottleneck(nn.Module):
    method __init__ (line 109) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 131) | def forward(self, x):
    method extra_repr (line 153) | def extra_repr(self) -> str:
  class SEWResNet (line 157) | class SEWResNet(BaseModule):
    method __init__ (line 158) | def __init__(self, block, layers, num_classes=1000, step=8,encode_type...
    method _make_layer (line 228) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False, c...
    method _forward_impl (line 252) | def _forward_impl(self, inputs):
    method _forward_once (line 308) | def _forward_once(self,x):
    method forward (line 327) | def forward(self, x):
  class SEWResNet19 (line 331) | class SEWResNet19(BaseModule):
    method __init__ (line 332) | def __init__(self, block, layers, num_classes=1000, step=8,encode_type...
    method _make_layer (line 401) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False, c...
    method _forward_impl (line 425) | def _forward_impl(self, inputs):
    method _forward_once (line 479) | def _forward_once(self,x):
    method forward (line 498) | def forward(self, x):
  class SEWResNetCifar (line 502) | class SEWResNetCifar(BaseModule):
    method __init__ (line 503) | def __init__(self, block, layers, num_classes=1000, step=8,encode_type...
    method _make_layer (line 572) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False, c...
    method _forward_impl (line 596) | def _forward_impl(self, inputs):
    method _forward_once (line 648) | def _forward_once(self,x):
    method forward (line 667) | def forward(self, x):
  function _sew_resnet (line 672) | def _sew_resnet(arch, block, layers, pretrained, progress, cnf,  **kwargs):
  function sew_resnet19 (line 681) | def sew_resnet19(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet18 (line 701) | def sew_resnet18(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet20 (line 721) | def sew_resnet20(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet32 (line 740) | def sew_resnet32(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet44 (line 759) | def sew_resnet44(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet56 (line 778) | def sew_resnet56(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet34 (line 797) | def sew_resnet34(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet50 (line 817) | def sew_resnet50(pretrained=False, progress=True, cnf: str = None,  **kw...
  function sew_resnet101 (line 837) | def sew_resnet101(pretrained=False, progress=True, cnf: str = None,  **k...
  function sew_resnet152 (line 857) | def sew_resnet152(pretrained=False, progress=True, cnf: str = None,  **k...
  function sew_resnext50_32x4d (line 877) | def sew_resnext50_32x4d(pretrained=False, progress=True, cnf: str = None...
  function sew_resnext34_32x4d (line 899) | def sew_resnext34_32x4d(pretrained=False, progress=True, cnf: str = None...
  function sew_resnext101_32x8d (line 920) | def sew_resnext101_32x8d(pretrained=False, progress=True, cnf: str = Non...
  function sew_wide_resnet50_2 (line 941) | def sew_wide_resnet50_2(pretrained=False, progress=True, cnf: str = None...
  function sew_wide_resnet101_2 (line 966) | def sew_wide_resnet101_2(pretrained=False, progress=True, cnf: str = Non...

FILE: braincog/model_zoo/vgg_snn.py
  class SNN7_tiny (line 22) | class SNN7_tiny(BaseModule):
    method __init__ (line 23) | def __init__(self,
    method forward (line 58) | def forward(self, inputs):
  class SNN5 (line 80) | class SNN5(BaseModule):
    method __init__ (line 81) | def __init__(self,
    method forward (line 120) | def forward(self, inputs):
  class VGG_SNN (line 142) | class VGG_SNN(BaseModule):
    method __init__ (line 143) | def __init__(self,
    method forward (line 183) | def forward(self, inputs):

FILE: braincog/utils.py
  function setup_seed (line 13) | def setup_seed(seed):
  function random_gradient (line 35) | def random_gradient(model: nn.Module, sigma: float):
  class AverageMeter (line 49) | class AverageMeter(object):
    method __init__ (line 50) | def __init__(self):
    method reset (line 53) | def reset(self):
    method update (line 58) | def update(self, val, n=1):
  class TensorGather (line 63) | class TensorGather(object):
    method __init__ (line 64) | def __init__(self):
    method reset (line 66) | def reset(self):
    method update (line 69) | def update(self, val):
  function accuracy (line 73) | def accuracy(output, target, topk=(1,)):
  function mse (line 90) | def mse(x, y):
  function rand_ortho (line 95) | def rand_ortho(shape, irange):
  function adjust_surrogate_coeff (line 101) | def adjust_surrogate_coeff(epoch, tot_epochs):
  function save_feature_map (line 111) | def save_feature_map(x, dir=''):
  function save_spike_info (line 126) | def save_spike_info(fname, epoch, batch_idx, step, avg, var, spike, avg_...
  function calc_aurc (line 159) | def calc_aurc(confidences, labels):

FILE: examples/Embodied_Cognition/RHI/RHI_Test.py
  class CustomLinear (line 23) | class CustomLinear(nn.Module):
    method __init__ (line 24) | def __init__(self, weight,mask=None):
    method forward (line 29) | def forward(self, x: torch.Tensor):
    method update (line 34) | def update(self, dw):
  class M1Net (line 40) | class M1Net(nn.Module):
    method __init__ (line 41) | def __init__(self,connection):
    method forward (line 47) | def forward(self, input):
    method reset (line 66) | def reset(self):
  class VNet (line 70) | class VNet(nn.Module):
    method __init__ (line 71) | def __init__(self,connection):
    method forward (line 77) | def forward(self, input):
    method reset (line 96) | def reset(self):
  class S1Net (line 100) | class S1Net(nn.Module):
    method __init__ (line 101) | def __init__(self,connection):
    method forward (line 107) | def forward(self, input, FR, C):
    method reset (line 137) | def reset(self):
  class EBANet (line 141) | class EBANet(nn.Module):
    method __init__ (line 142) | def __init__(self,connection):
    method forward (line 148) | def forward(self, input, FR, C):
    method reset (line 178) | def reset(self):
  class TPJNet (line 182) | class TPJNet(nn.Module):
    method __init__ (line 183) | def __init__(self,connection):
    method forward (line 189) | def forward(self, input, FR, C):
    method reset (line 219) | def reset(self):
    method UpdateWeight (line 223) | def UpdateWeight(self, i, W):
  class AINet (line 226) | class AINet(nn.Module):
    method __init__ (line 227) | def __init__(self,connection):
    method forward (line 233) | def forward(self, input, FR, C):
    method reset (line 263) | def reset(self):
    method UpdateWeight (line 267) | def UpdateWeight(self, i, W):
  function DeltaWeight (line 271) | def DeltaWeight(Pre, Pre_n, Post, Post_n):

FILE: examples/Embodied_Cognition/RHI/RHI_Train.py
  class CustomLinear (line 23) | class CustomLinear(nn.Module):
    method __init__ (line 24) | def __init__(self, weight,mask=None):
    method forward (line 29) | def forward(self, x: torch.Tensor):
    method update (line 34) | def update(self, dw):
  class M1Net (line 40) | class M1Net(nn.Module):
    method __init__ (line 41) | def __init__(self,connection):
    method forward (line 47) | def forward(self, input):
    method reset (line 66) | def reset(self):
  class VNet (line 70) | class VNet(nn.Module):
    method __init__ (line 71) | def __init__(self,connection):
    method forward (line 77) | def forward(self, input):
    method reset (line 96) | def reset(self):
  class S1Net (line 100) | class S1Net(nn.Module):
    method __init__ (line 101) | def __init__(self,connection):
    method forward (line 107) | def forward(self, input, FR, C, Fired, W_LatInh):
    method reset (line 145) | def reset(self):
  class EBANet (line 149) | class EBANet(nn.Module):
    method __init__ (line 150) | def __init__(self,connection):
    method forward (line 156) | def forward(self, input, FR, C, Fired, W_LatInh):
    method reset (line 194) | def reset(self):
  class TPJNet (line 198) | class TPJNet(nn.Module):
    method __init__ (line 199) | def __init__(self,connection):
    method forward (line 205) | def forward(self, input, FR, C):
    method reset (line 235) | def reset(self):
    method UpdateWeight (line 239) | def UpdateWeight(self, i, W):
  class AINet (line 242) | class AINet(nn.Module):
    method __init__ (line 243) | def __init__(self,connection):
    method forward (line 249) | def forward(self, input, FR, C):
    method reset (line 279) | def reset(self):
    method UpdateWeight (line 283) | def UpdateWeight(self, i, W, WIn):
  function DeltaWeight (line 287) | def DeltaWeight(Pre, Pre_n, Post, Post_n):

FILE: examples/Hardware_acceleration/firefly_v1_schedule_on_pynq.py
  class FireFlyV1ConvSchedule (line 9) | class FireFlyV1ConvSchedule:
    method __init__ (line 10) | def __init__(
    method gen_cmd (line 119) | def gen_cmd(self):
    method send_config (line 139) | def send_config(self):
    method begin_schedule_non_blocking (line 156) | def begin_schedule_non_blocking(self):
    method begin_schedule_blocking (line 161) | def begin_schedule_blocking(self):
    method clear_schedule (line 167) | def clear_schedule(self):
    method run_all (line 170) | def run_all(self):
    method read_status (line 199) | def read_status(self):
  function create_schedule (line 212) | def create_schedule(model_config_list: list,
  function schedule_run_all (line 320) | def schedule_run_all(schedule_list):
  function gen_cmd_array (line 325) | def gen_cmd_array(schedule_list):
  function init_firefly_c_lib (line 332) | def init_firefly_c_lib(path, schedule_list):
  function init_firefly_c_lib_with_time (line 347) | def init_firefly_c_lib_with_time(path, schedule_list):
  function firefly_v1_simulate (line 362) | def firefly_v1_simulate(model_config_list, x):
  function evaluate_simulate (line 380) | def evaluate_simulate(model_config_list, sample):

FILE: examples/Hardware_acceleration/standalone_utils.py
  function get_im2col_indices (line 7) | def get_im2col_indices(x_shape, field_height, field_width, padding=1, st...
  function im2col_indices (line 27) | def im2col_indices(x, field_height, field_width, padding=1, stride=1):
  function max_pool_forward_reshape (line 37) | def max_pool_forward_reshape(x, pool_param):
  function max_pool_forward_fast (line 49) | def max_pool_forward_fast(x, pool_param):
  function max_pool_forward_im2col (line 63) | def max_pool_forward_im2col(x, pool_param):
  function conv_forward_fast (line 82) | def conv_forward_fast(x, w, b, pad=1, stride=1):
  function spike_map_pack_to_bytes_array (line 101) | def spike_map_pack_to_bytes_array(spike_map, parallel):
  function bytes_array_split_to_spike_map (line 107) | def bytes_array_split_to_spike_map(buf_in, time_step, parallel, H, W):
  function preprocess (line 113) | def preprocess(model_config_list, x, parallel):
  function integrate_and_fire (line 128) | def integrate_and_fire(y, threshold):
  function direct_coding (line 139) | def direct_coding(x, w, b, time_step, threshold):
  function conv_ifnode_forward (line 145) | def conv_ifnode_forward(x, w, b, threshold):
  function conv_ifnode_maxpool_forward (line 151) | def conv_ifnode_maxpool_forward(x, w, b, threshold):
  function linear_wta_forward (line 157) | def linear_wta_forward(x, w, b):
  function linear_ifnode_forward (line 169) | def linear_ifnode_forward(x, w, b, threshold):
  function pad_conv_weight_round_to_parallel (line 180) | def pad_conv_weight_round_to_parallel(parallel, weight, pad_output_chann...
  function pad_linear_weight_round_to_parallel (line 191) | def pad_linear_weight_round_to_parallel(parallel, weight):
  function pad_linear_weight_round_to_factor (line 198) | def pad_linear_weight_round_to_factor(weight, factor):
  function pad_bias_round_to_parallel (line 206) | def pad_bias_round_to_parallel(parallel, bias, pad_value=0):
  function np_quantize_per_tensor (line 213) | def np_quantize_per_tensor(x, scale, zero_point):
  function np_quantize_prepare (line 221) | def np_quantize_prepare(x, scale, zero_point):
  function conv_weight_channel_tiling (line 226) | def conv_weight_channel_tiling(parallel, weight):
  function linear_weight_channel_tiling (line 230) | def linear_weight_channel_tiling(parallel, weight):
  function conv_to_linear_weight_tiling (line 234) | def conv_to_linear_weight_tiling(parallel, h, w, weight):
  function init_input_buffer (line 238) | def init_input_buffer(input_spikes,
  function get_from_output_buffer (line 254) | def get_from_output_buffer(output_buffer,
  function get_output_index (line 271) | def get_output_index(buffer, parallel):
  function save_model_config_list (line 281) | def save_model_config_list(model_config_list, path):
  function load_model_config_list (line 286) | def load_model_config_list(path):

FILE: examples/Knowledge_Representation_and_Reasoning/CKRGSNN/main.py
  class CKRNet (line 19) | class CKRNet(BrainArea):
    method __init__ (line 24) | def __init__(self, w1, w2):
    method forward (line 36) | def forward(self, x):
    method reset (line 44) | def reset(self):
  function S_bound (line 48) | def S_bound(S):

FILE: examples/Knowledge_Representation_and_Reasoning/CRSNN/main.py
  class CRNet (line 17) | class CRNet(BrainArea):
    method __init__ (line 29) | def __init__(self, w1, w2):
    method forward (line 41) | def forward(self, x):
    method reset (line 52) | def reset(self):
  function S_bound (line 56) | def S_bound(S):

FILE: examples/Knowledge_Representation_and_Reasoning/SPSNN/main.py
  class SPNet (line 20) | class SPNet(BrainArea):
    method __init__ (line 33) | def __init__(self, w1, w2 ):
    method forward (line 45) | def forward(self, x):
    method reset (line 57) | def reset(self):
  function S_bound (line 62) | def S_bound(S):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Areas/apac.py
  class APAC (line 10) | class APAC():
    method __init__ (line 16) | def __init__(self):
    method encodingNote (line 23) | def encodingNote(self,NoteID):
    method encodingMIDINote (line 31) | def encodingMIDINote(self,p):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Areas/cortex.py
  class Cortex (line 16) | class Cortex():
    method __init__ (line 21) | def __init__(self, neutype, dt):
    method addSubGoalToPFC (line 27) | def addSubGoalToPFC(self, goalname):
    method addComposerToPFC (line 33) | def addComposerToPFC(self, composername):
    method addGenreToPFC (line 39) | def addGenreToPFC(self, genrename):
    method musicSequenceMemroyInit (line 45) | def musicSequenceMemroyInit(self):
    method rememberANote (line 48) | def rememberANote(self, goalname, noteName, order):
    method connectKeyAndNotesUsingKSModel (line 66) | def connectKeyAndNotesUsingKSModel(self,keys, Notes):
    method connectKeyAndNotes (line 90) | def connectKeyAndNotes(self,keys, Notes):
    method connectKeyAndNotesUsingKSModel (line 107) | def connectKeyAndNotesUsingKSModel(self,keys, Notes):
    method rememberANoteWithKnowledge (line 130) | def rememberANoteWithKnowledge(self,goalname, composername, genrename,...
    method rememberANoteandTempo (line 161) | def rememberANoteandTempo(self, goalname, composername, genrename, tra...
    method actionSequenceMemoryInit (line 223) | def actionSequenceMemoryInit(self):
    method recallMusicPFC (line 226) | def recallMusicPFC(self, goalName):
    method recallMusicByEpisode (line 234) | def recallMusicByEpisode(self, episodeNotes):  # using time window sea...
    method generateEx_Nihilo (line 248) | def generateEx_Nihilo(self, firstNote, durations, length):
    method generateEx_Nihilo2 (line 310) | def generateEx_Nihilo2(self, firstNote, durations, length):
    method generateEx_NihiloAccordingToGenre (line 358) | def generateEx_NihiloAccordingToGenre(self, genreName, firstNote, dura...
    method generateEx_NihiloAccordingToComposer (line 407) | def generateEx_NihiloAccordingToComposer(self, composerName, firstNote...
    method generateMelodyWithKey (line 468) | def generateMelodyWithKey(self, key, firstNotes, durations, length):
    method recallActionIPS (line 528) | def recallActionIPS(self, goalName):
    method generate2TrackMusic (line 533) | def generate2TrackMusic(self, firstNotes, durations, lengths):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Areas/pac.py
  class PAC (line 16) | class PAC(BrainArea,SequenceMemory):
    method __init__ (line 21) | def __init__(self, neutype):
    method forward (line 27) | def forward(self, x):
    method createActionSequenceMem (line 30) | def createActionSequenceMem(self, layernum, neutype):
    method doRemembering_note_only (line 40) | def doRemembering_note_only(self, note, order, dt, t):
    method doRemembering (line 50) | def doRemembering(self, trackIndex, noteIndex, order, dt, t, tinterval...
    method doConnectToTitle (line 72) | def doConnectToTitle(self, title, track, order):
    method doConnectToComposer (line 76) | def doConnectToComposer(self, composer, track, order):
    method doConnectToGenre (line 80) | def doConnectToGenre(self, genre, track, order):
    method generateEx_Nihilo (line 84) | def generateEx_Nihilo(self, firstNote, durations, order, dt, t):
    method generateSimgleTrackNotes (line 109) | def generateSimgleTrackNotes(self, trackIndex, firstNote, durations, o...
  class Music_Sequence_Mem (line 136) | class Music_Sequence_Mem(SequenceMemory):
    method __init__ (line 141) | def __init__(self, neutype):
    method createActionSequenceMem (line 147) | def createActionSequenceMem(self, layernum, neutype):
    method doRemembering_note_only (line 157) | def doRemembering_note_only(self, note, order, dt, t):
    method doRemembering (line 167) | def doRemembering(self, trackIndex, noteIndex, order, dt, t, tinterval...
    method recallByEpisode (line 187) | def recallByEpisode(self, episodeNotes, goals):
    method recallByEpisode2 (line 277) | def recallByEpisode2(self, episodeNotes, goals):
    method doConnectToTitle (line 432) | def doConnectToTitle(self, title, track, order):
    method doConnectToComposer (line 436) | def doConnectToComposer(self, composer, track, order):
    method doConnectToGenre (line 440) | def doConnectToGenre(self, genre, track, order):
    method doConnectToEmotion (line 444) | def doConnectToEmotion(self, emo, track, order):
    method doConnectToKey (line 448) | def doConnectToKey(self, key, track, order, noteIndex):
    method doConnectToMode (line 483) | def doConnectToMode(self, mode, keyName, track, order, noteIndex):  # ...
    method generateEx_Nihilo (line 520) | def generateEx_Nihilo(self, firstNote, durations, order, dt, t):
    method generateMelodyWithTone (line 545) | def generateMelodyWithTone(self, firstNote, duration, tone, order, dt,...
    method generateSimgleTrackNotes (line 576) | def generateSimgleTrackNotes(self, trackIndex, firstNote, durations, o...

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Areas/pfc.py
  class PFC (line 12) | class PFC(PFC):
    method __init__ (line 17) | def __init__(self, neutype):
    method addNewKey (line 31) | def addNewKey(self):
    method addNewSubGoal (line 37) | def addNewSubGoal(self, goalname):
    method addNewComposer (line 41) | def addNewComposer(self, composername):
    method addNewGenre (line 45) | def addNewGenre(self, genrename):
    method addNewMode (line 49) | def addNewMode(self):
    method addNewKey (line 71) | def addNewKey(self):
    method addNewChord (line 77) | def addNewChord(self):
    method setTestStates (line 105) | def setTestStates(self):
    method doRecalling (line 114) | def doRecalling(self, goalname, asm):
    method doRecalling2 (line 139) | def doRecalling2(self, goalname, asm):
    method doRecalling3 (line 180) | def doRecalling3(self,goalname,asm):
    method doRemebering (line 236) | def doRemebering(self, goalname, dt, t):
    method doRememberingComposer (line 243) | def doRememberingComposer(self, composername, dt, t):
    method doRememberingGenre (line 249) | def doRememberingGenre(self, genrename, dt, t):
    method doRememberingKey (line 255) | def doRememberingKey(self, key, dt, t):
    method doRememberingMode (line 261) | def doRememberingMode(self,mode, dt,t):
    method innerLearning (line 267) | def innerLearning(self, goalname, composer, genre):
    method inhibitGenres (line 320) | def inhibitGenres(self,dt,t):
    method inhibiteGoals (line 327) | def inhibiteGoals(self, dt, t):
    method inhibitComposers (line 334) | def inhibitComposers(self, dt, t):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/PAC.py
  class PAC (line 10) | class PAC(BrainArea):
    method __int__ (line 12) | def __int__(self,w,mask):
    method forward (line 19) | def forward(self, x):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/cluster.py
  class Cluster (line 6) | class Cluster():
    method __init__ (line 11) | def __init__(self, neutype='LIF', neunum=10):
    method createClusterNetwork (line 22) | def createClusterNetwork(self):
    method setInhibitoryNeurons (line 43) | def setInhibitoryNeurons(self, ratio_inhneuron):
    method setPropertiesofNeurons (line 47) | def setPropertiesofNeurons(self, groupID, layerType, layerID):
    method setTestStates (line 53) | def setTestStates(self):
    method createFullConnections (line 57) | def createFullConnections(self):  # all in all connections
    method createInhibitoryConnections (line 67) | def createInhibitoryConnections(self):  # all in all inhibitory connec...
    method writeSelfInfoToJson (line 79) | def writeSelfInfoToJson(self):
    method writeSpikeInfoToJson (line 91) | def writeSpikeInfoToJson(self):
  class ModeCluster (line 102) | class ModeCluster(Cluster):
    method __init__ (line 103) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 106) | def createClusterNetwork(self, areaName):
  class KeyCluster (line 122) | class KeyCluster(Cluster):
    method __init__ (line 123) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 129) | def createClusterNetwork(self,tone,areaName):
  class ChordCluster (line 166) | class ChordCluster(Cluster):
    method __init__ (line 167) | def __init__(self, neutype,neunum):
    method createClusterNetwork (line 170) | def createClusterNetwork(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/composercluster.py
  class ComposerCluster (line 5) | class ComposerCluster(Cluster):
    method __init__ (line 10) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 16) | def createClusterNetwork(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/composerlayer.py
  class ComposerLayer (line 5) | class ComposerLayer(Layer):
    method __init__ (line 10) | def __init__(self, neutype='LIF'):
    method setTestStates (line 14) | def setTestStates(self):
    method addNewGroups (line 18) | def addNewGroups(self, groupID, layerID, neunum, composername):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/composerlifneuron.py
  class ComposerLIFNeuron (line 4) | class ComposerLIFNeuron(LIFNeuron):
    method __init__ (line 9) | def __init__(self, tau_ref=0, vthresh=5, Rm=2, Cm=0.2):
    method update (line 15) | def update(self, dt, t):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/genrecluster.py
  class GenreCluster (line 4) | class GenreCluster(Cluster):
    method __init__ (line 9) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 15) | def createClusterNetwork(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/genrelayer.py
  class GenreLayer (line 3) | class GenreLayer(Layer):
    method __init__ (line 8) | def __init__(self, neutype='LIF'):
    method setTestStates (line 12) | def setTestStates(self):
    method addNewGroups (line 16) | def addNewGroups(self, groupID, layerID, neunum, genrename):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/genrelifneuron.py
  class GenreLIFNeuron (line 3) | class GenreLIFNeuron(LIFNeuron):
    method __init__ (line 8) | def __init__(self, tau_ref=0, vthresh=5, Rm=2, Cm=0.2):
    method update (line 14) | def update(self, dt, t):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/izhikevichneuron.py
  class IzhikevichNeuron (line 12) | class IzhikevichNeuron(IzhNodeMU):
    method __init__ (line 18) | def __init__(self, a = 0.1,b = 0.2,c = -65,d = 8,vthresh = 30, dt=0.1):
    method update_old (line 50) | def update_old(self,dt,t):
    method update (line 65) | def update(self,dt,t,state):
    method update_learn (line 70) | def update_learn(self,dt,t):
    method update_test (line 82) | def update_test(self,dt,t):
    method update_normal (line 91) | def update_normal(self,dt,t):
    method updateSynapses (line 102) | def updateSynapses(self,t):
    method updateCurrentOfLowerAndUpperLayer (line 106) | def updateCurrentOfLowerAndUpperLayer(self,t):
    method setTestStates (line 130) | def setTestStates(self):
    method writeBasicInfoToJson (line 140) | def writeBasicInfoToJson(self):
    method writeSpikeTimeToJson (line 162) | def writeSpikeTimeToJson(self):
  class NoteIzhikevichNeuron (line 172) | class NoteIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 173) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh = 30):
    method setPreference (line 175) | def setPreference(self):
    method computeFilterCurrent (line 177) | def computeFilterCurrent(self):
    method updateCurrentOfLowerAndUpperLayer (line 181) | def updateCurrentOfLowerAndUpperLayer(self, t):
  class TempoIzhikevichNeuron (line 205) | class TempoIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 206) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh = 30):
    method setPreference (line 208) | def setPreference(self):
    method computeFilterCurrent (line 211) | def computeFilterCurrent(self):
    method updateCurrentOfLowerAndUpperLayer (line 215) | def updateCurrentOfLowerAndUpperLayer(self, t):
  class TitleIzhikevichNeuron (line 243) | class TitleIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 244) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh=30):
  class ComposerIzhikevichNeuron (line 247) | class ComposerIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 248) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh=30):
  class GenreIzhikevichNeuron (line 251) | class GenreIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 252) | def __init__(self, a = 0.1,b = 0.2,c = -65,d = 8, vthresh=30):
  class AmyIzhikevichNeuron (line 255) | class AmyIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 256) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh=30):
  class DirectionIzhikevichNeuron (line 259) | class DirectionIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 260) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh=30):
    method setPreference (line 263) | def setPreference(self):
    method computeFilterCurrent (line 267) | def computeFilterCurrent(self, input):
    method updateCurrentOfLowerAndUpperLayer (line 271) | def updateCurrentOfLowerAndUpperLayer(self, t):
  class GridIzhikevichCell (line 296) | class GridIzhikevichCell(IzhikevichNeuron):
    method __init__ (line 297) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh = 30):
  class KeyIzhikevichNeuron (line 299) | class KeyIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 300) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh = 30):
  class ModeIzhikevichNeuron (line 303) | class ModeIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 304) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8,vthresh = 30):
  class ChordIzhikevichNeuron (line 307) | class ChordIzhikevichNeuron(IzhikevichNeuron):
    method __init__ (line 308) | def __init__(self,a = 0.1,b = 0.2,c = -65,d = 8, vthresh = 30):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/layer.py
  class Layer (line 4) | class Layer():
    method __init__ (line 10) | def __init__(self, neutype):
    method resetProperties (line 18) | def resetProperties(self):
    method addNewGroups (line 21) | def addNewGroups(self, layerID, neunum):
  class ModeLayer (line 24) | class ModeLayer(Layer):
    method __init__ (line 25) | def __init__(self, neutype = 'LIF'):
    method setTestStates (line 29) | def setTestStates(self):
    method addNewGroups (line 33) | def addNewGroups(self, groupID, layerID, neunum, modeName):
  class KeyLayer (line 41) | class KeyLayer(Layer):
    method __init__ (line 42) | def __init__(self, neutype='LIF'):
    method setTestStates (line 46) | def setTestStates(self):
    method addNewGroups (line 50) | def addNewGroups(self, groupID, layerID, neunum, key):
  class ChordLayer (line 58) | class ChordLayer(Layer):
    method __init__ (line 59) | def __init__(self, neutype = 'LIF'):
    method setTestStates (line 62) | def setTestStates(self):
    method addNewGroups (line 66) | def addNewGroups(self,groupID, layerID, neunum):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/lifneuron.py
  class LIFNeuron (line 5) | class LIFNeuron(node.LIFNode):
    method __init__ (line 7) | def __init__(self, tau_ref = 0, vthresh = 5, Rm = 2, Cm = 0.2,dt = 0.1...
    method update (line 36) | def update(self, dt, t, state):  # state = 'learn' or  state = 'test'
    method update_learn (line 50) | def update_learn(self, dt, t):
    method update_test (line 70) | def update_test(self, dt, t):
    method update_normal (line 81) | def update_normal(self, dt, t):
    method updateSynapses (line 93) | def updateSynapses(self, t):
    method setTestStates (line 97) | def setTestStates(self):
    method computeFilterCurrent (line 108) | def computeFilterCurrent(self):
    method setPreference (line 111) | def setPreference(self):  # set preference of a neuron or called selec...
    method writeBasicInfoToJson (line 115) | def writeBasicInfoToJson(self, areaName):
    method writeSpikeTimeToJson (line 139) | def writeSpikeTimeToJson(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/note.py
  class Note (line 7) | class Note():
    method __init__ (line 12) | def __init__(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/notecluster.py
  class NoteCluster (line 5) | class NoteCluster(Cluster):
    method __init__ (line 10) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 16) | def createClusterNetwork(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/notelifneuron.py
  class NoteLIFNeuron (line 4) | class NoteLIFNeuron(LIFNeuron):
    method __init__ (line 9) | def __init__(self, tau_ref=0.5, vthresh=5, Rm=2, Cm=0.2):
    method setPreference (line 15) | def setPreference(self):
    method computeFilterCurrent (line 18) | def computeFilterCurrent(self):
    method updateCurrentOfLowerAndUpperLayer (line 22) | def updateCurrentOfLowerAndUpperLayer(self, t):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/notesequencelayer.py
  class NoteSequenceLayer (line 6) | class NoteSequenceLayer(SequenceLayer):
    method __init__ (line 11) | def __init__(self, neutype):
    method addNewGroups (line 17) | def addNewGroups(self, GroupID, layerID, neunum):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/pitch.py
  class Pitch (line 7) | class Pitch():
    method __init__ (line 13) | def __init__(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/sequencelayer.py
  class SequenceLayer (line 6) | class SequenceLayer(Layer):
    method __init__ (line 11) | def __init__(self, neutype='LIF'):
    method addNewGroups (line 19) | def addNewGroups(self, GroupID, layerID, neunum):
    method setTestStates (line 39) | def setTestStates(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/sequencememory.py
  class SequenceMemory (line 6) | class SequenceMemory():
    method __init__ (line 11) | def __init__(self, neutype):
    method createActionSequenceMem (line 18) | def createActionSequenceMem(self, layernum, neutype, neunumpergroup):
    method doRemembering (line 21) | def doRemembering(self):
    method doConnecting (line 24) | def doConnecting(self, goal, sl, order):
    method setTestStates (line 192) | def setTestStates(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/synapse.py
  class Synapse (line 3) | class Synapse():
    method __init__ (line 8) | def __init__(self, pre, post):
    method computeWeight (line 20) | def computeWeight(self, t):
    method computeShortTermFacilitation (line 56) | def computeShortTermFacilitation(self, t):
    method computeShortTermFacilitation2 (line 79) | def computeShortTermFacilitation2(self, t):
    method computeShortTermReduction (line 96) | def computeShortTermReduction(self, t):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/tempocluster.py
  class TempoCluster (line 5) | class TempoCluster(Cluster):
    method __init__ (line 10) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 16) | def createClusterNetwork(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/tempolifneuron.py
  class TempoLIFNeuron (line 5) | class TempoLIFNeuron(LIFNeuron):
    method __init__ (line 10) | def __init__(self, tau_ref=0.5, vthresh=5, Rm=2, Cm=0.2):
    method setPreference (line 16) | def setPreference(self):
    method computeFilterCurrent (line 20) | def computeFilterCurrent(self):
    method updateCurrentOfLowerAndUpperLayer (line 24) | def updateCurrentOfLowerAndUpperLayer(self, t):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/temposequencelayer.py
  class TempoSequenceLayer (line 6) | class TempoSequenceLayer(SequenceLayer):
    method __init__ (line 11) | def __init__(self, neutype):
    method addNewGroups (line 17) | def addNewGroups(self, GroupID, layerID, neunum):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/titlecluster.py
  class TitleCluster (line 5) | class TitleCluster(Cluster):
    method __init__ (line 10) | def __init__(self, neutype, neunum):
    method createClusterNetwork (line 17) | def createClusterNetwork(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/titlelayer.py
  class TitleLayer (line 7) | class TitleLayer(Layer):
    method __init__ (line 12) | def __init__(self, neutype='LIF'):
    method setTestStates (line 19) | def setTestStates(self):
    method addNewGroups (line 23) | def addNewGroups(self, groupID, layerID, neunum, goalname):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/Modal/titlelifneuron.py
  class TitleLIFNeuron (line 5) | class TitleLIFNeuron(LIFNeuron):
    method __init__ (line 10) | def __init__(self, tau_ref=0, vthresh=5, Rm=2, Cm=0.2):
    method updateCurrentOfLowerAndUpperLayer (line 16) | def updateCurrentOfLowerAndUpperLayer(self, t):
    method update (line 30) | def update(self, dt, t):
    method computeFiringRate (line 41) | def computeFiringRate(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/api/music_engine_api.py
  class EngineAPI (line 11) | class EngineAPI():
    method __init__ (line 16) | def __init__(self):
    method cortexInit (line 23) | def cortexInit(self):
    method rememberMusic (line 29) | def rememberMusic(self, muiscName, composerName="None"):
    method learnFourPartMusic (line 58) | def learnFourPartMusic(self,xmldata, musicName, composerName="None"):
    method rememberPartNotes (line 73) | def rememberPartNotes(self,musicName, composerName, genreName, emo, ke...
    method rememberMIDIMusic (line 93) | def rememberMIDIMusic(self, musicName, composerName, noteLength, fileN...
    method rememberTrackNotes (line 113) | def rememberTrackNotes(self, musicName, composerName, genreName, track...
    method rememberNotes (line 196) | def rememberNotes(self, MusicName, notes, intervals, tempo=True):
    method rememberANote (line 213) | def rememberANote(self, MusicName, ComposerName, genreName, TrackIndex...
    method memorizing (line 223) | def memorizing(self,MusicName, ComposerName, noteLength, fileName):
    method recallMusic (line 234) | def recallMusic(self, musicName):
    method generateEx_Nihilo (line 255) | def generateEx_Nihilo(self, firstNote, durations, length,gen_fName):
    method generateEx_NihiloAccordingToGenre (line 268) | def generateEx_NihiloAccordingToGenre(self, genreName, firstNote, dura...
    method generateEx_NihiloAccordingToComposer (line 282) | def generateEx_NihiloAccordingToComposer(self, composerName, firstNote...
    method generate2TrackMusic (line 296) | def generate2TrackMusic(self, firstNotes, durations, lengths):
    method generateMelodyWithKey (line 300) | def generateMelodyWithKey(self,tone, firstNotes,durations = None,lengt...
    method writeMidiFile (line 306) | def writeMidiFile(self,fileName, mudic):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/conf/conf.py
  class Conf (line 4) | class Conf():
    method __init__ (line 9) | def __init__(self, neutype="LIF", task="MusicLearning", dt=0.1):
    method readNoteFiles (line 29) | def readNoteFiles(self):
    method readGenreFils (line 42) | def readGenreFils(self):
    method readEmotionFiles (line 56) | def readEmotionFiles(self):
    method readKeysFile (line 69) | def readKeysFile(self):
    method readKeys2IndexFile (line 86) | def readKeys2IndexFile(self):
    method readChordsFile (line 97) | def readChordsFile(self):
    method readModesFile (line 112) | def readModesFile(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/tools/generateData.py
  class joint (line 9) | class joint():
    method __init__ (line 10) | def __init__(self):
    method self2dic (line 14) | def self2dic(self):
  class data (line 19) | class data():
    method __init__ (line 21) | def __init__(self):
    method self2dic (line 26) | def self2dic(self):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/tools/msg.py
  class MyListener (line 9) | class MyListener(object):
    method on_error (line 10) | def on_error(self, headers, message):
    method on_message (line 12) | def on_message(self, headers, message):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/tools/msgq.py
  function createMSQ (line 10) | def createMSQ():

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/tools/readjson.py
  function readjsonFile (line 11) | def readjsonFile(filename):

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/tools/testopengl.py
  function drawFunc (line 10) | def drawFunc():

FILE: examples/Knowledge_Representation_and_Reasoning/musicMemory/tools/xmlParser.py
  function readXmlAsCsv (line 10) | def readXmlAsCsv(xmlPath='xml/'):

FILE: examples/MotorControl/experimental/brain_area.py
  class MoColumnPOP (line 7) | class MoColumnPOP(nn.Module):
    method __init__ (line 8) | def __init__(self,
    method reset (line 29) | def reset(self):
    method _emb_decode (line 34) | def _emb_decode(self, x):
    method forward (line 42) | def forward(self, inputs):
  class MotorCortex (line 48) | class MotorCortex(nn.Module):
    method __init__ (line 49) | def __init__(self,
    method reset (line 84) | def reset(self):
    method _compute_motor_out (line 90) | def _compute_motor_out(self, inputs):
    method forward (line 99) | def forward(self, inputs):
  class Celebellum (line 110) | class Celebellum(nn.Module):
    method __init__ (line 111) | def __init__(self,
    method reset (line 136) | def reset(self):
    method forward (line 140) | def forward(self, x):

FILE: examples/MotorControl/experimental/main.py
  function creat_key_finger_emb (line 72) | def creat_key_finger_emb():
  function mse_loss (line 81) | def mse_loss(pred, target):
  function main (line 85) | def main():

FILE: examples/MotorControl/experimental/model.py
  class Motion (line 7) | class Motion(nn.Module):
    method __init__ (line 8) | def __init__(self, in_dims: int, out_dims: int=17, time_window: int=8,...
    method forward (line 16) | def forward(self, x):
    method learn (line 22) | def learn(self):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/model/cortex.py
  class Cortex (line 11) | class Cortex():
    method __init__ (line 17) | def __init__(self,neuronnumscale):
    method setNeuronToIndex (line 31) | def setNeuronToIndex(self,node):
    method setLayers (line 35) | def setLayers(self):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/model/cortex_thalamus.py
  class Cortex_Thalamus (line 17) | class Cortex_Thalamus():
    method __init__ (line 31) | def __init__(self, neuronnumscale):
    method setSynapseNum (line 44) | def setSynapseNum(self):
    method setLayer (line 51) | def setLayer(self):
    method setNeuronsDendritesAndSynapes (line 62) | def setNeuronsDendritesAndSynapes(self):
    method setSynapsesToDendrites (line 192) | def setSynapsesToDendrites(self):
    method setCortexProperties (line 227) | def setCortexProperties(self):
    method setThalamusProperties (line 229) | def setThalamusProperties(self):
    method CreateCortexNetwork (line 232) | def CreateCortexNetwork(self):
    method getTotalNeuronNumber (line 240) | def getTotalNeuronNumber(self):
    method getTotalSynapseNumber (line 242) | def getTotalSynapseNumber(self):
    method getCortexNeuronNumber (line 244) | def getCortexNeuronNumber(self):
    method getThalamoNeuronNumber (line 246) | def getThalamoNeuronNumber(self):
    method getSpecifiedNeuronNumber (line 248) | def getSpecifiedNeuronNumber(self,name):
    method getNeuronTypesNumber (line 259) | def getNeuronTypesNumber(self):
    method getNeuronTypes (line 261) | def getNeuronTypes(self):
    method getCorticalSynapseNumber (line 263) | def getCorticalSynapseNumber(self):
    method getThalamoSynapseNumber (line 265) | def getThalamoSynapseNumber(self):
    method getPreAndPostNeuronsOfSynapse (line 267) | def getPreAndPostNeuronsOfSynapse(self,index):
    method getCortexLayerNeuronNumber (line 272) | def getCortexLayerNeuronNumber(self,layername):
    method getCortexLayerSynapseNumber (line 275) | def getCortexLayerSynapseNumber(self,layername):
    method getCortexLayerNeuronTypes (line 278) | def getCortexLayerNeuronTypes(self,layername):
    method getCortexLayerPreAndPostNeuronsOfSynapse (line 284) | def getCortexLayerPreAndPostNeuronsOfSynapse(self,layername,index):
    method getNeuronAllPreNeuronsTypes (line 288) | def getNeuronAllPreNeuronsTypes(self,index):
    method outputNeuronInfo (line 292) | def outputNeuronInfo(self):
    method outputConnectionMatrix (line 301) | def outputConnectionMatrix(self):
    method outputsynapspercent (line 321) | def outputsynapspercent(self,namelist):
    method run (line 334) | def run(self):
    method outputSpikeThreashold (line 344) | def outputSpikeThreashold(self):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/model/dendrite.py
  class Dendrite (line 11) | class Dendrite():
    method __init__ (line 16) | def __init__(self):
    method setSynapse (line 24) | def setSynapse(self,syn):
    method getSynapseInfo (line 35) | def getSynapseInfo(self,f,nodename,denpos):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/model/layer.py
  class Layer (line 10) | class Layer():
    method __init__ (line 21) | def __init__(self):
    method getLayerNeuronNumber (line 29) | def getLayerNeuronNumber(self):
    method getLayerSynapseNumber (line 31) | def getLayerSynapseNumber(self):
    method getLayerNeuronTypes (line 33) | def getLayerNeuronTypes(self):
    method stimulateNeuronInLayer4_BFS (line 36) | def stimulateNeuronInLayer4_BFS(self, T, neulist):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/model/synapse.py
  class Synapse (line 7) | class Synapse():
    method __init__ (line 17) | def __init__(self, pre,post,locationlayer):
    method getInfo (line 31) | def getInfo(self,f,nodename,denpos,denlayer):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/model/thalamus.py
  class Thalamus (line 7) | class Thalamus():
    method __init__ (line 13) | def __init__(self):
    method setNeuronToIndex (line 23) | def setNeuronToIndex(self,node):
    method setThalamusProperties (line 27) | def setThalamusProperties(self):

FILE: examples/Multiscale_Brain_Structure_Simulation/CorticothalamicColumn/tools/exdata.py
  class EXDATA (line 4) | class EXDATA():
    method __int__ (line 5) | def __int__(self):
    method getCortexData (line 8) | def getCortexData(self):
    method getCortexData2 (line 28) | def getCortexData2(self):
    method getLayerData (line 34) | def getLayerData(self):
    method getNeuronData (line 54) | def getNeuronData(self):
    method getSynapseData (line 72) | def getSynapseData(self, postneuron):

FILE: examples/Multiscale_Brain_Structure_Simulation/Corticothalamic_Brain_Model/Bioinformatics_propofol_circle.py
  class brain_model_91 (line 13) | class brain_model_91():
    method __init__ (line 15) | def __init__(self, W, D):
    method simulation (line 155) | def simulation(self):

FILE: examples/Multiscale_Brain_Structure_Simulation/Corticothalamic_Brain_Model/spectrogram.py
  function region_sxx (line 41) | def region_sxx(region):
  function global_sxx (line 60) | def global_sxx():
  function compare_sxx (line 76) | def compare_sxx():

FILE: examples/Multiscale_Brain_Structure_Simulation/HumanBrain/human_brain.py
  class Syn (line 15) | class Syn(nn.Module):
    method __init__ (line 16) | def __init__(self, syn, weight, neuron_num, tao_d, tao_r, dt, device):
    method forward (line 33) | def forward(self, neuron):
  class brain (line 42) | class brain(nn.Module):
    method __init__ (line 43) | def __init__(self, syn, weight, neuron_model, p_neuron, dt, device):
    method forward (line 52) | def forward(self, inputs):
  function brain_region (line 57) | def brain_region(neuron_num):
  function neuron_type (line 67) | def neuron_type(neuron_num, ratio, regions):
  function syn_within_region (line 72) | def syn_within_region(syn_num, region):
  function syn_cross_region (line 84) | def syn_cross_region(weight_matrix, region):

FILE: examples/Multiscale_Brain_Structure_Simulation/HumanBrain/human_multi.py
  class MultiCompartmentaEIF (line 19) | class MultiCompartmentaEIF(BaseNode):
    method __init__ (line 30) | def __init__(self,
    method integral (line 62) | def integral(self,apical_inputs):
    method calc_spike (line 71) | def calc_spike(self):
    method forward (line 75) | def forward(self, inputs):
  class aEIF (line 85) | class aEIF(BaseNode):
    method __init__ (line 93) | def __init__(self, p, dt, device, *args, **kwargs):
    method integral (line 133) | def integral(self, inputs):
    method calc_spike (line 143) | def calc_spike(self):
    method forward (line 149) | def forward(self, inputs):
  class HHNode (line 157) | class HHNode(BaseNode):
    method __init__ (line 170) | def __init__(self, p, dt, device, act_fun=AtanGrad, *args, **kwargs):
    method integral (line 203) | def integral(self, inputs):
    method calc_spike (line 237) | def calc_spike(self):
    method forward (line 240) | def forward(self, inputs):
    method requires_activation (line 245) | def requires_activation(self):
  class Syn (line 248) | class Syn(nn.Module):
    method __init__ (line 249) | def __init__(self, syn, weight, neuron_num, tao_d, tao_r, dt, device):
    method forward (line 266) | def forward(self, neuron):
  class brain (line 275) | class brain(nn.Module):
    method __init__ (line 276) | def __init__(self, syn, weight, neuron_model, p_neuron, dt, device):
    method forward (line 287) | def forward(self, inputs):
  function brain_region (line 292) | def brain_region(neuron_num):
  function neuron_type (line 302) | def neuron_type(neuron_num, ratio, regions):
  function syn_within_region (line 307) | def syn_within_region(syn_num, region):
  function syn_cross_region (line 319) | def syn_cross_region(weight_matrix, region):
  function neuron_delete (line 484) | def neuron_delete(model, rate):
  function syn_delete (line 491) | def syn_delete(model, rate):
  function syn_strength (line 502) | def syn_strength(model, rate):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_Brain_Model/NA.py
  function histogram_entropy (line 16) | def histogram_entropy(data, bins='auto'):
  function hub_degree (line 38) | def hub_degree(df, W_new):
  function visual (line 57) | def visual(df, W_new):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_Brain_Model/main_246.py
  class brain_model (line 14) | class brain_model():
    method __init__ (line 16) | def __init__(self, W):
    method simulation (line 173) | def simulation(self, per):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_Brain_Model/main_84.py
  class brain_model (line 14) | class brain_model():
    method __init__ (line 16) | def __init__(self, W):
    method simulation (line 173) | def simulation(self, per):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_Brain_Model/pci.py
  function generate_rm (line 15) | def generate_rm(Iraster):
  function lempel_ziv_complexity (line 70) | def lempel_ziv_complexity(data):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_Brain_Model/pci_246.py
  function generate_rm (line 15) | def generate_rm(Iraster):
  function lempel_ziv_complexity (line 70) | def lempel_ziv_complexity(data):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_Brain_Model/spectrogram.py
  function region_sxx (line 42) | def region_sxx(region):
  function global_sxx (line 58) | def global_sxx():
  function compare_sxx (line 74) | def compare_sxx():
  function fit (line 99) | def fit(xx, yy):

FILE: examples/Multiscale_Brain_Structure_Simulation/Human_PFC_Model/Six_Layer_PFC.py
  class six_layer_pfc (line 12) | class six_layer_pfc():
    method __init__ (line 18) | def __init__(self):
    method picture (line 30) | def picture(self,path=None):
    method mex_function (line 48) | def mex_function(self, path=None):
  class SynType (line 623) | class SynType:
    method __init__ (line 624) | def __init__(self):
  class Neuron (line 641) | class Neuron:
    method __init__ (line 653) | def __init__(self):
  class InpNeuron (line 685) | class InpNeuron:
    method __init__ (line 692) | def __init__(self):
  class Synapse (line 703) | class Synapse:
    method __init__ (line 707) | def __init__(self):
  class SynDepr (line 715) | class SynDepr:
    method __init__ (line 723) | def __init__(self):
  class SynList (line 733) | class SynList:
    method __init__ (line 737) | def __init__(self):

FILE: examples/Multiscale_Brain_Structure_Simulation/MacaqueBrain/macaque_brain.py
  class Syn (line 14) | class Syn(nn.Module):
    method __init__ (line 15) | def __init__(self, syn, weight, neuron_num, tao_d, tao_r, dt, device):
    method forward (line 32) | def forward(self, neuron):
  class brain (line 41) | class brain(nn.Module):
    method __init__ (line 42) | def __init__(self, syn, weight, neuron_model, p_neuron, dt, device):
    method forward (line 51) | def forward(self, inputs):
  function brain_region (line 56) | def brain_region(neuron_num):
  function neuron_type (line 66) | def neuron_type(neuron_num, ratio, regions):
  function syn_within_region (line 71) | def syn_within_region(syn_num, region):
  function syn_cross_region (line 83) | def syn_cross_region(weight_matrix, region):

FILE: examples/Multiscale_Brain_Structure_Simulation/MouseBrain/mouse_brain.py
  class Syn (line 14) | class Syn(nn.Module):
    method __init__ (line 15) | def __init__(self, syn, weight, neuron_num, tao_d, tao_r, dt, device):
    method forward (line 32) | def forward(self, neuron):
  class brain (line 41) | class brain(nn.Module):
    method __init__ (line 42) | def __init__(self, syn, weight, neuron_model, p_neuron, dt, device):
    method forward (line 51) | def forward(self, inputs):
  function brain_region (line 56) | def brain_region(neuron_num):
  function neuron_type (line 66) | def neuron_type(neuron_num, ratio, regions):
  function syn_within_region (line 71) | def syn_within_region(syn_num, region):
  function syn_cross_region (line 83) | def syn_cross_region(weight_matrix, region):

FILE: examples/Perception_and_Learning/Conversion/burst_conversion/CIFAR10_VGG16.py
  class VGG16 (line 17) | class VGG16(nn.Module):
    method __init__ (line 18) | def __init__(self, relu_max=1):  # 1   3e38
    method forward (line 43) | def forward(self, input):
  function get_cifar10_loader (line 50) | def get_cifar10_loader(batch_size, train_batch=None, num_workers=4, conv...
  function train (line 74) | def train(net, train_iter, test_iter, optimizer, scheduler, device, num_...
  function evaluate_accuracy (line 117) | def evaluate_accuracy(data_iter, net, device=None, only_onebatch=False):

FILE: examples/Perception_and_Learning/Conversion/burst_conversion/converted_CIFAR10.py
  function evaluate_snn (line 44) | def evaluate_snn(test_iter, snn, device=None, duration=50):

FILE: examples/Perception_and_Learning/Conversion/msat_conversion/CIFAR10_VGG16.py
  class VGG16 (line 17) | class VGG16(nn.Module):
    method __init__ (line 18) | def __init__(self, relu_max=1):  # 1   3e38
    method forward (line 43) | def forward(self, input):
  function get_cifar10_loader (line 50) | def get_cifar10_loader(batch_size, train_batch=None, num_workers=4, conv...
  function train (line 74) | def train(net, train_iter, test_iter, optimizer, scheduler, device, num_...
  function evaluate_accuracy (line 117) | def evaluate_accuracy(data_iter, net, device=None, only_onebatch=False):

FILE: examples/Perception_and_Learning/Conversion/msat_conversion/converted_CIFAR10.py
  function evaluate_snn (line 46) | def evaluate_snn(test_iter, snn, device=None, duration=50):

FILE: examples/Perception_and_Learning/Conversion/msat_conversion/convertor.py
  class FolderPath (line 13) | class FolderPath:
  class HookScale (line 16) | class HookScale(nn.Module):
    method __init__ (line 23) | def __init__(self,
    method forward (line 38) | def forward(self, x):
  class Hookoutput (line 52) | class Hookoutput(nn.Module):
    method __init__ (line 57) | def __init__(self, module):
    method forward (line 62) | def forward(self, x):
  class Scale (line 68) | class Scale(nn.Module):
    method __init__ (line 73) | def __init__(self, scale: float = 1.0):
    method forward (line 77) | def forward(self, x):
  function reset (line 84) | def reset(self):
  class Convertor (line 97) | class Convertor(nn.Module):
    method __init__ (line 118) | def __init__(self,
    method forward (line 146) | def forward(self, model):
    method register_hook (line 157) | def register_hook(model, p=0.99, channelnorm=False, gamma=0.999):
    method get_percentile (line 172) | def get_percentile(model, dataloader, device, batch_num=1):
    method replace_for_spike (line 184) | def replace_for_spike(model, lipool=True, soft_mode=True, gamma=1, spi...
  class SNode (line 208) | class SNode(nn.Module):
    method __init__ (line 215) | def __init__(self, soft_mode=False, gamma=5, useDET=False, useDTT=Fals...
    method forward (line 256) | def forward(self, x):
    method hard_reset (line 317) | def hard_reset(self):
    method soft_reset (line 323) | def soft_reset(self):
    method reset (line 329) | def reset(self):

FILE: examples/Perception_and_Learning/IllusionPerception/AbuttingGratingIllusion/distortion/abutting_grating_illusion/abutting_grating_distortion.py
  function save_image (line 30) | def save_image(image, filename):
  function get_mnist_data (line 37) | def get_mnist_data(train = False, batch_size = 100):
  function get_silhouette_data (line 56) | def get_silhouette_data(path):
  function ag_distort_28 (line 75) | def ag_distort_28(imgs, threshold=0, interval=4, phase=2, direction=(1,0)):
  function transform_224 (line 95) | def transform_224(imgs):
  function ag_distort_224 (line 100) | def ag_distort_224(imgs, threshold=0, interval=8, phase=4, direction=(1,...
  function ag_distort_silhouette (line 123) | def ag_distort_silhouette(imgs, threshold=0.5, interval=2, phase=1, dire...

FILE: examples/Perception_and_Learning/MultisensoryIntegration/code/MultisensoryIntegrationDEMO_AM.py
  class AMNet (line 10) | class AMNet(nn.Module):
    method __init__ (line 11) | def __init__(self,
    method forward (line 28) | def forward(self, x):
  function get_concept_dataset_dic_and_AM_initial_weights_lst (line 35) | def get_concept_dataset_dic_and_AM_initial_weights_lst(BBSR_path):
  function convert_vec_into_spike_trains (line 76) | def convert_vec_into_spike_trains(each_concept_vec):
  function reducing_to_binarycode (line 84) | def reducing_to_binarycode(post_neuron_states_lst, tolerance):

FILE: examples/Perception_and_Learning/MultisensoryIntegration/code/MultisensoryIntegrationDEMO_IM.py
  class IMNet (line 12) | class IMNet(nn.Module):
    method __init__ (line 13) | def __init__(self,
    method forward (line 30) | def forward(self, x):
  function get_concept_dataset_dic_and_initial_weights_lst (line 37) | def get_concept_dataset_dic_and_initial_weights_lst(BBSR_path):
  function convert_vec_into_spike_trains (line 70) | def convert_vec_into_spike_trains(each_concept_vec):
  function reducing_to_binarycode (line 78) | def reducing_to_binarycode(post_neuron_states_lst, tolerance):

FILE: examples/Perception_and_Learning/MultisensoryIntegration/code/measure_and_visualization.py
  function get_concept_dataset_dic_and_initial_weights_lst (line 4) | def get_concept_dataset_dic_and_initial_weights_lst(BBSR_path):
  function load_binarycode_dic (line 36) | def load_binarycode_dic(filename):
  function load_m_dataset_concept_set_lst (line 42) | def load_m_dataset_concept_set_lst(m_dataset_name):
  function load_McRae_concept_feature_lst (line 48) | def load_McRae_concept_feature_lst():
  function load_CSLB_concept_feature_lst (line 64) | def load_CSLB_concept_feature_lst():
  function get_m_dataset_concept_k_similar_concepts_dic (line 82) | def get_m_dataset_concept_k_similar_concepts_dic(m_dataset_name, overlap...
  function get_dataset_concept_ME_dic (line 101) | def get_dataset_concept_ME_dic(origin_dataset_dic):
  function get_dataset_concept_k_similar_concepts_ranking_dic_dic (line 113) | def get_dataset_concept_k_similar_concepts_ranking_dic_dic (dataset_dic,...
  function get_vec_Harmming_similarity (line 131) | def get_vec_Harmming_similarity(concept1_vecstr, concept2_vecstr):
  function get_ME_kAR_corr (line 135) | def get_ME_kAR_corr(binarycode_type, concept_ME_dic, m_dataset, k):
  function visualize_results (line 175) | def visualize_results(ME_lst, raking_mean_lst, jointplot_file):

FILE: examples/Perception_and_Learning/NeuEvo/auto_augment.py
  class ImageNetPolicy (line 14) | class ImageNetPolicy(object):
    method __init__ (line 28) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 60) | def __call__(self, img):
    method __repr__ (line 64) | def __repr__(self):
  class CIFAR10Policy (line 68) | class CIFAR10Policy(object):
    method __init__ (line 82) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 114) | def __call__(self, img):
    method __repr__ (line 118) | def __repr__(self):
  class SVHNPolicy (line 122) | class SVHNPolicy(object):
    method __init__ (line 136) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 168) | def __call__(self, img):
    method __repr__ (line 172) | def __repr__(self):
  class SubPolicy (line 176) | class SubPolicy(object):
    method __init__ (line 178) | def __init__(self,
    method __call__ (line 269) | def __call__(self, img):

FILE: examples/Perception_and_Learning/NeuEvo/main.py
  function _parse_args (line 345) | def _parse_args():
  function main (line 362) | def main():
  function train_epoch (line 722) | def train_epoch(
  function validate (line 857) | def validate(epoch, model, loader, loss_fn, args, amp_autocast=suppress,

FILE: examples/Perception_and_Learning/NeuEvo/separate_loss.py
  class MseSeparateLoss (line 10) | class MseSeparateLoss(nn.modules.loss._Loss):
    method __init__ (line 12) | def __init__(self, weight=0.1, size_average=None, ignore_index=-100,
    method forward (line 19) | def forward(self, input1, target1, input2):
  class ConvSeparateLoss (line 26) | class ConvSeparateLoss(nn.modules.loss._Loss):
    method __init__ (line 29) | def __init__(self, loss1_fn, weight=0.1, size_average=None, ignore_ind...
    method forward (line 36) | def forward(self, input1, target1, input2):
  class TriSeparateLoss (line 59) | class TriSeparateLoss(nn.modules.loss._Loss):
    method __init__ (line 62) | def __init__(self, loss1_fn, weight=0.1, size_average=None, ignore_ind...
    method forward (line 69) | def forward(self, input1, target1, input2):

FILE: examples/Perception_and_Learning/NeuEvo/train.py
  class TrainNetwork (line 75) | class TrainNetwork(object):
    method __init__ (line 78) | def __init__(self, args):
    method _init_log (line 87) | def _init_log(self):
    method _init_device (line 100) | def _init_device(self):
    method _init_data_queue (line 115) | def _init_data_queue(self):
    method _init_model (line 136) | def _init_model(self):
    method run (line 195) | def run(self):
    method train (line 232) | def train(self):
    method infer (line 267) | def infer(self):

FILE: examples/Perception_and_Learning/NeuEvo/train_search.py
  function main (line 138) | def main():
  function train (line 297) | def train(epoch, train_queue, valid_queue, model, architect, criterion, ...
  function infer (line 352) | def infer(valid_queue, model, criterion):

FILE: examples/Perception_and_Learning/NeuEvo/utils.py
  class AvgrageMeter (line 21) | class AvgrageMeter(object):
    method __init__ (line 23) | def __init__(self):
    method reset (line 26) | def reset(self):
    method update (line 31) | def update(self, val, n=1):
  function accuracy (line 37) | def accuracy(output, target, topk=(1,)):
  class Cutout (line 57) | class Cutout(object):
    method __init__ (line 58) | def __init__(self, length):
    method __call__ (line 61) | def __call__(self, img):
  function _data_transforms_cifar (line 79) | def _data_transforms_cifar(args):
  function count_parameters_in_MB (line 112) | def count_parameters_in_MB(model):
  function save_checkpoint (line 116) | def save_checkpoint(state, is_best, save):
  function save (line 124) | def save(model, model_path):
  function load (line 128) | def load(model, model_path):
  function drop_path (line 132) | def drop_path(x, drop_prob):
  function create_exp_dir (line 142) | def create_exp_dir(path, scripts_to_save=None):
  function calc_time (line 154) | def calc_time(seconds):
  function save_file (line 161) | def save_file(recoder, path='./', back_connection=False):

FILE: examples/Perception_and_Learning/QSNN/main.py
  function int2onehot (line 39) | def int2onehot(label, classes, factor):
  function train (line 45) | def train(net, epochs, lr):

FILE: examples/Perception_and_Learning/UnsupervisedSTDP/codef.py
  class STDPConv (line 46) | class STDPConv(nn.Module):
    method __init__ (line 47) | def __init__(self, in_planes, out_planes, kernel_size, stride, padding...
    method mem_update (line 65) | def mem_update(self, x, onespike=True):  # b,c,h,w
    method forward (line 77) | def forward(self, x, T=None, onespike=True):
    method reset (line 107) | def reset(self):
    method normgrad (line 110) | def normgrad(self, force=False):
    method normweight (line 121) | def normweight(self, clip=False):
    method getthresh (line 136) | def getthresh(self, scale):
  class STDPLinear (line 143) | class STDPLinear(nn.Module):
    method __init__ (line 144) | def __init__(self, in_planes, out_planes,
    method mem_update (line 161) | def mem_update(self, x, onespike=True):  # b,c,h,w
    method forward (line 176) | def forward(self, x, T, onespike=True):
    method reset (line 204) | def reset(self):
    method normgrad (line 207) | def normgrad(self, force=False):
    method normweight (line 218) | def normweight(self, clip=False):
    method getthresh (line 231) | def getthresh(self, scale):
    method updatethresh (line 236) | def updatethresh(self, plus=0.05):
  class STDPFlatten (line 243) | class STDPFlatten(nn.Module):
    method __init__ (line 244) | def __init__(self, start_dim=0, end_dim=-1):
    method forward (line 248) | def forward(self, x, T):  # [batch,T,c,w,h]
  class STDPMaxPool (line 253) | class STDPMaxPool(nn.Module):
    method __init__ (line 254) | def __init__(self, kernel_size, stride, padding, static=True):
    method forward (line 259) | def forward(self, x, T):  # [batch,T,c,w,h]
  class Normliaze (line 274) | class Normliaze(nn.Module):
    method __init__ (line 275) | def __init__(self, static=True):
    method forward (line 279) | def forward(self, x, T):  # [batch,T,c,w,h]
  class voting (line 287) | class voting(nn.Module):
    method __init__ (line 289) | def __init__(self, shape):
    method assign_labels (line 293) | def assign_labels(self, spikes, labels, rates=None, n_labels=10, alpha...
    method get_label (line 315) | def get_label(self, spikes):
  class Conv_Net (line 333) | class Conv_Net(nn.Module):
    method __init__ (line 334) | def __init__(self):
    method forward (line 351) | def forward(self, x, inlayer, outlayer, T, onespike=True):  # [b,t,w,h]
    method normgrad (line 357) | def normgrad(self, layer, force=False):
    method normweight (line 360) | def normweight(self, layer, clip=False):
    method updatethresh (line 363) | def updatethresh(self, layer, plus=0.05):
    method reset (line 366) | def reset(self, layer):
  function plot_confusion_matrix (line 374) | def plot_confusion_matrix(cm, classes, normalize=True, title='Test Confu...

FILE: examples/Perception_and_Learning/img_cls/bp/main.py
  function _parse_args (line 348) | def _parse_args():
  function resnet50d_pretrained (line 366) | def resnet50d_pretrained(*args, **kwargs):
  function main (line 373) | def main():
  function train_epoch (line 745) | def train_epoch(
  function validate (line 895) | def validate(epoch, model, loader, loss_fn, args, amp_autocast=suppress,

FILE: examples/Perception_and_Learning/img_cls/bp/main_backei.py
  function train (line 69) | def train(epoch):
  function eval (line 98) | def eval(epoch):
  function main (line 119) | def main():

FILE: examples/Perception_and_Learning/img_cls/bp/main_simplified.py
  function _parse_args (line 189) | def _parse_args():
  function main (line 206) | def main():
  function train_epoch (line 366) | def train_epoch(
  function validate (line 449) | def validate(model, loader, loss_fn, args, log_suffix='', visualize=Fals...

FILE: examples/Perception_and_Learning/img_cls/glsnn/cls_glsnn.py
  function train (line 52) | def train(epoch):
  function eval (line 81) | def eval(epoch):
  function main (line 101) | def main():

FILE: examples/Perception_and_Learning/img_cls/spiking_capsnet/spikingcaps.py
  class myLIFnode (line 21) | class myLIFnode(LIFNode):
    method __init__ (line 22) | def __init__(self, threshold=0.5, tau=2., *args, **kwargs):
    method integral (line 25) | def integral(self, inputs):
  class ConvLayer (line 30) | class ConvLayer(nn.Module):
    method __init__ (line 31) | def __init__(self, in_channels=1, out_channels=256, kernel_size=9):
    method forward (line 35) | def forward(self, x):
  class PrimaryCaps (line 39) | class PrimaryCaps(nn.Module):
    method __init__ (line 40) | def __init__(self, num_capsules=8, in_channels=256, out_channels=32, k...
    method forward (line 47) | def forward(self, x):
  class DigitCaps (line 55) | class DigitCaps(nn.Module):
    method __init__ (line 56) | def __init__(self, num_capsules=10, num_routes=32 * 6 * 6, in_channels...
    method forward (line 69) | def forward(self, x):
  class DigitCaps2 (line 78) | class DigitCaps2(nn.Module):
    method __init__ (line 79) | def __init__(self, num_capsules=10, num_routes=32 * 6 * 6):
    method forward (line 87) | def forward(self, u_hat):
    method init_bij (line 92) | def init_bij(self):
  class Decoder (line 97) | class Decoder(nn.Module):
    method __init__ (line 98) | def __init__(self):
    method forward (line 102) | def forward(self, x):
  class CapsNet (line 108) | class CapsNet(nn.Module):
    method __init__ (line 109) | def __init__(self):
    method forward (line 122) | def forward(self, data, time_window=5, train=True):
    method init (line 152) | def init(self):
  function evaluate (line 159) | def evaluate(test_iter, net, device):

FILE: examples/Perception_and_Learning/img_cls/transfer_for_dvs/GradCAM_visualization.py
  function get_proj (line 366) | def get_proj(self):
  function event_vis_raw (line 415) | def event_vis_raw(x):
  function get_dataloader_ncal (line 449) | def get_dataloader_ncal(step, **kwargs):
  function _parse_args (line 486) | def _parse_args():
  function main (line 503) | def main():
  function event_frame_plot_2d (line 848) | def event_frame_plot_2d(event):

FILE: examples/Perception_and_Learning/img_cls/transfer_for_dvs/datasets.py
  class TransferSampler (line 50) | class TransferSampler(torch.utils.data.sampler.Sampler):
    method __init__ (line 56) | def __init__(self, indices):
    method __iter__ (line 59) | def __iter__(self):
    method __len__ (line 62) | def __len__(self):
  class Transfer_DataSet (line 65) | class Transfer_DataSet(torchvision.datasets.VisionDataset):
    method __init__ (line 66) | def __init__(self, data, label):
    method __getitem__ (line 71) | def __getitem__(self, mask):
    method __len__ (line 76) | def __len__(self):
  class ConvertHSV (line 81) | class ConvertHSV(object):
    method __init__ (line 87) | def __init__(self):
    method __call__ (line 91) | def __call__(self, img):
  function unpack_mix_param (line 103) | def unpack_mix_param(args):
  function build_transform (line 116) | def build_transform(is_train, img_size, use_hsv=True):
  function build_dataset (line 167) | def build_dataset(is_train, img_size, dataset, path, same_da=False, use_...
  class MNISTData (line 199) | class MNISTData(object):
    method __init__ (line 204) | def __init__(self,
    method get_data_loaders (line 221) | def get_data_loaders(self):
    method get_standard_data (line 235) | def get_standard_data(self):
  function get_mnist_data (line 246) | def get_mnist_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_fashion_data (line 292) | def get_fashion_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_cifar10_data (line 325) | def get_cifar10_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_cifar100_data (line 351) | def get_cifar100_data(batch_size, num_workers=8, same_data=False, *args,...
  function get_transfer_cifar10_data (line 374) | def get_transfer_cifar10_data(batch_size, num_workers=8, same_da=False, ...
  function get_combined_cifar10_data (line 399) | def get_combined_cifar10_data(batch_size, num_workers=8, same_da=False, ...
  function get_transfer_CALTECH101_data (line 413) | def get_transfer_CALTECH101_data(batch_size, num_workers=8, same_da=Fals...
  function get_combined_CALTECH101_data (line 435) | def get_combined_CALTECH101_data(batch_size, num_workers=8, same_da=Fals...
  function get_TinyImageNet_data (line 457) | def get_TinyImageNet_data(batch_size, num_workers=8, same_da=False, *arg...
  function get_transfer_imnet_data (line 490) | def get_transfer_imnet_data(args, _logger, data_config, num_aug_splits, ...
  function get_dvsg_data (line 529) | def get_dvsg_data(batch_size, step, **kwargs):
  function get_dvsc10_data (line 629) | def get_dvsc10_data(batch_size, step, dvs_da=False, **kwargs):
  function get_transfer_dvsc10_data (line 747) | def get_transfer_dvsc10_data(batch_size, step, dvs_da=False, **kwargs):
  function get_NCALTECH101_data (line 837) | def get_NCALTECH101_data(batch_size, step, dvs_da=False, **kwargs):
  function get_transfer_NCALTECH101_data (line 974) | def get_transfer_NCALTECH101_data(batch_size, step, dvs_da=False, **kwar...
  function get_NCARS_data (line 1067) | def get_NCARS_data(batch_size, step, **kwargs):
  function get_nomni_data (line 1165) | def get_nomni_data(batch_size, train_portion=1., **kwargs):
  function get_transfer_omni_data (line 1229) | def get_transfer_omni_data(batch_size, train_portion=1., **kwargs):
  function get_esimnet_data (line 1259) | def get_esimnet_data(batch_size, step, **kwargs):
  function get_CUB2002011_data (line 1359) | def get_CUB2002011_data(batch_size, num_workers=8, same_da=False, *args,...
  function get_StanfordCars_data (line 1390) | def get_StanfordCars_data(batch_size, num_workers=8, same_da=False, *arg...
  function get_StanfordDogs_data (line 1421) | def get_StanfordDogs_data(batch_size, num_workers=8, same_da=False, *arg...
  function get_FGVCAircraft_data (line 1453) | def get_FGVCAircraft_data(batch_size, num_workers=8, same_da=False, *arg...
  function get_Flowers102_data (line 1485) | def get_Flowers102_data(batch_size, num_workers=8, same_da=False, *args,...

FILE: examples/Perception_and_Learning/img_cls/transfer_for_dvs/main.py
  function _parse_args (line 359) | def _parse_args():
  function main (line 376) | def main():
  function train_epoch (line 745) | def train_epoch(
  function validate (line 944) | def validate(epoch, model, loader, loss_fn, args, amp_autocast=suppress,

FILE: examples/Perception_and_Learning/img_cls/transfer_for_dvs/main_transfer.py
  function _parse_args (line 384) | def _parse_args():
  function main (line 401) | def main():
  function train_epoch (line 860) | def train_epoch(
  function validate (line 1211) | def validate(epoch, model, loader, loss_fn, args, amp_autocast=suppress,

FILE: examples/Perception_and_Learning/img_cls/transfer_for_dvs/main_visual_losslandscape.py
  function _parse_args (line 402) | def _parse_args():
  function main (line 419) | def main():

FILE: examples/Snn_safety/DPSNN/load_data.py
  class CustomDataset (line 23) | class CustomDataset(Dataset):
    method __init__ (line 27) | def __init__(self, dataset, indices):
    method __len__ (line 31) | def __len__(self):
    method __getitem__ (line 34) | def __getitem__(self, item):
  function load_static_data (line 39) | def load_static_data(data_root, batch_size, dataset):
  function load_dvs10_data (line 107) | def load_dvs10_data(batch_size, step, **kwargs):
  function load_nmnist_data (line 161) | def load_nmnist_data(batch_size, step, **kwargs):

FILE: examples/Snn_safety/DPSNN/main_dpsnn.py
  function train (line 38) | def train(model, device, train_loader, optimizer, epoch, privacy_engine):
  function test (line 76) | def test(model, device, test_loader):
  function run (line 104) | def run():

FILE: examples/Snn_safety/DPSNN/model.py
  class TEP (line 13) | class TEP(nn.Module):
    method __init__ (line 14) | def __init__(self, step, channel, device=None, dtype=None):
    method forward (line 21) | def forward(self, x):
  class BaseConvNet (line 33) | class BaseConvNet(BaseModule, abc.ABC):
    method __init__ (line 34) | def __init__(self,
    method _create_feature (line 77) | def _create_feature(self):
    method _create_fc (line 81) | def _create_fc(self):
    method forward (line 84) | def forward(self, inputs):
  class LayerWiseConvModule (line 123) | class LayerWiseConvModule(nn.Module):
    method __init__ (line 136) | def __init__(self,
    method forward (line 164) | def forward(self, x):
  class LayerWiseLinearModule (line 177) | class LayerWiseLinearModule(nn.Module):
    method __init__ (line 188) | def __init__(self,
    method forward (line 217) | def forward(self, x):
  class LayWiseConvNet (line 239) | class LayWiseConvNet(BaseConvNet):
    method __init__ (line 240) | def __init__(self,
    method _create_feature (line 262) | def _create_feature(self):
    method _create_fc (line 303) | def _create_fc(self):
  function cifar_convnet (line 314) | def cifar_convnet(step,
  function dvs_convnet (line 342) | def dvs_convnet(step,
  class SimpleSNN (line 372) | class SimpleSNN(BaseModule, abc.ABC):
    method __init__ (line 373) | def __init__(self,
    method forward (line 400) | def forward(self, inputs):

FILE: examples/Snn_safety/RandHet-SNN/evaluate.py
  function get_args (line 28) | def get_args():
  function evaluate_attack (line 44) | def evaluate_attack(model, test_loader, args, atk, atk_name, logger):
  function main (line 74) | def main():

FILE: examples/Snn_safety/RandHet-SNN/my_node.py
  class RHLIFNode (line 4) | class RHLIFNode(BaseNode):
    method __init__ (line 23) | def __init__(self, threshold=0.5, tau=0., sigma=1.0, act_fun=AtanGrad,...
    method integral (line 36) | def integral(self, inputs):
    method calc_spike (line 40) | def calc_spike(self):
    method n_reset (line 45) | def n_reset(self):
  class RHLIFNode2 (line 52) | class RHLIFNode2(BaseNode):
    method __init__ (line 71) | def __init__(self, threshold=0.5, tau=0., sigma=1.0, act_fun=AtanGrad,...
    method integral (line 85) | def integral(self, inputs):
    method calc_spike (line 91) | def calc_spike(self):
    method n_reset (line 96) | def n_reset(self):

FILE: examples/Snn_safety/RandHet-SNN/sew_resnet.py
  function sew_function (line 16) | def sew_function(x: torch.Tensor, y: torch.Tensor, cnf: str):
  function conv3x3 (line 27) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 33) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 38) | class BasicBlock(nn.Module):
    method __init__ (line 41) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 63) | def forward(self, x):
    method extra_repr (line 81) | def extra_repr(self) -> str:
  class Bottleneck (line 85) | class Bottleneck(nn.Module):
    method __init__ (line 94) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 116) | def forward(self, x):
    method extra_repr (line 138) | def extra_repr(self) -> str:
  class SEWResNet19 (line 142) | class SEWResNet19(BaseModule):
    method __init__ (line 143) | def __init__(self, block, layers, num_classes=1000, step=8, encode_typ...
    method _make_layer (line 206) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False, c...
    method _forward_impl (line 231) | def _forward_impl(self, inputs):
    method _forward_once (line 263) | def _forward_once(self, x):
    method forward (line 282) | def forward(self, x):

FILE: examples/Snn_safety/RandHet-SNN/train.py
  function get_args (line 28) | def get_args():
  function main (line 63) | def main():

FILE: examples/Snn_safety/RandHet-SNN/utils.py
  function get_norm_stat (line 14) | def get_norm_stat(mean, std):
  function clamp (line 23) | def clamp(X, lower_limit, upper_limit):
  function normalize_fn (line 27) | def normalize_fn(tensor, mean, std):
  class NormalizeByChannelMeanStd (line 35) | class NormalizeByChannelMeanStd(nn.Module):
    method __init__ (line 36) | def __init__(self, mean, std):
    method forward (line 45) | def forward(self, tensor):
    method extra_repr (line 48) | def extra_repr(self):
  function get_loaders (line 52) | def get_loaders(dir_, batch_size, dataset='cifar10', worker=4, norm=True):
  function evaluate_standard (line 107) | def evaluate_standard(test_loader, model, args):
  function orthogonal_retraction (line 124) | def orthogonal_retraction(model, beta=0.002):

FILE: examples/Social_Cognition/FOToM/algorithms/ToM_class.py
  class ToM1 (line 7) | class ToM1(object):
    method __init__ (line 14) | def __init__(self, tom_base, alg_types, agent_types, num_lm, device, h...
    method _agent_tom1_init (line 34) | def _agent_tom1_init(self):
    method _get_index1 (line 48) | def _get_index1(self, lst=None, item=''):
    method c_function (line 51) | def c_function(self, tom0_actions_q, tom1_actions_q):
    method tom1_output (line 70) | def tom1_output(self, agent_i, adv_indx, good_indx, obs_, acs_pre_):

FILE: examples/Social_Cognition/FOToM/algorithms/maddpg.py
  class MADDPG (line 17) | class MADDPG(object):
    method __init__ (line 18) | def __init__(self, agent_init_params, alg_types, device,
    method policies (line 55) | def policies(self):
    method target_policies (line 59) | def target_policies(self):
    method scale_noise (line 62) | def scale_noise(self, scale):
    method reset_noise (line 71) | def reset_noise(self):
    method step (line 75) | def step(self, observations, explore=False):
    method update (line 87) | def update(self, sample, agent_i, parallel=False, logger=None):
    method update_all_targets (line 179) | def update_all_targets(self):
    method prep_training (line 189) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 216) | def prep_rollouts(self, device='cpu'):
    method save (line 229) | def save(self, filename):
    method init_from_env (line 239) | def init_from_env(cls, env, device, agent_alg="MADDPG", adversary_alg=...
    method init_from_save (line 291) | def init_from_save(cls, filename):
  class MADDPG_RNN (line 302) | class MADDPG_RNN(object):
    method __init__ (line 306) | def __init__(self, agent_init_params, alg_types,
    method _init_agent (line 341) | def _init_agent(self, n_rollout_threads):
    method policies (line 347) | def policies(self, len_ep):
    method target_policies (line 353) | def target_policies(self, len_ep):
    method scale_noise (line 358) | def scale_noise(self, scale):
    method reset_noise (line 367) | def reset_noise(self):
    method step (line 371) | def step(self, observations, explore=False):
    method _compute_rnn (line 383) | def _compute_rnn(self, fn, hidden, inputs, logit):
    method update (line 398) | def update(self, sample, agent_i, parallel=False, logger=None):
    method update_all_targets (line 481) | def update_all_targets(self):
    method prep_training (line 491) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 518) | def prep_rollouts(self, device='cpu'):
    method save (line 531) | def save(self, filename):
    method init_from_env (line 541) | def init_from_env(cls, env, agent_alg="MADDPG", adversary_alg="MADDPG_...
    method init_from_save (line 580) | def init_from_save(cls, filename):

FILE: examples/Social_Cognition/FOToM/algorithms/tom11.py
  class ToM_decision11 (line 20) | class ToM_decision11(object):
    method __init__ (line 22) | def __init__(self, agent_init_params, alg_types, agent_types, num_lm,
    method policies (line 87) | def policies(self):
    method target_policies (line 91) | def target_policies(self):
    method scale_noise (line 94) | def scale_noise(self, scale):
    method reset_noise (line 103) | def reset_noise(self):
    method _get_index1 (line 107) | def _get_index1(self, lst=None, item=''):
    method _agent_tom_init (line 110) | def _agent_tom_init(self):
    method step (line 124) | def step(self, observations, actions_pre, explore=False):    #simple_tag
    method _get_obs (line 195) | def _get_obs(self, observations, action_tom):
    method train_tom0 (line 205) | def train_tom0(self, sample, agent_i):
    method tom1_infer_other (line 245) | def tom1_infer_other(self, sample):
    method tom0_output (line 328) | def tom0_output(self, sample):
    method update (line 365) | def update(self, sample, agent_i, parallel=False, logger=None, sample_...
    method update_all_targets (line 509) | def update_all_targets(self):
    method prep_training (line 519) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 563) | def prep_rollouts(self, device='cpu'):
    method save (line 576) | def save(self, filename):
    method init_from_env (line 587) | def init_from_env(cls, env, config, device, agent_alg, adversary_alg,
    method init_from_save (line 647) | def init_from_save(cls, filename):
    method get_params (line 661) | def get_params(self):
    method load_params (line 671) | def load_params(self, params):

FILE: examples/Social_Cognition/FOToM/common/distributions.py
  class Pd (line 10) | class Pd(object):
    method flatparam (line 14) | def flatparam(self):
    method mode (line 16) | def mode(self):
    method logp (line 18) | def logp(self, x):
    method kl (line 20) | def kl(self, other):
    method entropy (line 22) | def entropy(self):
    method sample (line 24) | def sample(self):
  class PdType (line 27) | class PdType(object):
    method pdclass (line 31) | def pdclass(self):
    method pdfromflat (line 33) | def pdfromflat(self, flat):
    method param_shape (line 35) | def param_shape(self):
    method sample_shape (line 37) | def sample_shape(self):
    method sample_dtype (line 39) | def sample_dtype(self):
    method param_placeholder (line 42) | def param_placeholder(self, prepend_shape, name=None):
    method sample_placeholder (line 44) | def sample_placeholder(self, prepend_shape, name=None):
  class CategoricalPdType (line 47) | class CategoricalPdType(PdType):
    method __init__ (line 48) | def __init__(self, ncat):
    method pdclass (line 50) | def pdclass(self):
    method param_shape (line 52) | def param_shape(self):
    method sample_shape (line 54) | def sample_shape(self):
    method sample_dtype (line 56) | def sample_dtype(self):
  class SoftCategoricalPdType (line 59) | class SoftCategoricalPdType(PdType):
    method __init__ (line 60) | def __init__(self, ncat):
    method pdclass (line 62) | def pdclass(self):
    method param_shape (line 64) | def param_shape(self):
    method sample_shape (line 66) | def sample_shape(self):
    method sample_dtype (line 68) | def sample_dtype(self):
  class MultiCategoricalPdType (line 71) | class MultiCategoricalPdType(PdType):
    method __init__ (line 72) | def __init__(self, low, high):
    method pdclass (line 76) | def pdclass(self):
    method pdfromflat (line 78) | def pdfromflat(self, flat):
    method param_shape (line 80) | def param_shape(self):
    method sample_shape (line 82) | def sample_shape(self):
    method sample_dtype (line 84) | def sample_dtype(self):
  class SoftMultiCategoricalPdType (line 87) | class SoftMultiCategoricalPdType(PdType):
    method __init__ (line 88) | def __init__(self, low, high):
    method pdclass (line 92) | def pdclass(self):
    method pdfromflat (line 94) | def pdfromflat(self, flat):
    method param_shape (line 96) | def param_shape(self):
    method sample_shape (line 98) | def sample_shape(self):
    method sample_dtype (line 100) | def sample_dtype(self):
  class DiagGaussianPdType (line 103) | class DiagGaussianPdType(PdType):
    method __init__ (line 104) | def __init__(self, size):
    method pdclass (line 106) | def pdclass(self):
    method param_shape (line 108) | def param_shape(self):
    method sample_shape (line 110) | def sample_shape(self):
    method sample_dtype (line 112) | def sample_dtype(self):
  class BernoulliPdType (line 115) | class BernoulliPdType(PdType):
    method __init__ (line 116) | def __init__(self, size):
    method pdclass (line 118) | def pdclass(self):
    method param_shape (line 120) | def param_shape(self):
    method sample_shape (line 122) | def sample_shape(self):
    method sample_dtype (line 124) | def sample_dtype(self):
  class CategoricalPd (line 150) | class CategoricalPd(Pd):
    method __init__ (line 151) | def __init__(self, logits):
    method flatparam (line 153) | def flatparam(self):
    method mode (line 155) | def mode(self):
    method logp (line 157) | def logp(self, x):
    method kl (line 159) | def kl(self, other):
    method entropy (line 168) | def entropy(self):
    method sample (line 174) | def sample(self):
    method fromflat (line 178) | def fromflat(cls, flat):
  class SoftCategoricalPd (line 181) | class SoftCategoricalPd(Pd):
    method __init__ (line 182) | def __init__(self, logits):
    method flatparam (line 184) | def flatparam(self):
    method mode (line 186) | def mode(self):
    method logp (line 188) | def logp(self, x):
    method kl (line 190) | def kl(self, other):
    method entropy (line 199) | def entropy(self):
    method sample (line 205) | def sample(self):
    method fromflat (line 209) | def fromflat(cls, flat):
  class MultiCategoricalPd (line 212) | class MultiCategoricalPd(Pd):
    method __init__ (line 213) | def __init__(self, low, high, flat):
    method flatparam (line 217) | def flatparam(self):
    method mode (line 219) | def mode(self):
    method logp (line 221) | def logp(self, x):
    method kl (line 223) | def kl(self, other):
    method entropy (line 227) | def entropy(self):
    method sample (line 229) | def sample(self):
    method fromflat (line 232) | def fromflat(cls, flat):
  class SoftMultiCategoricalPd (line 235) | class SoftMultiCategoricalPd(Pd):  # doesn't work yet
    method __init__ (line 236) | def __init__(self, low, high, flat):
    method flatparam (line 240) | def flatparam(self):
    method mode (line 242) | def mode(self):
    method logp (line 247) | def logp(self, x):
    method kl (line 249) | def kl(self, other):
    method entropy (line 253) | def entropy(self):
    method sample (line 255) | def sample(self):
    method fromflat (line 261) | def fromflat(cls, flat):
  class DiagGaussianPd (line 264) | class DiagGaussianPd(Pd):
    method __init__ (line 265) | def __init__(self, flat):
    method flatparam (line 271) | def flatparam(self):
    method mode (line 273) | def mode(self):
    method logp (line 275) | def logp(self, x):
    method kl (line 279) | def kl(self, other):
    method entropy (line 282) | def entropy(self):
    method sample (line 284) | def sample(self):
    method fromflat (line 287) | def fromflat(cls, flat):
  class BernoulliPd (line 290) | class BernoulliPd(Pd):
    method __init__ (line 291) | def __init__(self, logits):
    method flatparam (line 294) | def flatparam(self):
    method mode (line 296) | def mode(self):
    method logp (line 298) | def logp(self, x):
    method kl (line 300) | def kl(self, other):
    method entropy (line 302) | def entropy(self):
    method sample (line 304) | def sample(self):
    method fromflat (line 309) | def fromflat(cls, flat):
  function make_pdtype (line 312) | def make_pdtype(ac_space):
  function shape_el (line 328) | def shape_el(v, i):

FILE: examples/Social_Cognition/FOToM/common/tile_images.py
  function tile_images (line 3) | def tile_images(img_nhwc):

FILE: examples/Social_Cognition/FOToM/common/vec_env/vec_env.py
  class AlreadySteppingError (line 7) | class AlreadySteppingError(Exception):
    method __init__ (line 13) | def __init__(self):
  class NotSteppingError (line 18) | class NotSteppingError(Exception):
    method __init__ (line 24) | def __init__(self):
  class VecEnv (line 29) | class VecEnv(ABC):
    method __init__ (line 43) | def __init__(self, num_envs, observation_space, action_space):
    method reset (line 49) | def reset(self):
    method step_async (line 61) | def step_async(self, actions):
    method step_wait (line 73) | def step_wait(self):
    method close_extras (line 86) | def close_extras(self):
    method close (line 93) | def close(self):
    method step (line 101) | def step(self, actions):
    method render (line 110) | def render(self, mode='human'):
    method get_images (line 121) | def get_images(self):
    method unwrapped (line 128) | def unwrapped(self):
    method get_viewer (line 134) | def get_viewer(self):
  class VecEnvWrapper (line 140) | class VecEnvWrapper(VecEnv):
    method __init__ (line 146) | def __init__(self, venv, observation_space=None, action_space=None):
    method step_async (line 152) | def step_async(self, actions):
    method reset (line 156) | def reset(self):
    method step_wait (line 160) | def step_wait(self):
    method close (line 163) | def close(self):
    method render (line 166) | def render(self, mode='human'):
    method get_images (line 169) | def get_images(self):
    method __getattr__ (line 172) | def __getattr__(self, name):
  class VecEnvObservationWrapper (line 177) | class VecEnvObservationWrapper(VecEnvWrapper):
    method process (line 179) | def process(self, obs):
    method reset (line 182) | def reset(self):
    method step_wait (line 186) | def step_wait(self):
  class CloudpickleWrapper (line 190) | class CloudpickleWrapper(object):
    method __init__ (line 195) | def __init__(self, x):
    method __getstate__ (line 198) | def __getstate__(self):
    method __setstate__ (line 202) | def __setstate__(self, ob):
  function clear_mpi_env_vars (line 208) | def clear_mpi_env_vars():

FILE: examples/Social_Cognition/FOToM/evaluate.py
  function display_frames_as_gif (line 15) | def display_frames_as_gif(frames):
  function make_parallel_env (line 21) | def make_parallel_env(env_id, n_rollout_threads, discrete_action, num_go...
  function run (line 34) | def run(config):

FILE: examples/Social_Cognition/FOToM/main.py
  function get_common_args (line 22) | def get_common_args():
  function make_parallel_env (line 76) | def make_parallel_env(env_id, n_rollout_threads, seed, discrete_action, ...
  function run (line 89) | def run(config):

FILE: examples/Social_Cognition/FOToM/multiagent/core.py
  class EntityState (line 4) | class EntityState(object):
    method __init__ (line 5) | def __init__(self):
  class AgentState (line 12) | class AgentState(EntityState):
    method __init__ (line 13) | def __init__(self):
  class Action (line 19) | class Action(object):
    method __init__ (line 20) | def __init__(self):
  class Entity (line 27) | class Entity(object):
    method __init__ (line 28) | def __init__(self):
    method mass (line 50) | def mass(self):
  class Landmark (line 54) | class Landmark(Entity):
    method __init__ (line 55) | def __init__(self):
  class Agent (line 59) | class Agent(Entity):
    method __init__ (line 60) | def __init__(self):
  class World (line 82) | class World(object):
    method __init__ (line 83) | def __init__(self):
    method entities (line 103) | def entities(self):
    method policy_agents (line 108) | def policy_agents(self):
    method scripted_agents (line 113) | def scripted_agents(self):
    method step (line 117) | def step(self):
    method apply_action_force (line 134) | def apply_action_force(self, p_force):
    method apply_environment_force (line 143) | def apply_environment_force(self, p_force):
    method integrate_state (line 158) | def integrate_state(self, p_force):
    method update_agent_state (line 171) | def update_agent_state(self, agent):
    method get_collision_force (line 180) | def get_collision_force(self, entity_a, entity_b):

FILE: examples/Social_Cognition/FOToM/multiagent/environment.py
  class MultiAgentEnv (line 9) | class MultiAgentEnv(gym.Env):
    method __init__ (line 14) | def __init__(self, world, reset_callback=None, reward_callback=None,
    method step (line 80) | def step(self, action_n):
    method reset (line 106) | def reset(self):
    method _get_info (line 119) | def _get_info(self, agent):
    method _get_obs (line 125) | def _get_obs(self, agent):
    method _get_done (line 132) | def _get_done(self, agent):
    method _get_reward (line 138) | def _get_reward(self, agent):
    method _set_action (line 144) | def _set_action(self, action, agent, action_space, time=None):
    method _reset_render (line 195) | def _reset_render(self):
    method render (line 200) | def render(self, mode='human'):
    method _make_receptor_locations (line 266) | def _make_receptor_locations(self, agent):
  class BatchMultiAgentEnv (line 288) | class BatchMultiAgentEnv(gym.Env):
    method __init__ (line 294) | def __init__(self, env_batch):
    method n (line 298) | def n(self):
    method action_space (line 302) | def action_space(self):
    method observation_space (line 306) | def observation_space(self):
    method step (line 309) | def step(self, action_n, time):
    method reset (line 324) | def reset(self):
    method render (line 331) | def render(self, mode='human', close=True):

FILE: examples/Social_Cognition/FOToM/multiagent/multi_discrete.py
  class MultiDiscrete (line 9) | class MultiDiscrete(gym.Space):
    method __init__ (line 25) | def __init__(self, array_of_param_array):
    method sample (line 30) | def sample(self):
    method contains (line 36) | def contains(self, x):
    method shape (line 40) | def shape(self):
    method __repr__ (line 42) | def __repr__(self):
    method __eq__ (line 44) | def __eq__(self, other):

FILE: examples/Social_Cognition/FOToM/multiagent/policy.py
  class Policy (line 5) | class Policy(object):
    method __init__ (line 6) | def __init__(self):
    method action (line 8) | def action(self, obs):
  class InteractivePolicy (line 13) | class InteractivePolicy(Policy):
    method __init__ (line 14) | def __init__(self, env, agent_index):
    method action (line 24) | def action(self, obs):
    method key_press (line 43) | def key_press(self, k, mod):
    method key_release (line 48) | def key_release(self, k, mod):

FILE: examples/Social_Cognition/FOToM/multiagent/rendering.py
  function get_display (line 33) | def get_display(spec):
  class Viewer (line 46) | class Viewer(object):
    method __init__ (line 47) | def __init__(self, width, height, display=None):
    method close (line 67) | def close(self):
    method window_closed_by_user (line 70) | def window_closed_by_user(self):
    method set_bounds (line 73) | def set_bounds(self, left, right, bottom, top):
    method add_geom (line 81) | def add_geom(self, geom):
    method add_onetime (line 84) | def add_onetime(self, geom):
    method render (line 87) | def render(self, return_rgb_array=False):
    method draw_circle (line 116) | def draw_circle(self, radius=10, res=30, filled=True, **attrs):
    method draw_polygon (line 122) | def draw_polygon(self, v, filled=True, **attrs):
    method draw_polyline (line 128) | def draw_polyline(self, v, **attrs):
    method draw_line (line 134) | def draw_line(self, start, end, **attrs):
    method get_array (line 140) | def get_array(self):
  function _add_attrs (line 148) | def _add_attrs(geom, attrs):
  class Geom (line 154) | class Geom(object):
    method __init__ (line 155) | def __init__(self):
    method render (line 158) | def render(self):
    method render1 (line 164) | def render1(self):
    method add_attr (line 166) | def add_attr(self, attr):
    method set_color (line 168) | def set_color(self, r, g, b, alpha=1):
  class Attr (line 171) | class Attr(object):
    method enable (line 172) | def enable(self):
    method disable (line 174) | def disable(self):
  class Transform (line 177) | class Transform(Attr):
    method __init__ (line 178) | def __init__(self, translation=(0.0, 0.0), rotation=0.0, scale=(1,1)):
    method enable (line 182) | def enable(self):
    method disable (line 187) | def disable(self):
    method set_translation (line 189) | def set_translation(self, newx, newy):
    method set_rotation (line 191) | def set_rotation(self, new):
    method set_scale (line 193) | def set_scale(self, newx, newy):
  class Color (line 196) | class Color(Attr):
    method __init__ (line 197) | def __init__(self, vec4):
    method enable (line 199) | def enable(self):
  class LineStyle (line 202) | class LineStyle(Attr):
    method __init__ (line 203) | def __init__(self, style):
    method enable (line 205) | def enable(self):
    method disable (line 208) | def disable(self):
  class LineWidth (line 211) | class LineWidth(Attr):
    method __init__ (line 212) | def __init__(self, stroke):
    method enable (line 214) | def enable(self):
  class Point (line 217) | class Point(Geom):
    method __init__ (line 218) | def __init__(self):
    method render1 (line 220) | def render1(self):
  class FilledPolygon (line 225) | class FilledPolygon(Geom):
    method __init__ (line 226) | def __init__(self, v):
    method render1 (line 229) | def render1(self):
  function make_circle (line 244) | def make_circle(radius=10, res=30, filled=True):
  function make_polygon (line 254) | def make_polygon(v, filled=True):
  function make_polyline (line 258) | def make_polyline(v):
  function make_capsule (line 261) | def make_capsule(length, width):
  class Compound (line 270) | class Compound(Geom):
    method __init__ (line 271) | def __init__(self, gs):
    method render1 (line 276) | def render1(self):
  class PolyLine (line 280) | class PolyLine(Geom):
    method __init__ (line 281) | def __init__(self, v, close):
    method render1 (line 287) | def render1(self):
    method set_linewidth (line 292) | def set_linewidth(self, x):
  class Line (line 295) | class Line(Geom):
    method __init__ (line 296) | def __init__(self, start=(0.0, 0.0), end=(0.0, 0.0)):
    method render1 (line 303) | def render1(self):
  class Image (line 309) | class Image(Geom):
    method __init__ (line 310) | def __init__(self, fname, width, height):
    method render1 (line 317) | def render1(self):
  class SimpleImageViewer (line 322) | class SimpleImageViewer(object):
    method __init__ (line 323) | def __init__(self, display=None):
    method imshow (line 327) | def imshow(self, arr):
    method close (line 341) | def close(self):
    method __del__ (line 345) | def __del__(self):

FILE: examples/Social_Cognition/FOToM/multiagent/scenario.py
  class BaseScenario (line 4) | class BaseScenario(object):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 9) | def reset_world(self, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/__init__.py
  function load (line 5) | def load(name):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/hetero_spread.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, num_good_agents=2, num_adversaries=0):
    method reset_world (line 46) | def reset_world(self, world):
    method benchmark_data (line 67) | def benchmark_data(self, agent, world):
    method is_collision (line 86) | def is_collision(self, agent1, agent2):
    method reward (line 92) | def reward(self, agent, world):
    method observation (line 126) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 24) | def reset_world(self, world):
    method reward (line 41) | def reward(self, agent, world):
    method observation (line 45) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_adversary.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 8) | def make_world(self, num_good_agents=2, num_adversaries=1):
    method reset_world (line 37) | def reset_world(self, world):
    method benchmark_data (line 59) | def benchmark_data(self, agent, world):
    method good_agents (line 71) | def good_agents(self, world):
    method adversaries (line 75) | def adversaries(self, world):
    method reward (line 78) | def reward(self, agent, world):
    method agent_reward (line 82) | def agent_reward(self, agent, world):
    method adversary_reward (line 111) | def adversary_reward(self, agent, world):
    method observation (line 123) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_crypto.py
  class CryptoAgent (line 14) | class CryptoAgent(Agent):
    method __init__ (line 15) | def __init__(self):
  class Scenario (line 19) | class Scenario(BaseScenario):
    method make_world (line 21) | def make_world(self):
    method reset_world (line 47) | def reset_world(self, world):
    method benchmark_data (line 78) | def benchmark_data(self, agent, world):
    method good_listeners (line 83) | def good_listeners(self, world):
    method good_agents (line 87) | def good_agents(self, world):
    method adversaries (line 91) | def adversaries(self, world):
    method reward (line 94) | def reward(self, agent, world):
    method agent_reward (line 97) | def agent_reward(self, agent, world):
    method adversary_reward (line 116) | def adversary_reward(self, agent, world):
    method observation (line 124) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_push.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self, num_good_agents=2, num_adversaries=2):
    method reset_world (line 33) | def reset_world(self, world):
    method reward (line 58) | def reward(self, agent, world):
    method good_agents (line 62) | def good_agents(self, world):
    method adversaries (line 66) | def adversaries(self, world):
    method is_collision (line 69) | def is_collision(self, agent1, agent2):
    method agent_reward (line 75) | def agent_reward(self, agent, world):
    method adversary_reward (line 104) | def adversary_reward(self, agent, world):
    method observation (line 130) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_reference.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self, num_good_agents=2, num_adversaries=0):
    method reset_world (line 26) | def reset_world(self, world):
    method reward (line 55) | def reward(self, agent, world):
    method observation (line 61) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_speaker_listener.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 33) | def reset_world(self, world):
    method benchmark_data (line 59) | def benchmark_data(self, agent, world):
    method reward (line 63) | def reward(self, agent, world):
    method observation (line 69) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_spread.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, num_good_agents=2, num_adversaries=2):
    method reset_world (line 31) | def reset_world(self, world):
    method benchmark_data (line 47) | def benchmark_data(self, agent, world):
    method is_collision (line 66) | def is_collision(self, agent1, agent2):
    method reward (line 72) | def reward(self, agent, world):
    method observation (line 106) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_tag.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, num_good_agents=1, num_adversaries=3):
    method reset_world (line 39) | def reset_world(self, world):
    method benchmark_data (line 57) | def benchmark_data(self, agent, world):
    method is_collision (line 69) | def is_collision(self, agent1, agent2):
    method good_agents (line 76) | def good_agents(self, world):
    method adversaries (line 80) | def adversaries(self, world):
    method reward (line 84) | def reward(self, agent, world):
    method agent_reward (line 89) | def agent_reward(self, agent, world):
    method adversary_reward (line 115) | def adversary_reward(self, agent, world):
    method observation (line 131) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/multiagent/scenarios/simple_world_comm.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, num_good_agents=2, num_adversaries=4):
    method set_boundaries (line 59) | def set_boundaries(self, world):
    method reset_world (line 88) | def reset_world(self, world):
    method benchmark_data (line 115) | def benchmark_data(self, agent, world):
    method is_collision (line 126) | def is_collision(self, agent1, agent2):
    method good_agents (line 134) | def good_agents(self, world):
    method adversaries (line 138) | def adversaries(self, world):
    method reward (line 142) | def reward(self, agent, world):
    method outside_boundary (line 148) | def outside_boundary(self, agent):
    method agent_reward (line 155) | def agent_reward(self, agent, world):
    method adversary_reward (line 185) | def adversary_reward(self, agent, world):
    method observation2 (line 201) | def observation2(self, agent, world):
    method observation (line 224) | def observation(self, agent, world):

FILE: examples/Social_Cognition/FOToM/utils/agents.py
  class DDPGAgent (line 10) | class DDPGAgent(object):
    method __init__ (line 15) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, hidden_dim=64,
    method reset_noise (line 47) | def reset_noise(self):
    method scale_noise (line 51) | def scale_noise(self, scale):
    method step (line 57) | def step(self, obs, explore=False):
    method get_params (line 89) | def get_params(self):
    method load_params (line 97) | def load_params(self, params):
  class DDPGAgent_RNN (line 105) | class DDPGAgent_RNN(object):
    method __init__ (line 110) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, hidden_dim=64,
    method reset_noise (line 150) | def reset_noise(self):
    method scale_noise (line 154) | def scale_noise(self, scale):
    method step (line 160) | def step(self, obs, explore=False):
    method get_params (line 183) | def get_params(self):
    method load_params (line 191) | def load_params(self, params):
    method init_hidden (line 199) | def init_hidden(self, len_ep, policy_hidden=False, policy_target_hidde...
  class DDPGAgent_SNN (line 211) | class DDPGAgent_SNN(object):
    method __init__ (line 216) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, output_styl...
    method reset_noise (line 246) | def reset_noise(self):
    method scale_noise (line 250) | def scale_noise(self, scale):
    method step (line 256) | def step(self, obs, explore=False):
    method get_params (line 297) | def get_params(self):
    method load_params (line 305) | def load_params(self, params):
  class DDPGAgent_ToM (line 313) | class DDPGAgent_ToM(object):
    method __init__ (line 318) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, num_in_mle,...
    method reset_noise (line 366) | def reset_noise(self):
    method scale_noise (line 370) | def scale_noise(self, scale):
    method step (line 376) | def step(self, obs, explore=False):
    method get_params (line 411) | def get_params(self):
    method load_params (line 424) | def load_params(self, params):
  class rDDPGAgent_ToM (line 435) | class rDDPGAgent_ToM(object):
    method __init__ (line 440) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, num_in_mle,...
    method reset_noise (line 485) | def reset_noise(self):
    method scale_noise (line 489) | def scale_noise(self, scale):
    method step (line 495) | def step(self, obs, explore=False):
    method get_params (line 530) | def get_params(self):
    method load_params (line 543) | def load_params(self, params):
    method init_hidden (line 554) | def init_hidden(self, len_ep, policy_hidden=False, policy_target_hidde...
  class lDDPGAgent (line 566) | class lDDPGAgent(object):
    method __init__ (line 571) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, hidden_dim=64,
    method reset_noise (line 603) | def reset_noise(self):
    method scale_noise (line 607) | def scale_noise(self, scale):
    method step (line 613) | def step(self, obs, explore=False):
    method get_params (line 645) | def get_params(self):
    method load_params (line 653) | def load_params(self, params):

FILE: examples/Social_Cognition/FOToM/utils/buffer.py
  class ReplayBuffer (line 6) | class ReplayBuffer(object):
    method __init__ (line 10) | def __init__(self, max_steps, num_agents, obs_dims, ac_dims, device):
    method __len__ (line 37) | def __len__(self):
    method push (line 40) | def push(self, observations, actions, rewards, next_observations, dones):
    method sample (line 72) | def sample(self, N, to_gpu=False, norm_rews=True):
    method get_average_rewards (line 92) | def get_average_rewards(self, N):
  class ReplayBuffer_pre (line 99) | class ReplayBuffer_pre(object):
    method __init__ (line 103) | def __init__(self, max_steps, num_agents, obs_dims, ac_dims, device):
    method __len__ (line 132) | def __len__(self):
    method push (line 135) | def push(self, actions_pre, observations, actions, rewards, next_obser...
    method sample (line 170) | def sample(self, N, to_gpu=False, norm_rews=True):
    method get_average_rewards (line 194) | def get_average_rewards(self, N):
  class ReplayBuffer_RNN (line 202) | class ReplayBuffer_RNN(object):
    method __init__ (line 206) | def __init__(self, max_steps, num_agents, obs_dims, ac_dims, ep_dims, ...
    method __len__ (line 234) | def __len__(self):
    method push (line 237) | def push(self, observations_ep, actions_ep, rewards_ep, next_observati...
    method sample (line 278) | def sample(self, N, to_gpu=False, norm_rews=True):
    method get_average_rewards (line 298) | def get_average_rewards(self, N):

FILE: examples/Social_Cognition/FOToM/utils/env_wrappers.py
  function worker (line 9) | def worker(remote, parent_remote, env_fn_wrapper):
  class SubprocVecEnv (line 42) | class SubprocVecEnv(VecEnv):
    method __init__ (line 43) | def __init__(self, env_fns, spaces=None):
    method step_async (line 67) | def step_async(self, actions):
    method step_wait (line 72) | def step_wait(self):
    method reset (line 78) | def reset(self):
    method reset_task (line 83) | def reset_task(self):
    method close (line 88) | def close(self):
  class DummyVecEnv (line 101) | class DummyVecEnv(VecEnv):
    method __init__ (line 102) | def __init__(self, env_fns):
    method step_async (line 114) | def step_async(self, actions):
    method step_wait (line 117) | def step_wait(self):
    method reset (line 128) | def reset(self):
    method close (line 132) | def close(self):

FILE: examples/Social_Cognition/FOToM/utils/make_env.py
  function make_env (line 15) | def make_env(scenario_name, num_good_agents, num_adversaries, benchmark=...

FILE: examples/Social_Cognition/FOToM/utils/misc.py
  function soft_update (line 9) | def soft_update(target, source, tau):
  function hard_update (line 22) | def hard_update(target, source):
  function average_gradients (line 33) | def average_gradients(model):
  function init_processes (line 41) | def init_processes(rank, size, fn, backend='gloo'):
  function onehot_from_logits (line 48) | def onehot_from_logits(logits, eps=0.0):
  function sample_gumbel (line 65) | def sample_gumbel(shape, eps=1e-20, tens_type=torch.FloatTensor):
  function gumbel_softmax_sample (line 71) | def gumbel_softmax_sample(logits, temperature):
  function gumbel_softmax (line 77) | def gumbel_softmax(logits, temperature=1.0, hard=False):

FILE: examples/Social_Cognition/FOToM/utils/multiprocessing.py
  function _flatten_list (line 10) | def _flatten_list(l):
  function worker (line 18) | def worker(remote, parent_remote, env_fn_wrapper):
  class VecEnv (line 58) | class VecEnv(object):
    method __init__ (line 68) | def __init__(self, num_envs, observation_space, action_space):
    method observe (line 73) | def observe(self, agent):
    method reset (line 76) | def reset(self):
    method step_async (line 86) | def step_async(self, actions):
    method step_wait (line 96) | def step_wait(self):
    method close (line 108) | def close(self):
    method step (line 114) | def step(self, actions):
    method render (line 118) | def render(self, mode='human'):
    method get_images (line 130) | def get_images(self):
    method get_viewer (line 136) | def get_viewer(self):
    method tile_images (line 142) | def tile_images(self, img_nhwc):
  class CloudpickleWrapper (line 162) | class CloudpickleWrapper(object):
    method __init__ (line 167) | def __init__(self, x):
    method __getstate__ (line 170) | def __getstate__(self):
    method __setstate__ (line 174) | def __setstate__(self, ob):
  class SubprocVecEnv (line 179) | class SubprocVecEnv(VecEnv):
    method __init__ (line 180) | def __init__(self, env_fns, spaces=None):
    method step_async (line 203) | def step_async(self, actions):
    method step_wait (line 208) | def step_wait(self):
    method step_wait_2 (line 214) | def step_wait_2(self):
    method step_wait_3 (line 220) | def step_wait_3(self):
    method reset (line 226) | def reset(self):
    method agents (line 231) | def agents(self):
    method world (line 236) | def world(self):
    method reset_task (line 241) | def reset_task(self):
    method spec (line 246) | def spec(self):
    method get_images (line 251) | def get_images(self):
    method observe (line 259) | def observe(self, agent):
    method close (line 267) | def close(self):
    method __len__ (line 279) | def __len__(self):
  function _flatten_list (line 282) | def _flatten_list(l):
  class DummyVecEnv (line 289) | class DummyVecEnv(VecEnv):
    method __init__ (line 290) | def __init__(self, env_fns):
    method step_async (line 302) | def step_async(self, actions):
    method step_wait (line 305) | def step_wait(self):
    method reset (line 316) | def reset(self):
    method close (line 320) | def close(self):

FILE: examples/Social_Cognition/FOToM/utils/networks.py
  class MLPNetwork (line 6) | class MLPNetwork(nn.Module):
    method __init__ (line 10) | def __init__(self, input_dim, out_dim, hidden_dim=64, nonlin=F.relu,
    method forward (line 39) | def forward(self, X):
  class RNN (line 51) | class RNN(nn.Module):
    method __init__ (line 53) | def __init__(self, input_dim, out_dim, hidden_dim=64, nonlin=F.relu,
    method forward (line 73) | def forward(self, obs, hidden_state):
  class BCNoSpikingLIFNode (line 81) | class BCNoSpikingLIFNode(LIFNode):
    method __init__ (line 82) | def __init__(self, *args, **kwargs):
    method forward (line 85) | def forward(self, dv: torch.Tensor):
  class SNNNetwork (line 89) | class SNNNetwork(nn.Module):
    method __init__ (line 93) | def __init__(self, input_dim, out_dim, hidden_dim=64, node=LIFNode, ti...
    method reset (line 127) | def reset(self):
    method forward (line 132) | def forward(self, X):
  class LSTMClassifier (line 153) | class LSTMClassifier(nn.Module):
    method __init__ (line 154) | def __init__(self, input_size, output_size, hidden_size=256):
    method forward (line 159) | def forward(self, x):

FILE: examples/Social_Cognition/FOToM/utils/noise.py
  class OUNoise (line 5) | class OUNoise:
    method __init__ (line 6) | def __init__(self, action_dimension, scale=0.1, mu=0, theta=0.15, sigm...
    method reset (line 15) | def reset(self):
    method noise (line 18) | def noise(self):

FILE: examples/Social_Cognition/Intention_Prediction/Intention_Prediction.py
  class CustomLinear (line 25) | class CustomLinear(nn.Module):
    method __init__ (line 26) | def __init__(self, weight,mask=None):
    method forward (line 31) | def forward(self, x: torch.Tensor):
    method update (line 36) | def update(self, dw):
  class DLPFCNet (line 43) | class DLPFCNet(nn.Module):
    method __init__ (line 44) | def __init__(self,connection):
    method forward (line 57) | def forward(self, input):
    method reset (line 73) | def reset(self):
    method UpdateWeight (line 79) | def UpdateWeight(self, i, W):
  class OFCNet (line 83) | class OFCNet(nn.Module):
    method __init__ (line 84) | def __init__(self,connection):
    method forward (line 105) | def forward(self, Input_Tha, Input_SNc, Reward):
    method reset (line 120) | def reset(self):
  class BGNet (line 127) | class BGNet(nn.Module):
    method __init__ (line 128) | def __init__(self,connection):
    method forward (line 144) | def forward(self, input1, input2, input3):
    method reset (line 154) | def reset(self):
    method UpdateWeight (line 159) | def UpdateWeight(self, i, W):
  function STDP (line 163) | def STDP(Pre_mat, Post_mat, W):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/agents/agents.py
  class DDPGAgent (line 10) | class DDPGAgent(object):
    method __init__ (line 15) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, hidden_dim=64,
    method reset_noise (line 47) | def reset_noise(self):
    method scale_noise (line 51) | def scale_noise(self, scale):
    method step (line 57) | def step(self, obs, explore=False):
    method get_params (line 89) | def get_params(self):
    method load_params (line 97) | def load_params(self, params):
  class DDPGAgent_RNN (line 105) | class DDPGAgent_RNN(object):
    method __init__ (line 110) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, hidden_dim=64,
    method reset_noise (line 150) | def reset_noise(self):
    method scale_noise (line 154) | def scale_noise(self, scale):
    method step (line 160) | def step(self, obs, explore=False):
    method get_params (line 183) | def get_params(self):
    method load_params (line 191) | def load_params(self, params):
    method init_hidden (line 199) | def init_hidden(self, len_ep, policy_hidden=False, policy_target_hidde...
  class DDPGAgent_SNN (line 211) | class DDPGAgent_SNN(object):
    method __init__ (line 216) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, output_styl...
    method reset_noise (line 246) | def reset_noise(self):
    method scale_noise (line 250) | def scale_noise(self, scale):
    method step (line 256) | def step(self, obs, explore=False):
    method get_params (line 297) | def get_params(self):
    method load_params (line 305) | def load_params(self, params):
  class DDPGAgent_ToM (line 313) | class DDPGAgent_ToM(object):
    method __init__ (line 318) | def __init__(self, num_in_pol, num_out_pol, num_in_critic, num_in_mle,...
    method reset_noise (line 354) | def reset_noise(self):
    method scale_noise (line 358) | def scale_noise(self, scale):
    method step (line 364) | def step(self, obs, explore=False):
    method get_params (line 399) | def get_params(self):
    method load_params (line 412) | def load_params(self, params):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/common/distributions.py
  class Pd (line 10) | class Pd(object):
    method flatparam (line 14) | def flatparam(self):
    method mode (line 16) | def mode(self):
    method logp (line 18) | def logp(self, x):
    method kl (line 20) | def kl(self, other):
    method entropy (line 22) | def entropy(self):
    method sample (line 24) | def sample(self):
  class PdType (line 27) | class PdType(object):
    method pdclass (line 31) | def pdclass(self):
    method pdfromflat (line 33) | def pdfromflat(self, flat):
    method param_shape (line 35) | def param_shape(self):
    method sample_shape (line 37) | def sample_shape(self):
    method sample_dtype (line 39) | def sample_dtype(self):
    method param_placeholder (line 42) | def param_placeholder(self, prepend_shape, name=None):
    method sample_placeholder (line 44) | def sample_placeholder(self, prepend_shape, name=None):
  class CategoricalPdType (line 47) | class CategoricalPdType(PdType):
    method __init__ (line 48) | def __init__(self, ncat):
    method pdclass (line 50) | def pdclass(self):
    method param_shape (line 52) | def param_shape(self):
    method sample_shape (line 54) | def sample_shape(self):
    method sample_dtype (line 56) | def sample_dtype(self):
  class SoftCategoricalPdType (line 59) | class SoftCategoricalPdType(PdType):
    method __init__ (line 60) | def __init__(self, ncat):
    method pdclass (line 62) | def pdclass(self):
    method param_shape (line 64) | def param_shape(self):
    method sample_shape (line 66) | def sample_shape(self):
    method sample_dtype (line 68) | def sample_dtype(self):
  class MultiCategoricalPdType (line 71) | class MultiCategoricalPdType(PdType):
    method __init__ (line 72) | def __init__(self, low, high):
    method pdclass (line 76) | def pdclass(self):
    method pdfromflat (line 78) | def pdfromflat(self, flat):
    method param_shape (line 80) | def param_shape(self):
    method sample_shape (line 82) | def sample_shape(self):
    method sample_dtype (line 84) | def sample_dtype(self):
  class SoftMultiCategoricalPdType (line 87) | class SoftMultiCategoricalPdType(PdType):
    method __init__ (line 88) | def __init__(self, low, high):
    method pdclass (line 92) | def pdclass(self):
    method pdfromflat (line 94) | def pdfromflat(self, flat):
    method param_shape (line 96) | def param_shape(self):
    method sample_shape (line 98) | def sample_shape(self):
    method sample_dtype (line 100) | def sample_dtype(self):
  class DiagGaussianPdType (line 103) | class DiagGaussianPdType(PdType):
    method __init__ (line 104) | def __init__(self, size):
    method pdclass (line 106) | def pdclass(self):
    method param_shape (line 108) | def param_shape(self):
    method sample_shape (line 110) | def sample_shape(self):
    method sample_dtype (line 112) | def sample_dtype(self):
  class BernoulliPdType (line 115) | class BernoulliPdType(PdType):
    method __init__ (line 116) | def __init__(self, size):
    method pdclass (line 118) | def pdclass(self):
    method param_shape (line 120) | def param_shape(self):
    method sample_shape (line 122) | def sample_shape(self):
    method sample_dtype (line 124) | def sample_dtype(self):
  class CategoricalPd (line 150) | class CategoricalPd(Pd):
    method __init__ (line 151) | def __init__(self, logits):
    method flatparam (line 153) | def flatparam(self):
    method mode (line 155) | def mode(self):
    method logp (line 157) | def logp(self, x):
    method kl (line 159) | def kl(self, other):
    method entropy (line 168) | def entropy(self):
    method sample (line 174) | def sample(self):
    method fromflat (line 178) | def fromflat(cls, flat):
  class SoftCategoricalPd (line 181) | class SoftCategoricalPd(Pd):
    method __init__ (line 182) | def __init__(self, logits):
    method flatparam (line 184) | def flatparam(self):
    method mode (line 186) | def mode(self):
    method logp (line 188) | def logp(self, x):
    method kl (line 190) | def kl(self, other):
    method entropy (line 199) | def entropy(self):
    method sample (line 205) | def sample(self):
    method fromflat (line 209) | def fromflat(cls, flat):
  class MultiCategoricalPd (line 212) | class MultiCategoricalPd(Pd):
    method __init__ (line 213) | def __init__(self, low, high, flat):
    method flatparam (line 217) | def flatparam(self):
    method mode (line 219) | def mode(self):
    method logp (line 221) | def logp(self, x):
    method kl (line 223) | def kl(self, other):
    method entropy (line 227) | def entropy(self):
    method sample (line 229) | def sample(self):
    method fromflat (line 232) | def fromflat(cls, flat):
  class SoftMultiCategoricalPd (line 235) | class SoftMultiCategoricalPd(Pd):  # doesn't work yet
    method __init__ (line 236) | def __init__(self, low, high, flat):
    method flatparam (line 240) | def flatparam(self):
    method mode (line 242) | def mode(self):
    method logp (line 247) | def logp(self, x):
    method kl (line 249) | def kl(self, other):
    method entropy (line 253) | def entropy(self):
    method sample (line 255) | def sample(self):
    method fromflat (line 261) | def fromflat(cls, flat):
  class DiagGaussianPd (line 264) | class DiagGaussianPd(Pd):
    method __init__ (line 265) | def __init__(self, flat):
    method flatparam (line 271) | def flatparam(self):
    method mode (line 273) | def mode(self):
    method logp (line 275) | def logp(self, x):
    method kl (line 279) | def kl(self, other):
    method entropy (line 282) | def entropy(self):
    method sample (line 284) | def sample(self):
    method fromflat (line 287) | def fromflat(cls, flat):
  class BernoulliPd (line 290) | class BernoulliPd(Pd):
    method __init__ (line 291) | def __init__(self, logits):
    method flatparam (line 294) | def flatparam(self):
    method mode (line 296) | def mode(self):
    method logp (line 298) | def logp(self, x):
    method kl (line 300) | def kl(self, other):
    method entropy (line 302) | def entropy(self):
    method sample (line 304) | def sample(self):
    method fromflat (line 309) | def fromflat(cls, flat):
  function make_pdtype (line 312) | def make_pdtype(ac_space):
  function shape_el (line 328) | def shape_el(v, i):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/common/tile_images.py
  function tile_images (line 3) | def tile_images(img_nhwc):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/common/vec_env/vec_env.py
  class AlreadySteppingError (line 7) | class AlreadySteppingError(Exception):
    method __init__ (line 13) | def __init__(self):
  class NotSteppingError (line 18) | class NotSteppingError(Exception):
    method __init__ (line 24) | def __init__(self):
  class VecEnv (line 29) | class VecEnv(ABC):
    method __init__ (line 43) | def __init__(self, num_envs, observation_space, action_space):
    method reset (line 49) | def reset(self):
    method step_async (line 61) | def step_async(self, actions):
    method step_wait (line 73) | def step_wait(self):
    method close_extras (line 86) | def close_extras(self):
    method close (line 93) | def close(self):
    method step (line 101) | def step(self, actions):
    method render (line 110) | def render(self, mode='human'):
    method get_images (line 121) | def get_images(self):
    method unwrapped (line 128) | def unwrapped(self):
    method get_viewer (line 134) | def get_viewer(self):
  class VecEnvWrapper (line 140) | class VecEnvWrapper(VecEnv):
    method __init__ (line 146) | def __init__(self, venv, observation_space=None, action_space=None):
    method step_async (line 152) | def step_async(self, actions):
    method reset (line 156) | def reset(self):
    method step_wait (line 160) | def step_wait(self):
    method close (line 163) | def close(self):
    method render (line 166) | def render(self, mode='human'):
    method get_images (line 169) | def get_images(self):
    method __getattr__ (line 172) | def __getattr__(self, name):
  class VecEnvObservationWrapper (line 177) | class VecEnvObservationWrapper(VecEnvWrapper):
    method process (line 179) | def process(self, obs):
    method reset (line 182) | def reset(self):
    method step_wait (line 186) | def step_wait(self):
  class CloudpickleWrapper (line 190) | class CloudpickleWrapper(object):
    method __init__ (line 195) | def __init__(self, x):
    method __getstate__ (line 198) | def __getstate__(self):
    method __setstate__ (line 202) | def __setstate__(self, ob):
  function clear_mpi_env_vars (line 208) | def clear_mpi_env_vars():

FILE: examples/Social_Cognition/MAToM-SNN/MPE/main.py
  function get_common_args (line 16) | def get_common_args():
  function make_parallel_env (line 65) | def make_parallel_env(env_id, n_rollout_threads, seed, discrete_action):
  function run (line 78) | def run(config):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/__init__.py
  function load (line 5) | def load(name):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 24) | def reset_world(self, world):
    method reward (line 41) | def reward(self, agent, world):
    method observation (line 45) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple_crypto.py
  class CryptoAgent (line 14) | class CryptoAgent(Agent):
    method __init__ (line 15) | def __init__(self):
  class Scenario (line 19) | class Scenario(BaseScenario):
    method make_world (line 21) | def make_world(self):
    method reset_world (line 47) | def reset_world(self, world):
    method benchmark_data (line 78) | def benchmark_data(self, agent, world):
    method good_listeners (line 83) | def good_listeners(self, world):
    method good_agents (line 87) | def good_agents(self, world):
    method adversaries (line 91) | def adversaries(self, world):
    method reward (line 94) | def reward(self, agent, world):
    method agent_reward (line 97) | def agent_reward(self, agent, world):
    method adversary_reward (line 116) | def adversary_reward(self, agent, world):
    method observation (line 124) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple_push.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 33) | def reset_world(self, world):
    method reward (line 58) | def reward(self, agent, world):
    method agent_reward (line 62) | def agent_reward(self, agent, world):
    method adversary_reward (line 66) | def adversary_reward(self, agent, world):
    method observation (line 76) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple_reference.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 26) | def reset_world(self, world):
    method reward (line 55) | def reward(self, agent, world):
    method observation (line 61) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple_speaker_listener.py
  class Scenario (line 5) | class Scenario(BaseScenario):
    method make_world (line 6) | def make_world(self):
    method reset_world (line 33) | def reset_world(self, world):
    method benchmark_data (line 59) | def benchmark_data(self, agent, world):
    method reward (line 63) | def reward(self, agent, world):
    method observation (line 69) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple_spread.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self):
    method reset_world (line 31) | def reset_world(self, world):
    method benchmark_data (line 47) | def benchmark_data(self, agent, world):
    method is_collision (line 66) | def is_collision(self, agent1, agent2):
    method reward (line 72) | def reward(self, agent, world):
    method observation (line 84) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/multiagent/scenarios/simple_world_comm.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self):
    method set_boundaries (line 59) | def set_boundaries(self, world):
    method reset_world (line 88) | def reset_world(self, world):
    method benchmark_data (line 115) | def benchmark_data(self, agent, world):
    method is_collision (line 126) | def is_collision(self, agent1, agent2):
    method good_agents (line 134) | def good_agents(self, world):
    method adversaries (line 138) | def adversaries(self, world):
    method reward (line 142) | def reward(self, agent, world):
    method outside_boundary (line 148) | def outside_boundary(self, agent):
    method agent_reward (line 155) | def agent_reward(self, agent, world):
    method adversary_reward (line 185) | def adversary_reward(self, agent, world):
    method observation2 (line 201) | def observation2(self, agent, world):
    method observation (line 224) | def observation(self, agent, world):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/policy/maddpg.py
  class MADDPG (line 15) | class MADDPG(object):
    method __init__ (line 19) | def __init__(self, agent_init_params, alg_types, device,
    method policies (line 56) | def policies(self):
    method target_policies (line 60) | def target_policies(self):
    method scale_noise (line 63) | def scale_noise(self, scale):
    method reset_noise (line 72) | def reset_noise(self):
    method step (line 76) | def step(self, observations, explore=False):
    method update (line 88) | def update(self, sample, agent_i, parallel=False, logger=None):
    method update_all_targets (line 180) | def update_all_targets(self):
    method prep_training (line 190) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 217) | def prep_rollouts(self, device='cpu'):
    method save (line 230) | def save(self, filename):
    method init_from_env (line 240) | def init_from_env(cls, env, device, agent_alg="MADDPG", adversary_alg=...
    method init_from_save (line 292) | def init_from_save(cls, filename):
  class MADDPG_SNN (line 303) | class MADDPG_SNN(object):
    method __init__ (line 307) | def __init__(self, agent_init_params, alg_types,output_style, device,
    method policies (line 344) | def policies(self):
    method target_policies (line 348) | def target_policies(self):
    method scale_noise (line 351) | def scale_noise(self, scale):
    method reset_noise (line 360) | def reset_noise(self):
    method step (line 364) | def step(self, observations, explore=False):
    method update (line 376) | def update(self, sample, agent_i, parallel=False, logger=None):
    method update_all_targets (line 483) | def update_all_targets(self):
    method prep_training (line 493) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 520) | def prep_rollouts(self, device='cpu'):
    method save (line 533) | def save(self, filename):
    method init_from_env (line 543) | def init_from_env(cls, env, device, agent_alg="MADDPG_SNN", adversary_...
    method init_from_save (line 598) | def init_from_save(cls, filename):
  class MADDPG_ToM (line 609) | class MADDPG_ToM(object):
    method __init__ (line 614) | def __init__(self, agent_init_params, alg_types, output_style, device,
    method policies (line 699) | def policies(self):
    method target_policies (line 703) | def target_policies(self):
    method scale_noise (line 706) | def scale_noise(self, scale):
    method reset_noise (line 715) | def reset_noise(self):
    method step (line 719) | def step(self, observations, explore=False):    #simple_tag
    method _get_obs (line 805) | def _get_obs(self, observations):
    method trian_tag (line 853) | def trian_tag(self, agent_i, KL_criterion, obs, parallel, acs):
    method trian_adv (line 885) | def trian_adv(self, agent_i, KL_criterion, obs, parallel, acs):
    method trian_push (line 917) | def trian_push(self, agent_i, KL_criterion, obs, parallel, acs):
    method trian_com (line 939) | def trian_com(self, agent_i, KL_criterion, obs, parallel, acs):
    method update (line 964) | def update(self, sample, agent_i, parallel=False, logger=None, sample_...
    method update_all_targets (line 1067) | def update_all_targets(self):
    method prep_training (line 1077) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 1115) | def prep_rollouts(self, device='cpu'):
    method save (line 1128) | def save(self, filename):
    method init_from_env (line 1139) | def init_from_env(cls, env, device, agent_alg="MADDPG_ToM", adversary_...
    method init_from_save (line 1195) | def init_from_save(cls, filename):
    method get_params (line 1208) | def get_params(self):
    method load_params (line 1216) | def load_params(self, params):
  class ToM_SA (line 1221) | class ToM_SA(object):
    method __init__ (line 1226) | def __init__(self, agent_init_params, alg_types, output_style, device,
    method policies (line 1311) | def policies(self):
    method target_policies (line 1315) | def target_policies(self):
    method scale_noise (line 1318) | def scale_noise(self, scale):
    method reset_noise (line 1327) | def reset_noise(self):
    method step (line 1331) | def step(self, observations, actions_pre, explore=False):    #simple_tag
    method _get_obs (line 1442) | def _get_obs(self, observations, actions_pre):
    method trian_tag (line 1523) | def trian_tag(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_adv (line 1555) | def trian_adv(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_push (line 1587) | def trian_push(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_com (line 1609) | def trian_com(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method update (line 1631) | def update(self, sample, agent_i, parallel=False, logger=None, sample_...
    method update_all_targets (line 1730) | def update_all_targets(self):
    method prep_training (line 1740) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 1778) | def prep_rollouts(self, device='cpu'):
    method save (line 1791) | def save(self, filename):
    method init_from_env (line 1802) | def init_from_env(cls, env, device, agent_alg="ToM_SA", adversary_alg=...
    method init_from_save (line 1858) | def init_from_save(cls, filename):
    method get_params (line 1871) | def get_params(self):
    method load_params (line 1879) | def load_params(self, params):
  class ToM_S (line 1884) | class ToM_S(object):
    method __init__ (line 1889) | def __init__(self, agent_init_params, alg_types, output_style, device,
    method policies (line 1974) | def policies(self):
    method target_policies (line 1978) | def target_policies(self):
    method scale_noise (line 1981) | def scale_noise(self, scale):
    method reset_noise (line 1990) | def reset_noise(self):
    method step (line 1994) | def step(self, observations, actions_pre, explore=False):    #simple_tag
    method _get_obs (line 2100) | def _get_obs(self, observations, actions_pre):
    method trian_tag (line 2180) | def trian_tag(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_adv (line 2212) | def trian_adv(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_push (line 2244) | def trian_push(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_com (line 2266) | def trian_com(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method update (line 2289) | def update(self, sample, agent_i, parallel=False, logger=None, sample_...
    method update_all_targets (line 2388) | def update_all_targets(self):
    method prep_training (line 2398) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 2436) | def prep_rollouts(self, device='cpu'):
    method save (line 2449) | def save(self, filename):
    method init_from_env (line 2460) | def init_from_env(cls, env, device, agent_alg="ToM_S", adversary_alg="...
    method init_from_save (line 2516) | def init_from_save(cls, filename):
    method get_params (line 2529) | def get_params(self):
    method load_params (line 2537) | def load_params(self, params):
  class ToM_self (line 2542) | class ToM_self(object):
    method __init__ (line 2547) | def __init__(self, agent_init_params, alg_types, output_style, device,
    method policies (line 2632) | def policies(self):
    method target_policies (line 2636) | def target_policies(self):
    method scale_noise (line 2639) | def scale_noise(self, scale):
    method reset_noise (line 2648) | def reset_noise(self):
    method step (line 2652) | def step(self, observations, actions_pre, explore=False):    #simple_tag
    method _get_obs (line 2756) | def _get_obs(self, observations, actions_pre):
    method trian_tag (line 2840) | def trian_tag(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_adv (line 2862) | def trian_adv(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_push (line 2884) | def trian_push(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method trian_com (line 2896) | def trian_com(self, agent_i, KL_criterion, obs, acs_pre, parallel, acs):
    method update (line 2918) | def update(self, sample, agent_i, parallel=False, logger=None, sample_...
    method update_all_targets (line 3017) | def update_all_targets(self):
    method prep_training (line 3027) | def prep_training(self, device='gpu'):
    method prep_rollouts (line 3065) | def prep_rollouts(self, device='cpu'):
    method save (line 3078) | def save(self, filename):
    method init_from_env (line 3089) | def init_from_env(cls, env, device, agent_alg="ToM_self", adversary_al...
    method init_from_save (line 3145) | def init_from_save(cls, filename):
    method get_params (line 3158) | def get_params(self):
    method load_params (line 3166) | def load_params(self, params):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/buffer.py
  class ReplayBuffer (line 6) | class ReplayBuffer(object):
    method __init__ (line 10) | def __init__(self, max_steps, num_agents, obs_dims, ac_dims, device):
    method __len__ (line 37) | def __len__(self):
    method push (line 40) | def push(self, observations, actions, rewards, next_observations, dones):
    method sample (line 72) | def sample(self, N, to_gpu=False, norm_rews=True):
    method get_average_rewards (line 92) | def get_average_rewards(self, N):
  class ReplayBuffer_pre (line 99) | class ReplayBuffer_pre(object):
    method __init__ (line 103) | def __init__(self, max_steps, num_agents, obs_dims, ac_dims, device):
    method __len__ (line 132) | def __len__(self):
    method push (line 135) | def push(self, actions_pre, observations, actions, rewards, next_obser...
    method sample (line 170) | def sample(self, N, to_gpu=False, norm_rews=True):
    method get_average_rewards (line 191) | def get_average_rewards(self, N):
  class ReplayBuffer_RNN (line 199) | class ReplayBuffer_RNN(object):
    method __init__ (line 203) | def __init__(self, max_steps, num_agents, obs_dims, ac_dims, ep_dims):
    method __len__ (line 230) | def __len__(self):
    method push (line 233) | def push(self, observations_ep, actions_ep, rewards_ep, next_observati...
    method sample (line 274) | def sample(self, N, to_gpu=False, norm_rews=True):
    method get_average_rewards (line 294) | def get_average_rewards(self, N):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/env_wrappers.py
  function worker (line 9) | def worker(remote, parent_remote, env_fn_wrapper):
  class SubprocVecEnv (line 40) | class SubprocVecEnv(VecEnv):
    method __init__ (line 41) | def __init__(self, env_fns, spaces=None):
    method step_async (line 63) | def step_async(self, actions):
    method step_wait (line 68) | def step_wait(self):
    method reset (line 74) | def reset(self):
    method reset_task (line 79) | def reset_task(self):
    method close (line 84) | def close(self):
  class DummyVecEnv (line 97) | class DummyVecEnv(VecEnv):
    method __init__ (line 98) | def __init__(self, env_fns):
    method step_async (line 110) | def step_async(self, actions):
    method step_wait (line 113) | def step_wait(self):
    method reset (line 124) | def reset(self):
    method close (line 128) | def close(self):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/make_env.py
  function make_env (line 15) | def make_env(scenario_name, benchmark=False, discrete_action=False):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/misc.py
  function soft_update (line 9) | def soft_update(target, source, tau):
  function hard_update (line 22) | def hard_update(target, source):
  function average_gradients (line 33) | def average_gradients(model):
  function init_processes (line 41) | def init_processes(rank, size, fn, backend='gloo'):
  function onehot_from_logits (line 48) | def onehot_from_logits(logits, eps=0.0):
  function sample_gumbel (line 65) | def sample_gumbel(shape, eps=1e-20, tens_type=torch.FloatTensor):
  function gumbel_softmax_sample (line 71) | def gumbel_softmax_sample(logits, temperature):
  function gumbel_softmax (line 77) | def gumbel_softmax(logits, temperature=1.0, hard=False):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/multiprocessing.py
  function _flatten_list (line 10) | def _flatten_list(l):
  function worker (line 18) | def worker(remote, parent_remote, env_fn_wrapper):
  class VecEnv (line 56) | class VecEnv(object):
    method __init__ (line 66) | def __init__(self, num_envs, observation_space, action_space):
    method observe (line 71) | def observe(self, agent):
    method reset (line 74) | def reset(self):
    method step_async (line 84) | def step_async(self, actions):
    method step_wait (line 94) | def step_wait(self):
    method close (line 106) | def close(self):
    method step (line 112) | def step(self, actions):
    method render (line 116) | def render(self, mode='human'):
    method get_images (line 128) | def get_images(self):
    method get_viewer (line 134) | def get_viewer(self):
    method tile_images (line 140) | def tile_images(self, img_nhwc):
  class CloudpickleWrapper (line 160) | class CloudpickleWrapper(object):
    method __init__ (line 165) | def __init__(self, x):
    method __getstate__ (line 168) | def __getstate__(self):
    method __setstate__ (line 172) | def __setstate__(self, ob):
  class SubprocVecEnv (line 177) | class SubprocVecEnv(VecEnv):
    method __init__ (line 178) | def __init__(self, env_fns, spaces=None):
    method step_async (line 201) | def step_async(self, actions):
    method step_wait (line 206) | def step_wait(self):
    method step_wait_2 (line 212) | def step_wait_2(self):
    method step_wait_3 (line 218) | def step_wait_3(self):
    method reset (line 224) | def reset(self):
    method agents (line 229) | def agents(self):
    method reset_task (line 234) | def reset_task(self):
    method spec (line 239) | def spec(self):
    method get_images (line 244) | def get_images(self):
    method observe (line 252) | def observe(self, agent):
    method close (line 260) | def close(self):
    method __len__ (line 272) | def __len__(self):
  function _flatten_list (line 275) | def _flatten_list(l):
  class DummyVecEnv (line 282) | class DummyVecEnv(VecEnv):
    method __init__ (line 283) | def __init__(self, env_fns):
    method step_async (line 295) | def step_async(self, actions):
    method step_wait (line 298) | def step_wait(self):
    method reset (line 309) | def reset(self):
    method close (line 313) | def close(self):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/networks.py
  class MLPNetwork (line 7) | class MLPNetwork(nn.Module):
    method __init__ (line 11) | def __init__(self, input_dim, out_dim, hidden_dim=64, nonlin=F.relu,
    method forward (line 40) | def forward(self, X):
  class BCNoSpikingLIFNode (line 53) | class BCNoSpikingLIFNode(LIFNode):
    method __init__ (line 54) | def __init__(self, *args, **kwargs):
    method forward (line 57) | def forward(self, dv: torch.Tensor):
  class SNNNetwork (line 61) | class SNNNetwork(nn.Module):
    method __init__ (line 65) | def __init__(self, input_dim, out_dim, hidden_dim=64, node=LIFNode, ti...
    method reset (line 99) | def reset(self):
    method forward (line 104) | def forward(self, X):

FILE: examples/Social_Cognition/MAToM-SNN/MPE/utils/noise.py
  class OUNoise (line 5) | class OUNoise:
    method __init__ (line 6) | def __init__(self, action_dimension, scale=0.1, mu=0, theta=0.15, sigm...
    method reset (line 15) | def reset(self):
    method noise (line 18) | def noise(self):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/agents/sagent.py
  class Agents (line 10) | class Agents:
    method __init__ (line 11) | def __init__(self, args):
    method choose_action (line 58) | def choose_action(self, num_env, obs, last_action, agent_num, avail_ac...
    method _choose_action_from_softmax (line 121) | def _choose_action_from_softmax(self, inputs, avail_actions, epsilon, ...
    method _get_max_episode_len (line 143) | def _get_max_episode_len(self, batch):
    method train (line 157) | def train(self, batch, train_step, epsilon=None):  # coma needs epsilo...

FILE: examples/Social_Cognition/MAToM-SNN/STAG/common_sr/arguments.py
  function get_common_args (line 3) | def get_common_args():
  function get_coma_args (line 52) | def get_coma_args(args):
  function get_mixer_args (line 80) | def get_mixer_args(args):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/common_sr/dummy_vec_env.py
  class DummyVecEnv (line 5) | class DummyVecEnv(VecEnv):
    method __init__ (line 12) | def __init__(self, env_fns):
    method step_async (line 31) | def step_async(self, actions):
    method step_wait (line 45) | def step_wait(self):
    method reset (line 58) | def reset(self):
    method _save_obs (line 64) | def _save_obs(self, e, obs):
    method _obs_from_buf (line 71) | def _obs_from_buf(self):
    method get_images (line 74) | def get_images(self):
    method render (line 77) | def render(self, mode='human'):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/common_sr/multiprocessing_env.py
  function _flatten_list (line 7) | def _flatten_list(l):
  function worker (line 14) | def worker(remote, parent_remote, env_fn_wrapper):
  class VecEnv (line 43) | class VecEnv(object):
    method __init__ (line 47) | def __init__(self, num_envs, observation_space, action_space):
    method reset (line 52) | def reset(self):
    method step_async (line 62) | def step_async(self, actions):
    method step_wait (line 72) | def step_wait(self):
    method close (line 84) | def close(self):
    method step (line 90) | def step(self, actions):
    method render (line 94) | def render(self, mode='human'):
    method get_images (line 105) | def get_images(self):
  class CloudpickleWrapper (line 112) | class CloudpickleWrapper(object):
    method __init__ (line 116) | def __init__(self, x):
    method __getstate__ (line 118) | def __getstate__(self):
    method __setstate__ (line 121) | def __setstate__(self, ob):
  class SubprocVecEnv (line 126) | class SubprocVecEnv(VecEnv):
    method __init__ (line 127) | def __init__(self, env_fns, spaces=None):
    method step_async (line 148) | def step_async(self, actions):
    method step_wait (line 153) | def step_wait(self):
    method reset (line 159) | def reset(self):
    method reset_task (line 164) | def reset_task(self):
    method get_images (line 169) | def get_images(self):
    method close (line 177) | def close(self):
    method __len__ (line 189) | def __len__(self):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/common_sr/replay_buffer.py
  class ReplayBuffer (line 5) | class ReplayBuffer:
    method __init__ (line 6) | def __init__(self, args):
    method store_episode (line 34) | def store_episode(self, episode_batch):
    method sample (line 53) | def sample(self, batch_size):
    method _get_storage_idx (line 60) | def _get_storage_idx(self, inc=None):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/common_sr/srollout.py
  class RolloutWorker (line 4) | class RolloutWorker:
    method __init__ (line 5) | def __init__(self, env, agents, args):
    method generate_episode (line 19) | def generate_episode(self, episode_num=None, evaluate=False):
    method generate_episode_sample (line 154) | def generate_episode_sample(self, episodes, steps, episode_num=None, e...

FILE: examples/Social_Cognition/MAToM-SNN/STAG/envs/Stag_Hunt_env.py
  function env_creator (line 8) | def env_creator(args):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/envs/abstract.py
  class MetaEpisodicEnv (line 12) | class MetaEpisodicEnv(abc.ABC, Generic[ObsType]):
    method max_episode_len (line 15) | def max_episode_len(self) -> int:
    method new_env (line 22) | def new_env(self) -> None:
    method reset (line 34) | def reset(self) -> ObsType:
    method step (line 46) | def step(

FILE: examples/Social_Cognition/MAToM-SNN/STAG/main_spiking.py
  function make_env (line 56) | def make_env():

FILE: examples/Social_Cognition/MAToM-SNN/STAG/network/spiking_net.py
  class BCNoSpikingLIFNode (line 18) | class BCNoSpikingLIFNode(LIFNode):
    method __init__ (line 19) | def __init__(self, *args, **kwargs):
    method forward (line 22) | def forward(self, dv: torch.Tensor):
  class BCNoSpikingIFNode (line 27) | class BCNoSpikingIFNode(IFNode):
    method __init__ (line 28) | def __init__(self, *args, **kwargs):
    method forward (line 31) | def forward(self, dv: torch.Tensor):
  class ActFun (line 37) | class ActFun(torch.autograd.Function):
    method forward (line 40) | def forward(ctx, input):
    method backward (line 45) | def backward(ctx, grad_output):
  function mem_update (line 55) | def mem_update(fc, x, mem, spike):
  class Critic (line 62) | class Critic(nn.Module):
    method __init__ (line 63) | def __init__(self, input_shape, args):
    method forward (line 72) | def forward(self, inputs, h1_mem, h1_spike, h2_mem, h2_spike):
  class VDNNet (line 101) | class VDNNet(nn.Module):
    method __init__ (line 102) | def __init__(self):
    method forward (line 105) | def forward(self, q_values):
  class Linear_weight (line 108) | class Linear_weight(nn.Module):
    method __init__ (line 109) | def __init__(self, input_shape, out_shape, args):
    method forward (line 115) | def forward(self, x):
  class BiasNet (line 124) | class BiasNet(nn.Module):
    method __init__ (line 125) | def __init__(self, args):
    method reset (line 140) | def reset(self, episode_num):
    method forward (line 147) | def forward(self, state, hidden):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/policy/dqn.py
  class DQN (line 5) | class DQN:
    method __init__ (line 6) | def __init__(self, args, model_eval, model_target, agent_id):
    method learn (line 53) | def learn(self, batch, max_episode_len, train_step, epsilon=None):  # ...
    method _get_inputs (line 116) | def _get_inputs(self, batch, transition_idx):
    method get_q_values (line 150) | def get_q_values(self, batch, max_episode_len, eval_hidden, target_hid...
    method init_hidden (line 175) | def init_hidden(self, episode_num, num_env):
    method init_hidden_learn (line 180) | def init_hidden_learn(self, episode_num):
    method save_model (line 185) | def save_model(self, train_step):
    method load_model (line 191) | def load_model(self, train_step):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/policy/stomvdn.py
  class SToMVDN (line 7) | class SToMVDN:
    method __init__ (line 8) | def __init__(self, args):
    method learn (line 73) | def learn(self, batch, max_episode_len, train_step, epsilon=None):  # ...
    method _get_inputs (line 163) | def _get_inputs(self, batch, transition_idx):
    method get_q_values (line 191) | def get_q_values(self, batch, max_episode_len):
    method get_bias (line 231) | def get_bias(self, batch, hidden_evals, hidden_targets, episode_num, h...
    method _get_actor_inputs (line 252) | def _get_actor_inputs(self, batch, transition_idx):
    method _get_action_prob (line 275) | def _get_action_prob(self, batch, max_episode_len, epsilon):
    method init_hidden (line 320) | def init_hidden(self, episode_num, num_env):
    method init_hidden_learn (line 331) | def init_hidden_learn(self, episode_num):
    method save_model (line 342) | def save_model(self, train_step):
    method load_model (line 349) | def load_model(self, train_step):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/policy/svdn.py
  class SVDN (line 6) | class SVDN:
    method __init__ (line 7) | def __init__(self, args):
    method learn (line 58) | def learn(self, batch, max_episode_len, train_step, epsilon=None):  # ...
    method _get_inputs (line 114) | def _get_inputs(self, batch, transition_idx):
    method get_q_values (line 142) | def get_q_values(self, batch, max_episode_len):
    method init_hidden (line 171) | def init_hidden(self, episode_num, num_env):
    method init_hidden_learn (line 182) | def init_hidden_learn(self, episode_num):
    method save_model (line 193) | def save_model(self, train_step):
    method load_model (line 199) | def load_model(self, train_step):

FILE: examples/Social_Cognition/MAToM-SNN/STAG/preprocessoing/common.py
  class Preprocessing (line 11) | class Preprocessing(abc.ABC, tc.nn.Module):
    method forward (line 12) | def forward(
  function one_hot_torch (line 34) | def one_hot_torch(ys: tc.LongTensor, depth: int, device) -> tc.FloatTensor:
  function one_hot (line 53) | def one_hot(ys: int, depth: int) -> list:

FILE: examples/Social_Cognition/MAToM-SNN/STAG/runner.py
  class Runner (line 13) | class Runner:
    method __init__ (line 14) | def __init__(self, env, args):
    method run (line 32) | def run(self, num):
    method evaluate (line 73) | def evaluate(self):
    method plt (line 82) | def plt(self, num):

FILE: examples/Social_Cognition/SmashVat/dqn.py
  class ReplayBuffer (line 22) | class ReplayBuffer:
    method __init__ (line 23) | def __init__(self, capacity):
    method push (line 27) | def push(self, *args):
    method sample (line 32) | def sample(self, batch_size):
  class AnseEmpDQN (line 37) | class AnseEmpDQN:
    method __init__ (line 38) | def __init__(self, env, net_type='SNN',
    method state2tensor (line 69) | def state2tensor(self, state):
    method epsilon_greedy (line 81) | def epsilon_greedy(self, net, state, epsilon):
    method train (line 90) | def train(self, lr=1e-3, num_episodes=10000, gamma=0.99,
    method save (line 244) | def save(self, path):
    method load (line 249) | def load(self, path):
    method run (line 252) | def run(self, gif_name=None):
  function set_seed (line 277) | def set_seed(seed=114514):
  function main (line 284) | def main():

FILE: examples/Social_Cognition/SmashVat/environment.py
  class HumanVatGoalEnv (line 10) | class HumanVatGoalEnv(gym.Env):
    class Actions (line 13) | class Actions(IntEnum):
    class Cells (line 22) | class Cells(IntEnum):
    class CellsRender (line 29) | class CellsRender(object):
    class Params (line 37) | class Params(object):
      method __init__ (line 40) | def __init__(
    method __init__ (line 61) | def __init__(self, env_params=Params()):
    method reset (line 94) | def reset(self):
    method _gen_map (line 112) | def _gen_map(self):
    method _gen_obs (line 135) | def _gen_obs(self):
    method _encode (line 147) | def _encode(self, obs):
    method _decode (line 155) | def _decode(self, i):
    method render (line 163) | def render(self, mode="window", cell_size=64, style="realistic"):
    method _gen_img (line 177) | def _gen_img(self, cell_size, style):
    method close (line 312) | def close(self):
    method step (line 318) | def step(self, action):
  class BasicGoalEnv (line 392) | class BasicGoalEnv(HumanVatGoalEnv):
    method __init__ (line 393) | def __init__(self):
  class BasicVatGoalEnv (line 408) | class BasicVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 409) | def __init__(self):
  class BasicHumanVatGoalEnv (line 424) | class BasicHumanVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 425) | def __init__(self):
  class CShapeVatGoalEnv (line 440) | class CShapeVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 441) | def __init__(self):
  class CShapeHumanVatGoalEnv (line 456) | class CShapeHumanVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 457) | def __init__(self):
  class SShapeVatGoalEnv (line 472) | class SShapeVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 473) | def __init__(self):
  class SideHumanVatGoalEnv (line 488) | class SideHumanVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 489) | def __init__(self):
  class SmashAndDetourEnv (line 504) | class SmashAndDetourEnv(HumanVatGoalEnv):
    method __init__ (line 505) | def __init__(self):
  class CmpxHumanVatGoalEnv (line 520) | class CmpxHumanVatGoalEnv(HumanVatGoalEnv):
    method __init__ (line 521) | def __init__(self):

FILE: examples/Social_Cognition/SmashVat/main.py
  function set_seed (line 40) | def set_seed(seed=114514):
  function save_args (line 47) | def save_args(args, log_dir):
  function make_dirs (line 54) | def make_dirs(args, timestamp):
  function main (line 76) | def main():

FILE: examples/Social_Cognition/SmashVat/manual_control.py
  class ManualControl (line 6) | class ManualControl(object):
    method __init__ (line 9) | def __init__(self, env=HumanVatGoalEnv()):
    method display (line 14) | def display(self):
    method _redraw (line 21) | def _redraw(self):
    method _reset (line 26) | def _reset(self):
    method _step (line 39) | def _step(self, action):
    method _key_handler (line 59) | def _key_handler(self, event):

FILE: examples/Social_Cognition/SmashVat/qnets.py
  class CNNQnet (line 7) | class CNNQnet(nn.Module):
    method __init__ (line 8) | def __init__(self, input_dim, output_dim):
    method forward (line 26) | def forward(self, x):
  class SNNQnet (line 32) | class SNNQnet(nn.Module):
    method __init__ (line 33) | def __init__(self, input_dim, output_dim,
    method forward (line 54) | def forward(self, input):
    method reset (line 65) | def reset(self):

FILE: examples/Social_Cognition/SmashVat/side_effect_eval.py
  class StepwiseInactionModel (line 10) | class StepwiseInactionModel(object):
    method __init__ (line 13) | def __init__(self, noop_action=None):
    method reset (line 19) | def reset(self, baseline_state):
    method _sample (line 23) | def _sample(self, state):
    method calculate (line 31) | def calculate(self, prev_state, prev_action, current_state):
  class AttainableUtilityMeasure (line 44) | class AttainableUtilityMeasure(object):
    method __init__ (line 45) | def __init__(self, uf_num=10, uf_discount=0.99):
    method update (line 63) | def update(self, prev_state, prev_action, current_state):
    method calculate (line 84) | def calculate(self, current_state, baseline_state, dev_fun=lambda diff...
    method _get_aup_value (line 98) | def _get_aup_value(self, state):
    method _get_avgd_confid (line 116) | def _get_avgd_confid(self, state):
    method _get_u_values (line 121) | def _get_u_values(self, state):

FILE: examples/Social_Cognition/SmashVat/window.py
  class Window (line 9) | class Window(object):
    method __init__ (line 12) | def __init__(self, title):
    method set_window_title (line 27) | def set_window_title(self, title):
    method reg_key_press_handler (line 33) | def reg_key_press_handler(self, key_press_handler):
    method _default_key_press_handler (line 38) | def _default_key_press_handler(self, event):
    method show (line 44) | def show(self, block=True):
    method show_img (line 72) | def show_img(self, img):
    method close (line 87) | def close(self):
    method is_open (line 91) | def is_open(self):
  function on_press (line 100) | def on_press(event):

FILE: examples/Social_Cognition/ToCM/agent/controllers/ToCMController.py
  class ToCMController (line 12) | class ToCMController:
    method __init__ (line 14) | def __init__(self, config):
    method receive_params (line 28) | def receive_params(self, params):
    method init_buffer (line 32) | def init_buffer(self):
    method init_rnns (line 35) | def init_rnns(self):
    method dispatch_buffer (line 39) | def dispatch_buffer(self):
    method update_buffer (line 48) | def update_buffer(self, items):
    method step (line 54) | def step(self, observations, avail_actions, nn_mask):
    method advance_rnns (line 86) | def advance_rnns(self, state):
    method exploration (line 89) | def exploration(self, action):

FILE: examples/Social_Cognition/ToCM/agent/learners/ToCMLearner.py
  function orthogonal_init (line 17) | def orthogonal_init(tensor, gain=1):
  function initialize_weights (line 39) | def initialize_weights(mod, scale=1.0, mode='ortho'):
  class ToCMLearner (line 49) | class ToCMLearner:  # 通过ToCMLearnerConfig来构建
    method __init__ (line 51) | def __init__(self, config):
    method init_optimizers (line 112) | def init_optimizers(self):
    method params (line 118) | def params(self):
    method step (line 123) | def step(self, rollout):
    method train_model (line 157) | def train_model(self, samples):  # world model
    method train_agent (line 167) | def train_agent(self, samples):
    method apply_optimizer (line 203) | def apply_optimizer(self, opt, model, loss, grad_clip, name=None):  # ...
    method apply_optimizer_scheduler (line 211) | def apply_optimizer_scheduler(self, opt, sch, model, loss, grad_clip, ...

FILE: examples/Social_Cognition/ToCM/agent/memory/ToCMMemory.py
  class ToCMMemory (line 8) | class ToCMMemory:
    method __init__ (line 9) | def __init__(self, capacity, sequence_length, action_size, obs_size, n...
    method init_buffer (line 18) | def init_buffer(self, n_agents, env_type):  # 初始对环境进行采样，观察和动作都是np.arra...
    method append (line 31) | def append(self, obs, action, reward, done, fake, last, av_action):
    method tenzorify (line 46) | def tenzorify(self, nparray):
    method sample (line 49) | def sample(self, batch_size):
    method process_batch (line 52) | def process_batch(self, val, idxs, batch_size):  # 这里全部传到了cuda上
    method get_transitions (line 55) | def get_transitions(self, idxs):
    method sample_position (line 69) | def sample_position(self):
    method sample_positions (line 77) | def sample_positions(self, batch_size):
    method __len__ (line 80) | def __len__(self):
    method clean (line 83) | def clean(self):

FILE: examples/Social_Cognition/ToCM/agent/models/ToCMModel.py
  class ToCMModel (line 12) | class ToCMModel(nn.Module):
    method __init__ (line 13) | def __init__(self, config):
    method forward (line 40) | def forward(self, observations, prev_actions=None, prev_states=None, m...
    method get_state_representation (line 51) | def get_state_representation(self, observations, prev_actions, prev_st...

FILE: examples/Social_Cognition/ToCM/agent/optim/loss.py
  function model_loss (line 12) | def model_loss(config, model, obs, action, av_action, reward, done, fake...
  function actor_rollout (line 47) | def actor_rollout(obs, action, last, model, actor, critic, config):  # m...
  function critic_rollout (line 77) | def critic_rollout(model, critic, states, rew_states, actions, raw_state...
  function calculate_reward (line 94) | def calculate_reward(model, states, mask=None):
  function calculate_next_reward (line 101) | def calculate_next_reward(model, actions, states):
  function actor_loss (line 108) | def actor_loss(model, imag_state, obs_pred, actions, av_actions, old_pol...
  function value_loss (line 124) | def value_loss(critic, actions, imag_feat, targets):

FILE: examples/Social_Cognition/ToCM/agent/optim/utils.py
  function rec_loss (line 7) | def rec_loss(decoder, z, x, fake):
  function ppo_loss (line 14) | def ppo_loss(A, rho, eps=0.2):
  function mse (line 18) | def mse(model, x, target):
  function entropy_loss (line 23) | def entropy_loss(prob, logProb):
  function advantage (line 27) | def advantage(A):
  function calculate_ppo_loss (line 35) | def calculate_ppo_loss(logits, rho, A):  # pi rho adv
  function batch_multi_agent (line 43) | def batch_multi_agent(tensor, n_agents):
  function compute_return (line 51) | def compute_return(reward, value, discount, bootstrap, lmbda, gamma):
  function info_loss (line 64) | def info_loss(feat, model, actions, fake):
  function action_information_loss (line 70) | def action_information_loss(logits, target):
  function log_prob_loss (line 75) | def log_prob_loss(model, x, target):
  function kl_div_categorical (line 80) | def kl_div_categorical(p, q):
  function reshape_dist (line 85) | def reshape_dist(dist, config):
  function state_divergence_loss (line 89) | def state_divergence_loss(prior, posterior, config, reduce=True, balance...

FILE: examples/Social_Cognition/ToCM/agent/runners/ToCMRunner.py
  class ToCMServer (line 9) | class ToCMServer:
    method __init__ (line 10) | def __init__(self, n_workers, env_config, controller_config, model):
    method append (line 17) | def append(self, idx, update):
    method run (line 20) | def run(self):
  class ToCMRunner (line 28) | class ToCMRunner:
    method __init__ (line 30) | def __init__(self, env_config, learner_config, controller_config, n_wo...
    method run (line 42) | def run(self, max_steps=10 ** 10, max_episodes=10 ** 10):  # 10**10 50000

FILE: examples/Social_Cognition/ToCM/agent/utils/params.py
  function get_parameters (line 5) | def get_parameters(modules: Iterable[Module]):
  class FreezeParameters (line 17) | class FreezeParameters:
    method __init__ (line 18) | def __init__(self, modules: Iterable[Module]):
    method __enter__ (line 32) | def __enter__(self):
    method __exit__ (line 36) | def __exit__(self, exc_type, exc_val, exc_tb):

FILE: examples/Social_Cognition/ToCM/agent/workers/ToCMWorker.py
  class ToCMWorker (line 11) | class ToCMWorker:
    method __init__ (line 13) | def __init__(self, idx, env_config, controller_config):
    method _check_handle (line 22) | def _check_handle(self, handle):
    method _select_actions (line 29) | def _select_actions(self, state):
    method _wrap (line 62) | def _wrap(self, d):
    method get_absorbing_state (line 67) | def get_absorbing_state(self):
    method augment (line 71) | def augment(self, data, inverse=False):
    method _check_termination (line 81) | def _check_termination(self, info, steps_done):
    method run (line 87) | def run(self, ToCM_params):

FILE: examples/Social_Cognition/ToCM/configs/Config.py
  class Config (line 5) | class Config:
    method __init__ (line 6) | def __init__(self):
    method to_dict (line 9) | def to_dict(self, prefix=""):

FILE: examples/Social_Cognition/ToCM/configs/EnvConfigs.py
  class EnvConfig (line 6) | class EnvConfig(Config):
    method __init__ (line 7) | def __init__(self):
    method create_env (line 10) | def create_env(self):
  class MPEConfig (line 15) | class MPEConfig(EnvConfig):
    method __init__ (line 16) | def __init__(self, args):
    method create_env (line 19) | def create_env(self):
  class StarCraftConfig (line 23) | class StarCraftConfig(EnvConfig):
    method __init__ (line 24) | def __init__(self, env_name, random_seed):
    method create_env (line 28) | def create_env(self):
  class EnvCurriculumConfig (line 32) | class EnvCurriculumConfig(EnvConfig):
    method __init__ (line 33) | def __init__(self, env_configs, env_episodes, env_type, device, obs_bu...
    method update_random_seed (line 45) | def update_random_seed(self):
    method set_obs_builder_config (line 49) | def set_obs_builder_config(self, obs_builder_config):
    method set_reward_config (line 53) | def set_reward_config(self, reward_config):
    method create_env (line 57) | def create_env(self):
  class EnvCurriculumSampleConfig (line 61) | class EnvCurriculumSampleConfig(EnvConfig):
    method __init__ (line 62) | def __init__(self, env_configs, env_probs, obs_builder_config=None, re...
    method update_random_seed (line 72) | def update_random_seed(self):
    method set_obs_builder_config (line 76) | def set_obs_builder_config(self, obs_builder_config):
    method set_reward_config (line 80) | def set_reward_config(self, reward_config):
    method create_env (line 84) | def create_env(self):
  class EnvCurriculumPrioritizedSampleConfig (line 88) | class EnvCurriculumPrioritizedSampleConfig(EnvConfig):
    method __init__ (line 89) | def __init__(self, env_configs, repeat_random_seed, obs_builder_config...
    method update_random_seed (line 99) | def update_random_seed(self):
    method set_obs_builder_config (line 103) | def set_obs_builder_config(self, obs_builder_config):
    method set_reward_config (line 107) | def set_reward_config(self, reward_config):
    method create_env (line 111) | def create_env(self):

FILE: examples/Social_Cognition/ToCM/configs/Experiment.py
  class Experiment (line 4) | class Experiment(Config):  # 这个还没改且里面没有
    method __init__ (line 5) | def __init__(self, steps, episodes, random_seed, env_config, controlle...

FILE: examples/Social_Cognition/ToCM/configs/ToCM/ToCMAgentConfig.py
  class ToCMConfig (line 13) | class ToCMConfig(Config):  # 从Config继承
    method __init__ (line 14) | def __init__(self):
  class RSSMStateBase (line 43) | class RSSMStateBase:
    method map (line 47) | def map(self, func):
    method get_features (line 50) | def get_features(self):
    method get_dist (line 53) | def get_dist(self, *input):
    method type (line 56) | def type(self):
  class RSSMStateDiscrete (line 61) | class RSSMStateDiscrete(RSSMStateBase):
    method get_dist (line 64) | def get_dist(self, batch_shape, n_categoricals, n_classes):
  class RSSMStateCont (line 69) | class RSSMStateCont(RSSMStateBase):
    method get_dist (line 73) | def get_dist(self, *input):

FILE: examples/Social_Cognition/ToCM/configs/ToCM/ToCMControllerConfig.py
  class ToCMControllerConfig (line 6) | class ToCMControllerConfig(ToCMConfig):
    method __init__ (line 7) | def __init__(self, env_name, RANDOM_SEED, device):  # RANDOM_SEED:23 d...
    method create_controller (line 17) | def create_controller(self):

FILE: examples/Social_Cognition/ToCM/configs/ToCM/ToCMLearnerConfig.py
  class ToCMLearnerConfig (line 6) | class ToCMLearnerConfig(ToCMConfig):  # 从ToCMConfig继承，有输入维度、输出维度、隐层维度、隐层...
    method __init__ (line 7) | def __init__(self, env_name, RANDOM_SEED, device):
    method create_learner (line 32) | def create_learner(self):  # 通过config创建learner

FILE: examples/Social_Cognition/ToCM/configs/ToCM/optimal/starcraft/AgentConfig.py
  class ToCMConfig (line 4) | class ToCMConfig(Config):
    method __init__ (line 5) | def __init__(self):

FILE: examples/Social_Cognition/ToCM/configs/ToCM/optimal/starcraft/LearnerConfig.py
  class ToCMLearnerConfig (line 5) | class ToCMLearnerConfig(ToCMConfig):
    method __init__ (line 6) | def __init__(self):
    method create_learner (line 28) | def create_learner(self):

FILE: examples/Social_Cognition/ToCM/env/mpe/MPE.py
  class MPE (line 4) | class MPE:
    method __init__ (line 6) | def __init__(self, args):
    method to_dict (line 15) | def to_dict(self, l):
    method step (line 18) | def step(self, action_dict):  # action dict for each agent
    method reset (line 24) | def reset(self):
    method close (line 28) | def close(self):
    method get_avail_agent_actions (line 32) | def get_avail_agent_actions(self, handle):  # available handle is the ...

FILE: examples/Social_Cognition/ToCM/env/starcraft/StarCraft.py
  class StarCraft (line 4) | class StarCraft:
    method __init__ (line 6) | def __init__(self, env_name, random_seed):
    method to_dict (line 15) | def to_dict(self, l):
    method step (line 18) | def step(self, action_dict):
    method reset (line 23) | def reset(self):
    method render (line 27) | def render(self):
    method close (line 30) | def close(self):
    method get_avail_agent_actions (line 33) | def get_avail_agent_actions(self, handle):

FILE: examples/Social_Cognition/ToCM/environments.py
  class Env (line 4) | class Env(str, Enum):

FILE: examples/Social_Cognition/ToCM/mpe/MPE_Env.py
  function MPEEnv (line 18) | def MPEEnv(args):

FILE: examples/Social_Cognition/ToCM/mpe/core.py
  class EntityState (line 5) | class EntityState(object):
    method __init__ (line 6) | def __init__(self):
  class AgentState (line 13) | class AgentState(EntityState):
    method __init__ (line 14) | def __init__(self):
  class Action (line 20) | class Action(object):
    method __init__ (line 21) | def __init__(self):
  class Wall (line 28) | class Wall(object):
    method __init__ (line 29) | def __init__(self, orient='H', axis_pos=0.0, endpoints=(-1, 1), width=...
  class Entity (line 46) | class Entity(object):
    method __init__ (line 47) | def __init__(self):
    method mass (line 75) | def mass(self):
  class Landmark (line 79) | class Landmark(Entity):
    method __init__ (line 80) | def __init__(self):
  class Agent (line 84) | class Agent(Entity):
    method __init__ (line 85) | def __init__(self):
  class World (line 113) | class World(object):
    method __init__ (line 114) | def __init__(self):
    method entities (line 144) | def entities(self):
    method policy_agents (line 149) | def policy_agents(self):
    method scripted_agents (line 154) | def scripted_agents(self):
    method calculate_distances (line 157) | def calculate_distances(self):
    method assign_agent_colors (line 183) | def assign_agent_colors(self):
    method assign_landmark_colors (line 202) | def assign_landmark_colors(self):
    method step (line 207) | def step(self):
    method apply_action_force (line 228) | def apply_action_force(self, p_force):
    method apply_environment_force (line 240) | def apply_environment_force(self, p_force):
    method integrate_state (line 265) | def integrate_state(self, p_force):
    method update_agent_state (line 280) | def update_agent_state(self, agent):
    method get_entity_collision_force (line 290) | def get_entity_collision_force(self, ia, ib):
    method get_wall_collision_force (line 324) | def get_wall_collision_force(self, entity, wall):

FILE: examples/Social_Cognition/ToCM/mpe/environment.py
  class MultiAgentEnv (line 15) | class MultiAgentEnv(gym.Env):
    method __init__ (line 20) | def __init__(self, world, reset_callback=None, reward_callback=None,
    method seed (line 110) | def seed(self, seed=None):
    method step (line 117) | def step(self, action_n):
    method reset (line 148) | def reset(self):
    method _get_info (line 164) | def _get_info(self, agent):
    method _get_obs (line 170) | def _get_obs(self, agent):
    method _get_done (line 180) | def _get_done(self, agent):
    method _get_reward (line 191) | def _get_reward(self, agent):
    method _set_action (line 197) | def _set_action(self, action, agent, action_space, time=None):
    method _get_avail_action (line 261) | def _get_avail_action(self, handle):
    method _reset_render (line 265) | def _reset_render(self):
    method render (line 269) | def render(self, mode='human', close=True):
    method _make_receptor_locations (line 421) | def _make_receptor_locations(self, agent):

FILE: examples/Social_Cognition/ToCM/mpe/multi_discrete.py
  class MultiDiscrete (line 9) | class MultiDiscrete(gym.Space):
    method __init__ (line 26) | def __init__(self, array_of_param_array):
    method sample (line 31) | def sample(self):
    method contains (line 39) | def contains(self, x):
    method shape (line 43) | def shape(self):
    method __repr__ (line 46) | def __repr__(self):
    method __eq__ (line 49) | def __eq__(self, other):

FILE: examples/Social_Cognition/ToCM/mpe/rendering.py
  function get_display (line 35) | def get_display(spec):
  class Viewer (line 50) | class Viewer(object):
    method __init__ (line 51) | def __init__(self, width, height, display=None):
    method close (line 72) | def close(self):
    method window_closed_by_user (line 75) | def window_closed_by_user(self):
    method set_bounds (line 78) | def set_bounds(self, left, right, bottom, top):
    method add_geom (line 86) | def add_geom(self, geom):
    method add_onetime (line 89) | def add_onetime(self, geom):
    method render (line 92) | def render(self, return_rgb_array=False):
    method draw_circle (line 121) | def draw_circle(self, radius=10, res=30, filled=True, **attrs):
    method draw_polygon (line 127) | def draw_polygon(self, v, filled=True, **attrs):
    method draw_polyline (line 133) | def draw_polyline(self, v, **attrs):
    method draw_line (line 139) | def draw_line(self, start, end, **attrs):
    method get_array (line 145) | def get_array(self):
  function _add_attrs (line 154) | def _add_attrs(geom, attrs):
  class Geom (line 161) | class Geom(object):
    method __init__ (line 162) | def __init__(self):
    method render (line 166) | def render(self):
    method render1 (line 173) | def render1(self):
    method add_attr (line 176) | def add_attr(self, attr):
    method set_color (line 179) | def set_color(self, r, g, b, alpha=1):
  class Attr (line 183) | class Attr(object):
    method enable (line 184) | def enable(self):
    method disable (line 187) | def disable(self):
  class Transform (line 191) | class Transform(Attr):
    method __init__ (line 192) | def __init__(self, translation=(0.0, 0.0), rotation=0.0, scale=(1, 1)):
    method enable (line 197) | def enable(self):
    method disable (line 204) | def disable(self):
    method set_translation (line 207) | def set_translation(self, newx, newy):
    method set_rotation (line 210) | def set_rotation(self, new):
    method set_scale (line 213) | def set_scale(self, newx, newy):
  class Color (line 217) | class Color(Attr):
    method __init__ (line 218) | def __init__(self, vec4):
    method enable (line 221) | def enable(self):
  class LineStyle (line 225) | class LineStyle(Attr):
    method __init__ (line 226) | def __init__(self, style):
    method enable (line 229) | def enable(self):
    method disable (line 233) | def disable(self):
  class LineWidth (line 237) | class LineWidth(Attr):
    method __init__ (line 238) | def __init__(self, stroke):
    method enable (line 241) | def enable(self):
  class Point (line 245) | class Point(Geom):
    method __init__ (line 246) | def __init__(self):
    method render1 (line 249) | def render1(self):
  class FilledPolygon (line 255) | class FilledPolygon(Geom):
    method __init__ (line 256) | def __init__(self, v):
    method render1 (line 260) | def render1(self):
  function make_circle (line 280) | def make_circle(radius=10, res=30, filled=True):
  function make_polygon (line 291) | def make_polygon(v, filled=True):
  function make_polyline (line 298) | def make_polyline(v):
  function make_capsule (line 302) | def make_capsule(length, width):
  class Compound (line 312) | class Compound(Geom):
    method __init__ (line 313) | def __init__(self, gs):
    method render1 (line 319) | def render1(self):
  class PolyLine (line 324) | class PolyLine(Geom):
    method __init__ (line 325) | def __init__(self, v, close):
    method render1 (line 332) | def render1(self):
    method set_linewidth (line 338) | def set_linewidth(self, x):
  class Line (line 342) | class Line(Geom):
    method __init__ (line 343) | def __init__(self, start=(0.0, 0.0), end=(0.0, 0.0)):
    method render1 (line 350) | def render1(self):
  class Image (line 357) | class Image(Geom):
    method __init__ (line 358) | def __init__(self, fname, width, height):
    method render1 (line 366) | def render1(self):
  class SimpleImageViewer (line 373) | class SimpleImageViewer(object):
    method __init__ (line 374) | def __init__(self, display=None):
    method imshow (line 379) | def imshow(self, arr):
    method close (line 397) | def close(self):
    method __del__ (line 402) | def __del__(self):

FILE: examples/Social_Cognition/ToCM/mpe/scenario.py
  class BaseScenario (line 5) | class BaseScenario(object):
    method make_world (line 7) | def make_world(self):
    method reset_world (line 11) | def reset_world(self, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/__init__.py
  function load (line 4) | def load(name):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/hetero_spread.py
  class Scenario (line 7) | class Scenario(BaseScenario):
    method make_world (line 8) | def make_world(self, args):
    method reset_world (line 47) | def reset_world(self, world):
    method benchmark_data (line 68) | def benchmark_data(self, agent, world):
    method is_collision (line 87) | def is_collision(self, agent1, agent2):
    method reward (line 93) | def reward(self, agent, world):
    method observation (line 127) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_adversary.py
  class Scenario (line 7) | class Scenario(BaseScenario):
    method make_world (line 9) | def make_world(self, args):
    method reset_world (line 36) | def reset_world(self, world):
    method benchmark_data (line 55) | def benchmark_data(self, agent, world):
    method good_agents (line 67) | def good_agents(self, world):
    method adversaries (line 71) | def adversaries(self, world):
    method reward (line 74) | def reward(self, agent, world):
    method agent_reward (line 78) | def agent_reward(self, agent, world):
    method adversary_reward (line 107) | def adversary_reward(self, agent, world):
    method observation (line 119) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_crypto.py
  class CryptoAgent (line 13) | class CryptoAgent(Agent):
    method __init__ (line 14) | def __init__(self):
  class Scenario (line 19) | class Scenario(BaseScenario):
    method make_world (line 21) | def make_world(self, args):
    method reset_world (line 46) | def reset_world(self, world):
    method benchmark_data (line 76) | def benchmark_data(self, agent, world):
    method good_listeners (line 81) | def good_listeners(self, world):
    method good_agents (line 85) | def good_agents(self, world):
    method adversaries (line 89) | def adversaries(self, world):
    method reward (line 92) | def reward(self, agent, world):
    method agent_reward (line 95) | def agent_reward(self, agent, world):
    method adversary_reward (line 114) | def adversary_reward(self, agent, world):
    method observation (line 121) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_crypto_display.py
  class CryptoAgent (line 13) | class CryptoAgent(Agent):
    method __init__ (line 14) | def __init__(self):
  class Scenario (line 19) | class Scenario(BaseScenario):
    method make_world (line 21) | def make_world(self, args):
    method reset_world (line 46) | def reset_world(self, world):
    method benchmark_data (line 82) | def benchmark_data(self, agent, world):
    method good_listeners (line 87) | def good_listeners(self, world):
    method good_agents (line 91) | def good_agents(self, world):
    method adversaries (line 95) | def adversaries(self, world):
    method reward (line 98) | def reward(self, agent, world):
    method agent_reward (line 101) | def agent_reward(self, agent, world):
    method adversary_reward (line 120) | def adversary_reward(self, agent, world):
    method observation (line 127) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_push.py
  class Scenario (line 12) | class Scenario(BaseScenario):
    method make_world (line 13) | def make_world(self, args):
    method reset_world (line 42) | def reset_world(self, world):
    method reward (line 67) | def reward(self, agent, world):
    method agent_reward (line 71) | def agent_reward(self, agent, world):
    method adversary_reward (line 75) | def adversary_reward(self, agent, world):
    method observation (line 86) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_reference.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, args):
    method reset_world (line 34) | def reset_world(self, world):
    method reward (line 62) | def reward(self, agent, world):
    method observation (line 69) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_speaker_listener.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, args):
    method reset_world (line 38) | def reset_world(self, world):
    method benchmark_data (line 65) | def benchmark_data(self, agent, world):
    method reward (line 69) | def reward(self, agent, world):
    method observation (line 75) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_spread.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, args):
    method reset_world (line 32) | def reset_world(self, world):
    method benchmark_data (line 47) | def benchmark_data(self, agent, world):
    method is_collision (line 66) | def is_collision(self, agent1, agent2):
    method reward (line 72) | def reward(self, agent, world):
    method observation (line 86) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_tag.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, args):
    method reset_world (line 38) | def reset_world(self, world):
    method benchmark_data (line 54) | def benchmark_data(self, agent, world):
    method is_collision (line 65) | def is_collision(self, agent1, agent2):
    method good_agents (line 72) | def good_agents(self, world):
    method adversaries (line 76) | def adversaries(self, world):
    method reward (line 79) | def reward(self, agent, world):
    method agent_reward (line 84) | def agent_reward(self, agent, world):
    method adversary_reward (line 111) | def adversary_reward(self, agent, world):
    method observation (line 127) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/mpe/scenarios/simple_world_comm.py
  class Scenario (line 6) | class Scenario(BaseScenario):
    method make_world (line 7) | def make_world(self, args):
    method set_boundaries (line 59) | def set_boundaries(self, world):
    method reset_world (line 87) | def reset_world(self, world):
    method benchmark_data (line 114) | def benchmark_data(self, agent, world):
    method is_collision (line 124) | def is_collision(self, agent1, agent2):
    method good_agents (line 131) | def good_agents(self, world):
    method adversaries (line 135) | def adversaries(self, world):
    method reward (line 138) | def reward(self, agent, world):
    method outside_boundary (line 144) | def outside_boundary(self, agent):
    method agent_reward (line 151) | def agent_reward(self, agent, world):
    method adversary_reward (line 182) | def adversary_reward(self, agent, world):
    method observation2 (line 199) | def observation2(self, agent, world):
    method observation (line 222) | def observation(self, agent, world):

FILE: examples/Social_Cognition/ToCM/networks/ToCM/action.py
  class BCNoSpikingLIFNode (line 20) | class BCNoSpikingLIFNode(LIFNode):
    method __init__ (line 21) | def __init__(self, *args, **kwargs):
    method forward (line 24) | def forward(self, dv: torch.Tensor):
  class Actor (line 72) | class Actor(nn.Module):
    method __init__ (line 73) | def __init__(self, in_dim, out_dim, hidden_size, layers, activation=nn...
    method forward (line 78) | def forward(self, state_features):
  class AttentionActor (line 84) | class AttentionActor(nn.Module):
    method __init__ (line 85) | def __init__(self, in_dim, out_dim, hidden_size, layers, node='LIFNode...
    method forward (line 119) | def forward(self, state_features):  # 状态值tensor
    method reset (line 153) | def reset(self):

FILE: examples/Social_Cognition/ToCM/networks/ToCM/critic.py
  class BCNoSpikingLIFNode (line 19) | class BCNoSpikingLIFNode(LIFNode):
    method __init__ (line 20) | def __init__(self, *args, **kwargs):
    method forward (line 23) | def forward(self, dv: torch.Tensor):
  function mem_update (line 33) | def mem_update(fc, x, mem, spike):
  class Critic (line 40) | class Critic(nn.Module):
    method __init__ (line 41) | def __init__(self, in_dim, hidden_size, layers=2, node='LIFNode', time...
    method forward (line 79) | def forward(self, state_features, actions):
    method reset (line 99) | def reset(self):
  class MADDPGCritic (line 176) | class MADDPGCritic(nn.Module):
    method __init__ (line 177) | def __init__(self, in_dim, hidden_size, layers=2, activation=nn.ELU):
    method forward (line 184) | def forward(self, state_features, actions):

FILE: examples/Social_Cognition/ToCM/networks/ToCM/dense.py
  class DenseModel (line 8) | class DenseModel(nn.Module):
    method __init__ (line 9) | def __init__(self, in_dim, out_dim, layers, hidden, activation="nn.ELU...
    method forward (line 14) | def forward(self, features):
  class DenseBinaryModel (line 18) | class DenseBinaryModel(DenseModel):
    method __init__ (line 19) | def __init__(self, in_dim, out_dim, layers, hidden, activation="nn.ELU...
    method forward (line 22) | def forward(self, features):

FILE: examples/Social_Cognition/ToCM/networks/ToCM/rnns.py
  function stack_states (line 9) | def stack_states(rssm_states: list, dim):
  function cat_states (line 13) | def cat_states(rssm_states: list, dim):
  function reduce_states (line 17) | def reduce_states(rssm_states: list, dim, func):
  class DiscreteLatentDist (line 22) | class DiscreteLatentDist(nn.Module):
    method __init__ (line 23) | def __init__(self, in_dim, n_categoricals, n_classes, hidden_size):
    method forward (line 31) | def forward(self, x):
  class RSSMTransition (line 39) | class RSSMTransition(nn.Module):
    method __init__ (line 40) | def __init__(self, config, hidden_size=200, activation=nn.ReLU):
    method _build_rnn_input_model (line 52) | def _build_rnn_input_model(self, in_dim):
    method forward (line 57) | def forward(self, prev_actions, prev_states, mask=None):
  class RSSMRepresentation (line 68) | class RSSMRepresentation(nn.Module):
    method __init__ (line 69) | def __init__(self, config, transition_model: RSSMTransition):
    method initial_state (line 77) | def initial_state(self, batch_size, n_agents, **kwargs):
    method forward (line 82) | def forward(self, obs_embed, prev_actions, prev_states, mask=None):
  function rollout_representation (line 96) | def rollout_representation(representation_model, steps, obs_embed, actio...
  function rollout_policy (line 118) | def rollout_policy(transition_model, av_action, steps, policy, prev_stat...

FILE: examples/Social_Cognition/ToCM/networks/ToCM/utils.py
  class AtanLIFNode (line 9) | class AtanLIFNode(LIFNode):
    method __init__ (line 10) | def __init__(self, tau=0.5, *args, **kwargs):
  class BCNoSpikingLIFNode (line 15) | class BCNoSpikingLIFNode(LIFNode):
    method __init__ (line 16) | def __init__(self, tau, *args, **kwargs):
    method forward (line 20) | def forward(self, dv: torch.Tensor):
  function build_model_snn (line 27) | def build_model_snn(in_dim, out_dim, layers, hidden, th=0.5, re=0.0, tau...
  function build_model (line 57) | def build_model(in_dim, out_dim, layers, hidden, activation, normalize=l...

FILE: examples/Social_Cognition/ToCM/networks/ToCM/vae.py
  class Decoder (line 7) | class Decoder(nn.Module):
    method __init__ (line 9) | def __init__(self, embed, hidden, out_dim, layers=2):
    method forward (line 14) | def forward(self, z):
  class Encoder (line 19) | class Encoder(nn.Module):
    method __init__ (line 21) | def __init__(self, in_dim, hidden, embed, layers=2):
    method forward (line 27) | def forward(self, x):

FILE: examples/Social_Cognition/ToCM/networks/transformer/layers.py
  class PositionalEncoding (line 7) | class PositionalEncoding(nn.Module):
    method __init__ (line 10) | def __init__(self, d_hid, n_position=2):
    method _get_sinusoid_encoding_table (line 24) | def _get_sinusoid_encoding_table(n_position, d_hid):
    method forward (line 37) | def forward(self, x):
  class AttentionEncoder (line 41) | class AttentionEncoder(nn.Module):
    method __init__ (line 43) | def __init__(self, n_layers, in_dim, hidden, dropout=0.):
    method forward (line 50) | def forward(self, enc_input, **kwargs):
  class AttentionActorEncoder (line 56) | class AttentionActorEncoder(nn.Module):
    method __init__ (line 58) | def __init__(self, n_layers, in_dim, hidden, dropout=0.):
    method forward (line 64) | def forward(self, enc_input, **kwargs):

FILE: examples/Social_Cognition/ToCM/smac/bin/map_list.py
  function main (line 10) | def main():

FILE: examples/Social_Cognition/ToCM/smac/env/multiagentenv.py
  class MultiAgentEnv (line 6) | class MultiAgentEnv(object):
    method step (line 7) | def step(self, actions):
    method get_obs (line 11) | def get_obs(self):
    method get_obs_agent (line 15) | def get_obs_agent(self, agent_id):
    method get_obs_size (line 19) | def get_obs_size(self):
    method get_state (line 23) | def get_state(self):
    method get_state_size (line 27) | def get_state_size(self):
    method get_avail_actions (line 31) | def get_avail_actions(self):
    method get_avail_agent_actions (line 35) | def get_avail_agent_actions(self, agent_id):
    method get_total_actions (line 39) | def get_total_actions(self):
    method reset (line 43) | def reset(self):
    method render (line 47) | def render(self):
    method close (line 50) | def close(self):
    method seed (line 53) | def seed(self):
    method save_replay (line 56) | def save_replay(self):
    method get_env_info (line 60) | def get_env_info(self):

FILE: examples/Social_Cognition/ToCM/smac/env/pettingzoo/StarCraft2PZEnv.py
  function parallel_env (line 13) | def parallel_env(max_cycles=max_cycles_default, **smac_args):
  function raw_env (line 17) | def raw_env(max_cycles=max_cycles_default, **smac_args):
  function make_env (line 21) | def make_env(raw_env):
  class smac_parallel_env (line 32) | class smac_parallel_env(ParallelEnv):
    method __init__ (line 33) | def __init__(self, env, max_cycles):
    method _init_agents (line 63) | def _init_agents(self):
    method seed (line 106) | def seed(self, seed=None):
    method render (line 113) | def render(self, mode="human"):
    method close (line 116) | def close(self):
    method reset (line 119) | def reset(self):
    method get_agent_smac_id (line 128) | def get_agent_smac_id(self, agent):
    method _all_rewards (line 131) | def _all_rewards(self, reward):
    method _observe_all (line 137) | def _observe_all(self):
    method _all_dones (line 151) | def _all_dones(self, step_done=False):
    method step (line 163) | def step(self, all_actions):
    method __del__ (line 188) | def __del__(self):
  class _parallel_env (line 195) | class _parallel_env(smac_parallel_env, EzPickle):
    method __init__ (line 198) | def __init__(self, max_cycles, **smac_args):

FILE: examples/Social_Cognition/ToCM/smac/env/pettingzoo/test/all_test.py
  function test_env (line 18) | def test_env(map_name):

FILE: examples/Social_Cognition/ToCM/smac/env/starcraft2/maps/__init__.py
  function get_map_params (line 8) | def get_map_params(map_name):

FILE: examples/Social_Cognition/ToCM/smac/env/starcraft2/maps/smac_maps.py
  class SMACMap (line 8) | class SMACMap(lib.Map):
  function get_smac_map_registry (line 227) | def get_smac_map_registry():

FILE: examples/Social_Cognition/ToCM/smac/env/starcraft2/render.py
  function clamp (line 20) | def clamp(n, smallest, largest):
  function _get_desktop_size (line 24) | def _get_desktop_size():
  class StarCraft2Renderer (line 42) | class StarCraft2Renderer:
    method __init__ (line 43) | def __init__(self, env, mode):
    method close (line 110) | def close(self):
    method _get_units (line 114) | def _get_units(self):
    method get_unit_name (line 121) | def get_unit_name(self, surf, name, radius):
    method render (line 134) | def render(self, mode):
    method draw_base_map (line 170) | def draw_base_map(self, surf):
    method draw_units (line 190) | def draw_units(self, surf):
    method draw_overlay (line 310) | def draw_overlay(self, surf):
    method draw_screen (line 343) | def draw_screen(self, surf):

FILE: examples/Social_Cognition/ToCM/smac/env/starcraft2/starcraft2.py
  class Direction (line 54) | class Direction(enum.IntEnum):
  class StarCraft2Env (line 61) | class StarCraft2Env(MultiAgentEnv):
    method __init__ (line 65) | def __init__(
    method _launch (line 315) | def _launch(self):
    method reset (line 395) | def reset(self):
    method _restart (line 434) | def _restart(self):
    method full_restart (line 445) | def full_restart(self):
    method step (line 451) | def step(self, actions):
    method get_agent_action (line 547) | def get_agent_action(self, a_id, action):
    method get_agent_action_heuristic (line 656) | def get_agent_action_heuristic(self, a_id, action):
    method reward_battle (line 773) | def reward_battle(self):
    method get_total_actions (line 830) | def get_total_actions(self):
    method distance (line 835) | def distance(x1, y1, x2, y2):
    method unit_shoot_range (line 839) | def unit_shoot_range(self, agent_id):
    method unit_sight_range (line 843) | def unit_sight_range(self, agent_id):
    method unit_max_cooldown (line 847) | def unit_max_cooldown(self, unit):
    method save_replay (line 862) | def save_replay(self):
    method unit_max_shield (line 873) | def unit_max_shield(self, unit):
    method can_move (line 882) | def can_move(self, unit, direction):
    method get_surrounding_points (line 900) | def get_surrounding_points(self, unit, include_self=False):
    method check_bounds (line 923) | def check_bounds(self, x, y):
    method get_surrounding_pathing (line 927) | def get_surrounding_pathing(self, unit):
    method get_surrounding_height (line 936) | def get_surrounding_height(self, unit):
    method get_obs_agent (line 945) | def get_obs_agent(self, agent_id):
    method get_obs (line 1126) | def get_obs(self):
    method get_state (line 1134) | def get_state(self):
    method get_ally_num_attributes (line 1165) | def get_ally_num_attributes(self):
    method get_enemy_num_attributes (line 1168) | def get_enemy_num_attributes(self):
    method get_state_dict (line 1171) | def get_state_dict(self):
    method get_obs_enemy_feats_size (line 1259) | def get_obs_enemy_feats_size(self):
    method get_obs_ally_feats_size (line 1270) | def get_obs_ally_feats_size(self):
    method get_obs_own_feats_size (line 1284) | def get_obs_own_feats_size(self):
    method get_obs_move_feats_size (line 1296) | def get_obs_move_feats_size(self):
    method get_obs_size (line 1308) | def get_obs_size(self):
    method get_state_size (line 1321) | def get_state_size(self):
    method get_visibility_matrix (line 1341) | def get_visibility_matrix(self):
    method get_unit_type_id (line 1384) | def get_unit_type_id(self, unit, ally):
    method get_avail_agent_actions (line 1415) | def get_avail_agent_actions(self, agent_id):
    method get_avail_actions (line 1461) | def get_avail_actions(self):
    method close (line 1469) | def close(self):
    method seed (line 1477) | def seed(self):
    method render (line 1481) | def render(self, mode="human"):
    method _kill_all_units (line 1491) | def _kill_all_units(self):
    method init_units (line 1501) | def init_units(self):
    method get_unit_types (line 1564) | def get_unit_types(self):
    method update_units (line 1573) | def update_units(self):
    method _init_ally_unit_types (line 1625) | def _init_ally_unit_types(self, min_unit_type):
    method only_medivac_left (line 1655) | def only_medivac_left(self, ally):
    method get_unit_by_id (line 1679) | def get_unit_by_id(self, a_id):
    method get_stats (line 1683) | def get_stats(self):
    method get_env_info (line 1694) | def get_env_info(self):

FILE: examples/Social_Cognition/ToCM/smac/examples/pettingzoo/pettingzoo_demo.py
  function main (line 10) | def main():

FILE: examples/Social_Cognition/ToCM/smac/examples/random_agents.py
  function main (line 9) | def main():

FILE: examples/Social_Cognition/ToCM/smac/examples/rllib/env.py
  class RLlibStarCraft2Env (line 16) | class RLlibStarCraft2Env(rllib.MultiAgentEnv):
    method __init__ (line 19) | def __init__(self, **smac_args):
    method reset (line 44) | def reset(self):
    method step (line 62) | def step(self, action_dict):
    method close (line 109) | def close(self):
    method seed (line 113) | def seed(self, seed):

FILE: examples/Social_Cognition/ToCM/smac/examples/rllib/model.py
  class MaskedActionsModel (line 11) | class MaskedActionsModel(Model):
    method _build_layers_v2 (line 17) | def _build_layers_v2(self, input_dict, num_outputs, options):

FILE: examples/Social_Cognition/ToCM/smac/examples/rllib/run_qmix.py
  function env_creator (line 28) | def env_creator(smac_args):

FILE: examples/Social_Cognition/ToCM/train.py
  function occumpy_mem (line 20) | def occumpy_mem(cuda_device):
  function parse_args (line 30) | def parse_args():
  function setup_seed (line 49) | def setup_seed(seed):
  function train_ToCM (line 60) | def train_ToCM(exp, n_workers):  # no env.episode_length
  function get_env_info (line 65) | def get_env_info(configs, env):
  function get_env_info_mpe (line 72) | def get_env_info_mpe(configs, env):  # add to ToCM controller and worker
  function prepare_starcraft_configs (line 84) | def prepare_starcraft_configs(env_name, device):
  function prepare_mpe_configs (line 98) | def prepare_mpe_configs(arg):

FILE: examples/Social_Cognition/ToCM/utils/mlp_buffer.py
  function _cast (line 6) | def _cast(x):
  class MlpReplayBuffer (line 10) | class MlpReplayBuffer(object):
    method __init__ (line 11) | def __init__(self, policy_info, policy_agents, buffer_size, use_same_s...
    method __len__ (line 36) | def __len__(self):
    method insert (line 39) | def insert(self, num_insert_steps, obs, share_obs, acts, rewards,
    method sample (line 71) | def sample(self, batch_size):
  class MlpPolicyBuffer (line 98) | class MlpPolicyBuffer(object):
    method __init__ (line 100) | def __init__(self, buffer_size, num_agents, obs_space, share_obs_space...
    method __len__ (line 158) | def __len__(self):
    method insert (line 161) | def insert(self, num_insert_steps, obs, share_obs, acts, rewards,
    method sample_inds (line 210) | def sample_inds(self, sample_inds):
  class PrioritizedMlpReplayBuffer (line 260) | class PrioritizedMlpReplayBuffer(MlpReplayBuffer):
    method __init__ (line 261) | def __init__(self, alpha, policy_info, policy_agents, buffer_size, use...
    method insert (line 277) | def insert(self, num_insert_steps, obs, share_obs, acts, rewards, next...
    method _sample_proportional (line 289) | def _sample_proportional(self, batch_size, p_id=None):
    method sample (line 295) | def sample(self, batch_size, beta=0, p_id=None):
    method update_priorities (line 322) | def update_priorities(self, idxes, priorities, p_id=None):

FILE: examples/Social_Cognition/ToCM/utils/mlp_nstep_buffer.py
  class NStepReplayBuffer (line 6) | class NStepReplayBuffer:
    method __init__ (line 7) | def __init__(self, max_size, episode_len, n, policy_ids, agent_ids, po...
    method push (line 21) | def push(self, t_env, observation_batch, action_batch, reward_batch, n...
    method sample (line 52) | def sample(self, batch_size):
  class NStepPolicyBuffer (line 76) | class NStepPolicyBuffer:
    method __init__ (line 77) | def __init__(self, policy_id, max_size, episode_len, n, policy_agents,...
    method push (line 101) | def push(self, num_envs, t_env, observation_batch, action_batch, rewar...
    method get (line 141) | def get(self, batch_inds, start_inds):

FILE: examples/Social_Cognition/ToCM/utils/popart.py
  class PopArt (line 8) | class PopArt(nn.Module):
    method __init__ (line 11) | def __init__(self, input_shape, norm_axes=1, beta=0.99999, per_element...
    method reset_parameters (line 26) | def reset_parameters(self):
    method running_mean_var (line 31) | def running_mean_var(self):
    method forward (line 37) | def forward(self, input_vector, train=True):
    method denormalize (line 62) | def denormalize(self, input_vector):

FILE: examples/Social_Cognition/ToCM/utils/rec_buffer.py
  function _cast (line 6) | def _cast(x):
  class RecReplayBuffer (line 10) | class RecReplayBuffer(object):
    method __init__ (line 11) | def __init__(self, policy_info, policy_agents, buffer_size, episode_le...
    method __len__ (line 36) | def __len__(self):
    method insert (line 39) | def insert(self, num_insert_episodes, obs, share_obs, acts, rewards, d...
    method sample (line 62) | def sample(self, batch_size):
  class RecPolicyBuffer (line 85) | class RecPolicyBuffer(object):
    method __init__ (line 86) | def __init__(self, buffer_size, episode_length, num_agents, obs_space,...
    method __len__ (line 143) | def __len__(self):
    method insert (line 146) | def insert(self, num_insert_episodes, obs, share_obs, acts, rewards, d...
    method sample_inds (line 192) | def sample_inds(self, sample_inds):
  class PrioritizedRecReplayBuffer (line 243) | class PrioritizedRecReplayBuffer(RecReplayBuffer):
    method __init__ (line 244) | def __init__(self, alpha, policy_info, policy_agents, buffer_size, epi...
    method insert (line 262) | def insert(self, num_insert_episodes, obs, share_obs, acts, rewards, d...
    method _sample_proportional (line 272) | def _sample_proportional(self, batch_size, p_id=None):
    method sample (line 278) | def sample(self, batch_size, beta=0, p_id=None):
    method update_priorities (line 306) | def update_priorities(self, idxes, priorities, p_id=None):

FILE: examples/Social_Cognition/ToCM/utils/segment_tree.py
  function unique (line 4) | def unique(sorted_array):
  class SegmentTree (line 18) | class SegmentTree(object):
    method __init__ (line 19) | def __init__(self, capacity, operation, neutral_element):
    method _reduce_helper (line 42) | def _reduce_helper(self, start, end, node, node_start, node_end):
    method reduce (line 58) | def reduce(self, start=0, end=None):
    method __setitem__ (line 74) | def __setitem__(self, idx, val):
    method __getitem__ (line 91) | def __getitem__(self, idx):
  class SumSegmentTree (line 97) | class SumSegmentTree(SegmentTree):
    method __init__ (line 98) | def __init__(self, capacity):
    method sum (line 106) | def sum(self, start=0, end=None):
    method find_prefixsum_idx (line 115) | def find_prefixsum_idx(self, prefixsum):
  class MinSegmentTree (line 149) | class MinSegmentTree(SegmentTree):
    method __init__ (line 150) | def __init__(self, capacity):
    method min (line 158) | def min(self, start=0, end=None):

FILE: examples/Social_Cognition/ToCM/utils/util.py
  function to_torch (line 12) | def to_torch(input):
  function to_numpy (line 15) | def to_numpy(x):
  class FixedCategorical (line 18) | class FixedCategorical(torch.distributions.Categorical):
    method sample (line 19) | def sample(self):
    method log_probs (line 22) | def log_probs(self, actions):
    method mode (line 31) | def mode(self):
  class MultiDiscrete (line 35) | class MultiDiscrete(gym.Space):
    method __init__ (line 52) | def __init__(self, array_of_param_array):
    method sample (line 58) | def sample(self):
    method contains (line 64) | def contains(self, x):
    method shape (line 68) | def shape(self):
    method __repr__ (line 71) | def __repr__(self):
    method __eq__ (line 74) | def __eq__(self, other):
  class DecayThenFlatSchedule (line 78) | class DecayThenFlatSchedule():
    method __init__ (line 79) | def __init__(self,
    method eval (line 95) | def eval(self, T):
  function huber_loss (line 103) | def huber_loss(e, d):
  function mse_loss (line 109) | def mse_loss(e):
  function init (line 113) | def init(module, weight_init, bias_init, gain=1):
  function get_clones (line 119) | def get_clones(module, N):
  function soft_update (line 123) | def soft_update(target, source, tau):
  function hard_update (line 137) | def hard_update(target, source):
  function average_gradients (line 148) | def average_gradients(model):
  function onehot_from_logits (line 156) | def onehot_from_logits(logits, avail_logits=None, eps=0.0):
  function sample_gumbel (line 178) | def sample_gumbel(shape, eps=1e-20, tens_type=torch.FloatTensor):
  function gumbel_softmax_sample (line 184) | def gumbel_softmax_sample(logits, avail_logits, temperature, device=torc...
  function gumbel_softmax (line 199) | def gumbel_softmax(logits, avail_logits=None, temperature=1.0, hard=Fals...
  function gaussian_noise (line 217) | def gaussian_noise(shape, std):
  function get_obs_shape (line 221) | def get_obs_shape(obs_space):
  function get_dim_from_space (line 231) | def get_dim_from_space(space):
  function get_state_dim (line 247) | def get_state_dim(observation_dict, action_dict):
  function get_cent_act_dim (line 260) | def get_cent_act_dim(action_space):
  function is_discrete (line 271) | def is_discrete(space):
  function is_multidiscrete (line 278) | def is_multidiscrete(space):
  function make_onehot (line 285) | def make_onehot(int_action, action_dim, seq_len=None):
  function avail_choose (line 298) | def avail_choose(x, avail_x=None):
  function tile_images (line 306) | def tile_images(img_nhwc):

FILE: examples/Social_Cognition/ToM/BrainArea/PFC_ToM.py
  class PFC_ToM (line 17) | class PFC_ToM(dlPFC):
    method __init__ (line 21) | def __init__(self,
    method _rest_c (line 48) | def _rest_c(self):
    method _create_fc (line 52) | def _create_fc(self):
    method update_c (line 61) | def update_c(self, c, dw, tau_c=0.2):
    method _call_reward (line 78) | def _call_reward(self, R, c, s, T_map):  # eligibility
    method update_s (line 104) | def update_s(self, R, mapping):
    method forward (line 111) | def forward(self, inputs, num_action, episode):

FILE: examples/Social_Cognition/ToM/BrainArea/TPJ.py
  class ToM (line 23) | class ToM:
    method __init__ (line 24) | def __init__(self, env):
    method TPJ (line 36) | def TPJ(self, NPC_num, axis, obs):
    method gain_obs (line 70) | def gain_obs(self, a,aa,b,c,bb,cc):
    method belief_reasoning (line 85) | def belief_reasoning(self, test_x, net_NPC, num_action, episode):
    method state_evaluation (line 91) | def state_evaluation(self, prediction_next_state):
    method prediction_state (line 111) | def prediction_state(self, axis_new, axis, action_NPC1, net, num_actio...
    method altruism (line 144) | def altruism(self, axis_switch, axis_NPC, n_actions):
    method INS (line 207) | def INS(self, axis1, axis2):

FILE: examples/Social_Cognition/ToM/BrainArea/dACC.py
  class dACC (line 16) | class dACC(BaseModule):
    method __init__ (line 20) | def __init__(self,
    method _rest_c (line 41) | def _rest_c(self):
    method _create_fc (line 45) | def _create_fc(self):
    method update_c (line 54) | def update_c(self, c, STDP, tau_c=0.2):
    method forward (line 69) | def forward(self, inputs, epoch):

FILE: examples/Social_Cognition/ToM/BrainArea/one_hot.py
  function one_hot (line 4) | def one_hot(value):

FILE: examples/Social_Cognition/ToM/data/one_hot.py
  function one_hot (line 4) | def one_hot(value):

FILE: examples/Social_Cognition/ToM/env/env.py
  class FalseBelief_env (line 58) | class FalseBelief_env(object):
    method __init__ (line 59) | def __init__(self, reward=10):
    method _build_AB (line 82) | def _build_AB(self):
    method _agent_init (line 92) | def _agent_init(self):
    method actu_obs (line 130) | def actu_obs(self):
    method gain_obs (line 177) | def gain_obs(self, a, aa, b, c, bb, cc):
    method gain_axis (line 196) | def gain_axis(self,a,aa,b,c,bb,cc):
    method interact (line 219) | def interact(self, action_NPC1, action_NPC2, action_agent):
    method SHOW (line 328) | def SHOW(self):
    method reset (line 341) | def reset(self):
    method getBlankBoard (line 344) | def getBlankBoard(self):
    method ValidPos (line 360) | def ValidPos(self, piece1, piece2, xT=0, yT=0):
    method isNotWall (line 373) | def isNotWall(self, board, piece, xT=0 , yT=0 ):
    method gameover (line 387) | def gameover(self, location):
    method pixel (line 408) | def pixel(self, xbox, ybox):
    method DrawBox (line 411) | def DrawBox(self, xbox, ybox, color, xpixel=None, ypixel=None):
    method fun_trigger (line 435) | def fun_trigger(self):
    method DrawCircle (line 440) | def DrawCircle(self,  xbox, ybox, color, xpixel=None, ypixel=None):
    method DrawPiece (line 454) | def DrawPiece(self, piece, xpixel=None, ypixel=None):
    method DrawBoard (line 462) | def DrawBoard(self, board):
    method ShowScore (line 471) | def ShowScore(self, score):
    method Terminal (line 477) | def Terminal(self, piece1, piece2, piece1_old, piece2_old):
    method Paint (line 485) | def Paint(self, board, piece, color):

FILE: examples/Social_Cognition/ToM/env/env3_train_env00.py
  class FalseBelief_env0 (line 55) | class FalseBelief_env0(object):
    method __init__ (line 56) | def __init__(self, reward=10):
    method _build_AB (line 78) | def _build_AB(self):
    method _agent_init (line 88) | def _agent_init(self):
    method actu_obs (line 126) | def actu_obs(self):
    method gain_obs (line 173) | def gain_obs(self, a, aa, b, c, bb, cc):
    method gain_axis (line 192) | def gain_axis(self,a,aa,b,c,bb,cc):
    method interact (line 215) | def interact(self, action_NPC1, action_NPC2, action_agent):
    method SHOW (line 324) | def SHOW(self):
    method reset (line 337) | def reset(self):
    method getBlankBoard (line 340) | def getBlankBoard(self):
    method ValidPos (line 357) | def ValidPos(self, piece1, piece2, xT=0, yT=0):
    method isNotWall (line 370) | def isNotWall(self, board, piece, xT=0 , yT=0 ):
    method gameover (line 384) | def gameover(self, location):
    method pixel (line 405) | def pixel(self, xbox, ybox):
    method DrawBox (line 408) | def DrawBox(self, xbox, ybox, color, xpixel=None, ypixel=None):
    method DrawCircle (line 432) | def DrawCircle(self,  xbox, ybox, color, xpixel=None, ypixel=None):
    method DrawPiece (line 446) | def DrawPiece(self, piece, xpixel=None, ypixel=None):
    method DrawBoard (line 454) | def DrawBoard(self, board):
    method ShowScore (line 462) | def ShowScore(self, score):
    method Terminal (line 468) | def Terminal(self, piece1, piece2, piece1_old, piece2_old):
    method Paint (line 476) | def Paint(self, board, piece, color):

FILE: examples/Social_Cognition/ToM/env/env3_train_env01.py
  class FalseBelief_env1 (line 59) | class FalseBelief_env1(object):
    method __init__ (line 60) | def __init__(self, reward=10):
    method _build_AB (line 82) | def _build_AB(self):
    method _agent_init (line 93) | def _agent_init(self):
    method actu_obs (line 120) | def actu_obs(self):
    method gain_obs (line 152) | def gain_obs(self, a,aa,c,cc):
    method gain_axis (line 158) | def gain_axis(self,a,aa,b,c,bb,cc):
    method interact (line 172) | def interact(self, action_NPC2, action_agent):
    method SHOW (line 252) | def SHOW(self):
    method reset (line 262) | def reset(self):
    method getBlankBoard (line 265) | def getBlankBoard(self):
    method ValidPos (line 276) | def ValidPos(self, piece1, piece2, xT=0, yT=0):
    method isNotWall (line 289) | def isNotWall(self, board, piece, xT=0 , yT=0 ):
    method gameover (line 295) | def gameover(self, location):
    method pixel (line 312) | def pixel(self, xbox, ybox):
    method DrawBox (line 315) | def DrawBox(self, xbox, ybox, color, xpixel=None, ypixel=None):
    method DrawCircle (line 339) | def DrawCircle(self,  xbox, ybox, color, xpixel=None, ypixel=None):
    method DrawPiece (line 345) | def DrawPiece(self, piece, xpixel=None, ypixel=None):
    method DrawBoard (line 353) | def DrawBoard(self, board):
    method ShowScore (line 361) | def ShowScore(self, score):
    method Terminal (line 367) | def Terminal(self, piece1, piece2, piece1_old, piece2_old):
    method Paint (line 375) | def Paint(self, board, piece, color):

FILE: examples/Social_Cognition/ToM/main_ToM.py
  function update (line 68) | def update(env, net_agent_belief, net_NPC, episodes, trajectories):
  function train (line 158) | def train():

FILE: examples/Social_Cognition/ToM/main_both.py
  function reward_plot (line 59) | def reward_plot(episodes, scores, Note):
  function update (line 72) | def update(env0, env1, net_agent, net_NPC, episodes, trajectories, task):
  function train (line 203) | def train():
  function test (line 239) | def test():

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/Find_a_way.py
  function Find_a_way (line 13) | def Find_a_way(size, board, start_x, start_y, end_x, end_y):

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/a_star.py
  class AStar (line 11) | class AStar:
    method __init__ (line 12) | def __init__(self, map):
    method BaseCost (line 17) | def BaseCost(self, p):
    method HeuristicCost (line 23) | def HeuristicCost(self, p):
    method TotalCost (line 29) | def TotalCost(self, p):
    method IsValidPoint (line 32) | def IsValidPoint(self, x, y):
    method IsInPointList (line 39) | def IsInPointList(self, p, point_list):
    method IsInOpenList (line 45) | def IsInOpenList(self, p):
    method IsInCloseList (line 48) | def IsInCloseList(self, p):
    method IsStartPoint (line 51) | def IsStartPoint(self, p, start_x, start_y):
    method IsEndPoint (line 54) | def IsEndPoint(self, p, end_x, end_y):
    method SaveImage (line 57) | def SaveImage(self, plt):
    method ProcessPoint (line 62) | def ProcessPoint(self, x, y, parent):
    method SelectPointInOpenList (line 74) | def SelectPointInOpenList(self):
    method BuildPath (line 86) | def BuildPath(self, p,  start_time, start_x, start_y, end_x, end_y):#a...
    method RunAndSaveImage (line 123) | def RunAndSaveImage(self,  start_x, start_y, end_x, end_y):#ax, plt,

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/load_statedata.py
  class StateDataset (line 11) | class StateDataset:
    method __init__ (line 13) | def __init__(self, mode, num):
    method __getitem__ (line 19) | def __getitem__(self, item):
    method __len__ (line 30) | def __len__(self):
  function get_dataloader (line 35) | def get_dataloader(mode, num, batch):

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/point.py
  class Point (line 3) | class Point:
    method __init__ (line 4) | def __init__(self, x, y):

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/random_map.py
  class RandomMap (line 5) | class RandomMap:
    method __init__ (line 6) | def __init__(self, size, board):
    method GenerateObstacle (line 12) | def GenerateObstacle(self):
    method IsObstacle (line 22) | def IsObstacle(self, i ,j):

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/statedata_pre.py
  function data_transfer (line 3) | def data_transfer(B_txt, A_txt):

FILE: examples/Social_Cognition/ToM/rulebasedpolicy/world_model.py
  function data (line 9) | def data():
  function flip180 (line 27) | def flip180(arr):
  function flip90_left (line 38) | def flip90_left(arr):
  function flip90_right (line 48) | def flip90_right(arr):
  function gain_env (line 60) | def gain_env(obs, agent, wall):
  function shelter_env (line 106) | def shelter_env(obs):
  function big_env (line 181) | def big_env(env):

FILE: examples/Social_Cognition/ToM/utils/Encoder.py
  class PopEncoder (line 9) | class PopEncoder(nn.Module):
    method __init__ (line 13) | def __init__(self, step, encode_type):
    method forward (line 19) | def forward(self, inputs, *args, **kwargs):
    method rate (line 23) | def rate(self, inputs, pop , num_state):

FILE: examples/Social_Cognition/ToM/utils/one_hot.py
  function one_hot (line 3) | def one_hot(value):

FILE: examples/Social_Cognition/affective_empathy/BAE-SNN/BAESNN.py
  class BrainArea (line 22) | class BrainArea(nn.Module, abc.ABC):
    method __init__ (line 28) | def __init__(self):
    method forward (line 34) | def forward(self, x):
    method reset (line 42) | def reset(self):
  class BAESNN (line 51) | class BAESNN(BrainArea):
    method __init__ (line 56) | def __init__(self,):
    method forward (line 113) | def forward(self, x1,x2):
    method empathy (line 126) | def empathy(self,x3):
    method UpdateWeight (line 133) | def UpdateWeight(self, i, dw, delta):
    method reset (line 143) | def reset(self):
  function BAESNN_train (line 153) | def BAESNN_train():
  function BAESNN_test (line 232) | def BAESNN_test():

FILE: examples/Social_Cognition/affective_empathy/BAE-SNN/env_poly.py
  class Maze (line 12) | class Maze(tk.Tk, object):
    method __init__ (line 13) | def __init__(self):
    method _build_maze (line 27) | def _build_maze(self):
    method reset (line 132) | def reset(self):
    method step (line 160) | def step(self, s, action, pain):
    method step_RL1 (line 377) | def step_RL1(self, action):
    method step_RL2 (line 419) | def step_RL2(self, action):
    method _set_danger (line 486) | def _set_danger(self):
    method _set_switch (line 497) | def _set_switch(self):
    method _set_wall (line 507) | def _set_wall(self):
    method generate_expression (line 526) | def generate_expression(self,pain):
    method render (line 534) | def render(self):

FILE: examples/Social_Cognition/affective_empathy/BAE-SNN/env_two_poly.py
  class Maze2 (line 13) | class Maze2(tk.Tk, object):
    method __init__ (line 14) | def __init__(self):
    method _build_maze (line 31) | def _build_maze(self):
    method reset (line 123) | def reset(self):
    method step1 (line 174) | def step1(self, action1,pain):
    method agent_help (line 398) | def agent_help(self):
    method _set_danger (line 418) | def _set_danger(self):
    method _set_wall (line 434) | def _set_wall(self):
    method generate_expression1 (line 449) | def generate_expression1(self,pain1):
    method render (line 456) | def render(self):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/BEEAD-SNN.py
  class BrainArea (line 26) | class BrainArea(nn.Module, abc.ABC):
    method __init__ (line 28) | def __init__(self):
    method forward (line 32) | def forward(self, x):
    method reset (line 39) | def reset(self):
  class BAESNN (line 46) | class BAESNN(BrainArea):
    method __init__ (line 51) | def __init__(self,):
    method forward (line 95) | def forward(self, x1,x2):
    method empathy (line 104) | def empathy(self,x3):
    method UpdateWeight (line 111) | def UpdateWeight(self, i, dw, delta):
    method reset (line 115) | def reset(self):
  class DopamineArea (line 121) | class DopamineArea(BrainArea):
    method __init__ (line 125) | def __init__(self, n_neurons, beta=0.2):
    method forward (line 131) | def forward(self, spikes):
    method reset (line 140) | def reset(self):
  function BAESNN_train (line 145) | def BAESNN_train():
  function BAESNN_train_alstruism (line 234) | def BAESNN_train_alstruism(lamda, E):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/RL_Brain.py
  class QLearningTable (line 4) | class QLearningTable:
    method __init__ (line 5) | def __init__(self, actions, learning_rate=0.1, reward_decay=0.9):
    method choose_action (line 14) | def choose_action(self, observation,e_greedy):
    method learn_A (line 35) | def learn_A(self, s, a, r, s_,done_oval):
    method A_chack_q_table_A (line 46) | def A_chack_q_table_A(self, state):
  class EnvModel (line 65) | class EnvModel:
    method __init__ (line 68) | def __init__(self, actions):
    method store_transition (line 73) | def store_transition(self, s, a, r, s_):
    method sample_s_a (line 91) | def sample_s_a(self):
    method get_r_s_ (line 96) | def get_r_s_(self, s, a):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/env.py
  class Maze2 (line 11) | class Maze2(tk.Tk, object):
    method __init__ (line 12) | def __init__(self,lamda=0):
    method _build_maze (line 30) | def _build_maze(self):
    method reset (line 151) | def reset(self):
    method step1 (line 206) | def step1(self, s1, action1,emotion):
    method is_agent1_in_danger (line 400) | def is_agent1_in_danger(self):
    method step2 (line 415) | def step2(self, action):
    method reward2 (line 462) | def reward2(self):
    method _set_wall (line 486) | def _set_wall(self):
    method generate_expression1 (line 511) | def generate_expression1(self,emotion):
    method generate_expression2 (line 520) | def generate_expression2(self,emotion):
    method render (line 529) | def render(self):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/env_poly_SNN.py
  class Maze (line 11) | class Maze(tk.Tk, object):
    method __init__ (line 12) | def __init__(self):
    method _build_maze (line 26) | def _build_maze(self):
    method reset (line 52) | def reset(self):
    method step (line 69) | def step(self, s, action, pain):
    method _set_danger (line 236) | def _set_danger(self):
    method _set_switch (line 247) | def _set_switch(self):
    method _set_wall (line 256) | def _set_wall(self):
    method generate_expression (line 273) | def generate_expression(self,pain):
    method render (line 279) | def render(self):
    method is_agent_in_danger (line 283) | def is_agent_in_danger(self):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/rsnn.py
  class RSNN (line 13) | class RSNN(nn.Module):
    method __init__ (line 14) | def __init__(self,num_state,num_action):
    method forward (line 36) | def forward(self, input):
    method UpdateWeight (line 42) | def UpdateWeight(self,reward,a,C,n):
    method reset (line 56) | def reset(self):
    method getweight (line 61) | def getweight(self):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/sd_env.py
  class Snowdrift (line 11) | class Snowdrift(tk.Tk, object):
    method __init__ (line 12) | def __init__(self, n_agents=3, n_snowdrifts=4):
    method _build_maze (line 36) | def _build_maze(self):
    method reset (line 71) | def reset(self, agent_id):
    method step_all (line 114) | def step_all(self, actions):
    method _get_state_index (line 188) | def _get_state_index(self, agent_id):
    method render (line 197) | def render(self):

FILE: examples/Social_Cognition/affective_empathy/BEEAD-SNN/snowdrift_main.py
  function encode (line 22) | def encode(n, e):
  function aoencode (line 28) | def aoencode(n, e, env, agent_id):
  function poencode (line 47) | def poencode(n, e, env, agent_id):
  function chooseAct (line 80) | def chooseAct(Net, input, explore, n, env, agent_id):
  function train_model (line 113) | def train_model(n_agents, lamdas, episodes):

FILE: examples/Social_Cognition/affective_empathy/BRP-SNN/BRP-SNN.py
  class BrainArea (line 40) | class BrainArea(nn.Module, abc.ABC):
    method __init__ (line 46) | def __init__(self):
    method forward (line 52) | def forward(self, x):
    method reset (line 60) | def reset(self):
  class BNESNN (line 69) | class BNESNN(BrainArea):
    method __init__ (line 73) | def __init__(self,):
    method forward (line 115) | def forward(self, x1,x2):
    method calculate_error (line 124) | def calculate_error(self, x1,x2):
    method UpdateWeight (line 137) | def UpdateWeight(self, i, dw, delta):
    method reset (line 147) | def reset(self):
  function GRF (line 158) | def GRF(X,N):
  function encode (line 211) | def encode(input,n_neuron):
  class BAESNN (line 225) | class BAESNN(BrainArea):
    method __init__ (line 230) | def __init__(self,):
    method forward (line 284) | def forward(self, x1,x2):
    method empathy (line 297) | def empathy(self,x3):
    method UpdateWeight (line 304) | def UpdateWeight(self, i, dw, delta):
    method reset (line 314) | def reset(self):
  function BNESNN_train (line 324) | def BNESNN_train():
  function BAESNN_train (line 345) | def BAESNN_train():
  function BAESNN_test (line 447) | def BAESNN_test():

FILE: examples/Social_Cognition/affective_empathy/BRP-SNN/env_poly_SNN.py
  class Maze (line 12) | class Maze(tk.Tk, object):
    method __init__ (line 13) | def __init__(self):
    method _build_maze (line 27) | def _build_maze(self):
    method reset (line 65) | def reset(self):
    method step (line 93) | def step(self, s, action, pain):
    method _set_danger (line 313) | def _set_danger(self):
    method _set_switch (line 324) | def _set_switch(self):
    method _set_wall (line 334) | def _set_wall(self):
    method generate_expression (line 353) | def generate_expression(self,pain):
    method render (line 361) | def render(self):

FILE: examples/Social_Cognition/affective_empathy/BRP-SNN/env_two_poly_SNN.py
  class Maze2 (line 13) | class Maze2(tk.Tk, object):
    method __init__ (line 14) | def __init__(self):
    method _build_maze (line 31) | def _build_maze(self):
    method reset (line 123) | def reset(self):
    method step (line 174) | def step(self, s, action, pain):
    method agent_help (line 412) | def agent_help(self):
    method _set_danger (line 432) | def _set_danger(self):
    method _set_wall (line 448) | def _set_wall(self):
    method generate_expression1 (line 463) | def generate_expression1(self,pain1):
    method render (line 470) | def render(self):

FILE: examples/Spiking-Transformers/LIFNode.py
  class MyBaseNode (line 10) | class MyBaseNode(BaseNode):
    method __init__ (line 11) | def __init__(self, threshold=0.5, step=4, layer_by_layer=False, mem_de...
    method rearrange2node (line 14) | def rearrange2node(self, inputs):
    method rearrange2op (line 41) | def rearrange2op(self, inputs):
  class MyGrad (line 67) | class MyGrad(SurrogateFunctionBase):
    method __init__ (line 68) | def __init__(self, alpha=4., requires_grad=False):
    method act_fun (line 72) | def act_fun(x, alpha):
  class MyNode (line 76) | class MyNode(MyBaseNode):
    method __init__ (line 77) | def __init__(self, threshold=1., step=4, layer_by_layer=True, tau=2., ...
    method integral (line 85) | def integral(self, inputs):
    method calc_spike (line 88) | def calc_spike(self):

FILE: examples/Spiking-Transformers/datasets.py
  function unpack_mix_param (line 52) | def unpack_mix_param(args):
  function build_transform (line 65) | def build_transform(is_train, img_size):
  function build_dataset (line 109) | def build_dataset(is_train, img_size, dataset, path, same_da=False):
  class MNISTData (line 135) | class MNISTData(object):
    method __init__ (line 140) | def __init__(self,
    method get_data_loaders (line 157) | def get_data_loaders(self):
    method get_standard_data (line 171) | def get_standard_data(self):
  function get_mnist_data (line 182) | def get_mnist_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_fashion_data (line 228) | def get_fashion_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_cifar10_data (line 261) | def get_cifar10_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_cifar100_data (line 305) | def get_cifar100_data(batch_size, num_workers=8, same_data=False, *args,...
  function get_imnet_data (line 348) | def get_imnet_data(args, _logger, data_config, num_aug_splits, **kwargs):
  function get_dvsg_data (line 440) | def get_dvsg_data(batch_size, step, **kwargs):
  function get_dvsc10_data (line 541) | def get_dvsc10_data(batch_size, step, **kwargs):
  function get_nmnist_data (line 663) | def get_nmnist_data(batch_size, step, **kwargs):
  function get_NCALTECH101_data (line 785) | def get_NCALTECH101_data(batch_size, step, **kwargs):
  function get_UCF101DVS_data (line 914) | def get_UCF101DVS_data(batch_size, step, **kwargs):
  function get_HMDBDVS_data (line 1020) | def get_HMDBDVS_data(batch_size, step, **kwargs):
  function get_nomni_data (line 1247) | def get_nomni_data(batch_size, train_portion=1., **kwargs):

FILE: examples/Spiking-Transformers/main.py
  function _parse_args (line 358) | def _parse_args():
  function main (line 376) | def main():
  function train_epoch (line 747) | def train_epoch(
  function validate (line 897) | def validate(epoch, model, loader, loss_fn, args, amp_autocast=suppress,

FILE: examples/Spiking-Transformers/models/spike_driven_transformer.py
  class MLP (line 21) | class MLP(BaseModule):
    method __init__ (line 23) | def __init__(self, in_features, step=10, encode_type='direct', hidden_...
    method forward (line 38) | def forward(self, x):
  class SSA (line 53) | class SSA(BaseModule):
    method __init__ (line 54) | def __init__(self, dim, step=10, encode_type='direct', num_heads=16, q...
    method forward (line 89) | def forward(self, x):
  class Block (line 128) | class Block(nn.Module):
    method __init__ (line 129) | def __init__(self, dim, num_heads, step=10, mlp_ratio=4., qkv_bias=Fal...
    method forward (line 139) | def forward(self, x):
  class SPS (line 147) | class SPS(BaseModule):
    method __init__ (line 148) | def __init__(self, step=10, encode_type='direct', img_size_h=128, img_...
    method forward (line 184) | def forward(self, x):
  class Spikformer (line 222) | class Spikformer(BaseModule):
    method __init__ (line 223) | def __init__(self, step=10, encode_type='direct',
    method _get_pos_embed (line 262) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 270) | def _init_weights(self, m):
    method forward_features (line 279) | def forward_features(self, x):
    method forward (line 292) | def forward(self, x):
  function sd_transformer (line 303) | def sd_transformer(pretrained=False, **kwargs):

FILE: examples/Spiking-Transformers/models/spike_driven_transformer_dvs.py
  class MLP (line 21) | class MLP(BaseModule):
    method __init__ (line 23) | def __init__(self, in_features, step=10, encode_type='direct', hidden_...
    method forward (line 38) | def forward(self, x):
  class SSA (line 53) | class SSA(BaseModule):
    method __init__ (line 54) | def __init__(self, dim, step=10, encode_type='direct', num_heads=16, q...
    method forward (line 89) | def forward(self, x):
  class Block (line 128) | class Block(nn.Module):
    method __init__ (line 129) | def __init__(self, dim, num_heads, step=10, mlp_ratio=4., qkv_bias=Fal...
    method forward (line 139) | def forward(self, x):
  class SPS (line 147) | class SPS(BaseModule):
    method __init__ (line 148) | def __init__(self, step=10, encode_type='direct', img_size_h=128, img_...
    method forward (line 184) | def forward(self, x):
  class Spikformer (line 222) | class Spikformer(BaseModule):
    method __init__ (line 223) | def __init__(self, step=10, encode_type='direct',
    method _get_pos_embed (line 262) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 270) | def _init_weights(self, m):
    method forward_features (line 279) | def forward_features(self, x):
    method forward (line 292) | def forward(self, x):
  function sd_transformer_dvs (line 303) | def sd_transformer_dvs(pretrained=False, **kwargs):

FILE: examples/Spiking-Transformers/models/spike_driven_transformer_v2.py
  class BNAndPadLayer (line 24) | class BNAndPadLayer(nn.Module):
    method __init__ (line 25) | def __init__(
    method forward (line 40) | def forward(self, input):
    method weight (line 62) | def weight(self):
    method bias (line 66) | def bias(self):
    method running_mean (line 70) | def running_mean(self):
    method running_var (line 74) | def running_var(self):
    method eps (line 78) | def eps(self):
  class RepConv (line 82) | class RepConv(nn.Module):
    method __init__ (line 83) | def __init__(
    method forward (line 101) | def forward(self, x):
  class SepConv (line 105) | class SepConv(BaseModule):
    method __init__ (line 110) | def __init__(
    method forward (line 138) | def forward(self, x):
  class MLP (line 149) | class MLP(BaseModule):
    method __init__ (line 151) | def __init__(self, in_features, step=10, encode_type='direct', hidden_...
    method forward (line 166) | def forward(self, x):
  class SDSA (line 187) | class SDSA(BaseModule):
    method __init__ (line 188) | def __init__(self, dim, step=10, encode_type='direct', num_heads=16, q...
    method forward (line 221) | def forward(self, x):
  class Block (line 261) | class Block(nn.Module):
    method __init__ (line 262) | def __init__(self, dim, num_heads, step=10, mlp_ratio=4., qkv_bias=Fal...
    method forward (line 272) | def forward(self, x):
  class DownSampling (line 278) | class DownSampling(BaseModule):
    method __init__ (line 279) | def __init__(
    method forward (line 307) | def forward(self, x):
  class ConvBlock (line 320) | class ConvBlock(BaseModule):
    method __init__ (line 321) | def __init__(
    method forward (line 347) | def forward(self, x):
  class Spikformer (line 359) | class Spikformer(BaseModule):
    method __init__ (line 360) | def __init__(self, step=4, encode_type='direct',
    method _get_pos_embed (line 499) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 507) | def _init_weights(self, m):
    method forward_features (line 516) | def forward_features(self, x):
    method forward (line 539) | def forward(self, x):
  function sd_transformer_v2 (line 559) | def sd_transformer_v2(pretrained=False, **kwargs):

FILE: examples/Spiking-Transformers/models/spike_driven_transformer_v2_dvs.py
  class BNAndPadLayer (line 24) | class BNAndPadLayer(nn.Module):
    method __init__ (line 25) | def __init__(
    method forward (line 40) | def forward(self, input):
    method weight (line 62) | def weight(self):
    method bias (line 66) | def bias(self):
    method running_mean (line 70) | def running_mean(self):
    method running_var (line 74) | def running_var(self):
    method eps (line 78) | def eps(self):
  class RepConv (line 82) | class RepConv(nn.Module):
    method __init__ (line 83) | def __init__(
    method forward (line 101) | def forward(self, x):
  class SepConv (line 105) | class SepConv(BaseModule):
    method __init__ (line 110) | def __init__(
    method forward (line 138) | def forward(self, x):
  class MLP (line 149) | class MLP(BaseModule):
    method __init__ (line 151) | def __init__(self, in_features, step=10, encode_type='direct', hidden_...
    method forward (line 166) | def forward(self, x):
  class SDSA (line 187) | class SDSA(BaseModule):
    method __init__ (line 188) | def __init__(self, dim, step=10, encode_type='direct', num_heads=16, q...
    method forward (line 221) | def forward(self, x):
  class Block (line 261) | class Block(nn.Module):
    method __init__ (line 262) | def __init__(self, dim, num_heads, step=10, mlp_ratio=4., qkv_bias=Fal...
    method forward (line 272) | def forward(self, x):
  class DownSampling (line 278) | class DownSampling(BaseModule):
    method __init__ (line 279) | def __init__(
    method forward (line 307) | def forward(self, x):
  class ConvBlock (line 320) | class ConvBlock(BaseModule):
    method __init__ (line 321) | def __init__(
    method forward (line 347) | def forward(self, x):
  class Spikformer (line 359) | class Spikformer(BaseModule):
    method __init__ (line 360) | def __init__(self, step=10, encode_type='direct',
    method _get_pos_embed (line 499) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 507) | def _init_weights(self, m):
    method forward_features (line 516) | def forward_features(self, x):
    method forward (line 539) | def forward(self, x):
  function sd_transformer_v2_dvs (line 559) | def sd_transformer_v2_dvs(pretrained=False, **kwargs):

FILE: examples/Spiking-Transformers/models/spikformer.py
  class MLP (line 17) | class MLP(BaseModule):
    method __init__ (line 19) | def __init__(self, in_features, step=4, encode_type='direct', hidden_f...
    method forward (line 34) | def forward(self, x):
  class SSA (line 51) | class SSA(BaseModule):
    method __init__ (line 52) | def __init__(self, dim, step=4, encode_type='rate', num_heads=12, qkv_...
    method forward (line 80) | def forward(self, x):
  class Block (line 114) | class Block(nn.Module):
    method __init__ (line 115) | def __init__(self, dim, num_heads, step =4,  mlp_ratio=4., qkv_bias=Fa...
    method forward (line 126) | def forward(self, x):
  class SPS (line 135) | class SPS(BaseModule):
    method __init__ (line 136) | def __init__(self, step=4, encode_type='direct', img_size_h=32, img_si...
    method forward (line 170) | def forward(self, x):
  class Spikformer (line 204) | class Spikformer(BaseModule):
    method __init__ (line 205) | def __init__(self, step=4, encode_type='direct',
    method _get_pos_embed (line 240) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 248) | def _init_weights(self, m):
    method forward_features (line 257) | def forward_features(self, x):
    method forward (line 267) | def forward(self, x):
  function spikformer (line 275) | def spikformer(pretrained=False, **kwargs):

FILE: examples/Spiking-Transformers/models/spikformer_dvs.py
  class MLP (line 20) | class MLP(BaseModule):
    method __init__ (line 22) | def __init__(self, in_features, step=10, encode_type='direct', hidden_...
    method forward (line 37) | def forward(self, x):
  class SSA (line 52) | class SSA(BaseModule):
    method __init__ (line 53) | def __init__(self, dim, step=10, encode_type='direct', num_heads=16, q...
    method forward (line 83) | def forward(self, x):
  class Block (line 118) | class Block(nn.Module):
    method __init__ (line 119) | def __init__(self, dim, num_heads, step=10, mlp_ratio=4., qkv_bias=Fal...
    method forward (line 129) | def forward(self, x):
  class SPS (line 137) | class SPS(BaseModule):
    method __init__ (line 138) | def __init__(self, step=10, encode_type='direct', img_size_h=128, img_...
    method forward (line 176) | def forward(self, x):
  class Spikformer (line 209) | class Spikformer(nn.Module):
    method __init__ (line 210) | def __init__(self, step=10,
    method _get_pos_embed (line 245) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 253) | def _init_weights(self, m):
    method forward_features (line 262) | def forward_features(self, x):
    method forward (line 272) | def forward(self, x):
  function spikformer_dvs (line 282) | def spikformer_dvs(pretrained=False, **kwargs):

FILE: examples/Structural_Development/DPAP/mask_model.py
  class my_cifar_model (line 20) | class my_cifar_model(BaseModule):
    method __init__ (line 21) | def __init__(self,
    method _cflatten (line 51) | def _cflatten(self):
    method _create_fc_prun (line 57) | def _create_fc_prun(self):
    method _create_fc (line 63) | def _create_fc(self):
    method forward (line 69) | def forward(self, inputs):
  class Mask (line 102) | class Mask:
    method __init__ (line 103) | def __init__(self, model,batch,step):
    method init_length (line 118) | def init_length(self):
    method get_filter_codebook (line 133) | def get_filter_codebook(self,ww,dendrite,ii,index,epoch):
    method convert2tensor (line 174) | def convert2tensor(self, x):
    method init_mask (line 178) | def init_mask(self, wwfc,convtra,epoch):
    method do_mask (line 192) | def do_mask(self):
    method if_zero (line 204) | def if_zero(self):
  class Trace (line 218) | class Trace:
    method __init__ (line 219) | def __init__(self, model,batch,step):
    method computing_trace (line 230) | def computing_trace(self,spikes):

FILE: examples/Structural_Development/DPAP/prun_main.py
  function BCM_and_trace (line 93) | def BCM_and_trace(NUM,trace,spikes,neuron_th,bcm,epoch_trace):
  function train_epoch (line 115) | def train_epoch(
  function validate (line 165) | def validate(model, loader, loss_fn, amp_autocast=suppress, log_suffix=''):

FILE: examples/Structural_Development/DPAP/utils.py
  function print_log (line 5) | def print_log(print_string, log):
  function unit (line 10) | def unit(x):
  function unit_tensor (line 25) | def unit_tensor(x):
  function init (line 38) | def init(batch,convlayer,fclayer,size,fcsize):

FILE: examples/Structural_Development/DSD-SNN/cifar100/main_simplified.py
  function _parse_args (line 191) | def _parse_args():
  function get_dataset (line 207) | def get_dataset(name, type='train', download=True, capacity=None, permut...
  function main (line 238) | def main():
  function train_epoch (line 421) | def train_epoch(
  function validate (line 522) | def validate(task, model, loader, loss_fn, args, mat,log_suffix='', visu...

FILE: examples/Structural_Development/DSD-SNN/cifar100/manipulate.py
  function permutate_image_pixels (line 5) | def permutate_image_pixels(image, permutation):
  class SubDataset (line 22) | class SubDataset(Dataset):
    method __init__ (line 28) | def __init__(self, original_dataset, sub_labels, target_transform=None):
    method __len__ (line 49) | def __len__(self):
    method __getitem__ (line 52) | def __getitem__(self, index):
  class MemorySetDataset (line 60) | class MemorySetDataset(Dataset):
    method __init__ (line 65) | def __init__(self, memory_sets, target_transform=None):
    method __len__ (line 70) | def __len__(self):
    method __getitem__ (line 76) | def __getitem__(self, index):
  class TransformedDataset (line 90) | class TransformedDataset(Dataset):
    method __init__ (line 94) | def __init__(self, original_dataset, transform=None, target_transform=...
    method __len__ (line 100) | def __len__(self):
    method __getitem__ (line 103) | def __getitem__(self, index):
  class UnNormalize (line 113) | class UnNormalize(object):
    method __init__ (line 114) | def __init__(self, mean, std):
    method __call__ (line 118) | def __call__(self, tensor):

FILE: examples/Structural_Development/DSD-SNN/cifar100/maskcl2.py
  function unit (line 7) | def unit(x):
  class Mask (line 23) | class Mask:
    method __init__ (line 24) | def __init__(self, model):
    method init_length (line 44) | def init_length(self):
    method get_filter_codebook (line 72) | def get_filter_codebook(self,index,ww,task,epoch):
    method convert2tensor (line 124) | def convert2tensor(self, x):
    method init_mask (line 128) | def init_mask(self,task,epoch):
    method do_mask (line 133) | def do_mask(self,task):
    method init_grow (line 140) | def init_grow(self,task):
    method if_zero (line 188) | def if_zero(self):
    method record (line 202) | def record(self):

FILE: examples/Structural_Development/DSD-SNN/cifar100/vgg_snn.py
  class SNN (line 22) | class SNN(BaseModule):
    method __init__ (line 23) | def __init__(self,
    method logits (line 80) | def logits(self, x):
    method _create_decision (line 87) | def _create_decision(self):
    method forward (line 92) | def forward(self, inputs, mat):

FILE: examples/Structural_Development/ELSM/evolve.py
  function _parse_args (line 37) | def _parse_args():
  class Evolve (line 44) | class Evolve(Problem):
    method __init__ (line 46) | def __init__(self, args,n_var=20, n_obj=1, n_constr=0, lb=None, ub=None):
    method _evaluate (line 54) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 100) | def do_every_generations(algorithm):

FILE: examples/Structural_Development/ELSM/lsm.py
  function lr_scheduler (line 21) | def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=50):

FILE: examples/Structural_Development/ELSM/model.py
  class nSNN (line 20) | class nSNN(BaseModule):
    method __init__ (line 21) | def __init__(self,
    method forward (line 61) | def forward(self, x):
  class mSNN (line 79) | class mSNN(BaseModule):
    method __init__ (line 80) | def __init__(self,
    method forward (line 122) | def forward(self, x):

FILE: examples/Structural_Development/ELSM/nsganet.py
  class NSGANet (line 24) | class NSGANet(GeneticAlgorithm):
    method __init__ (line 26) | def __init__(self, **kwargs):
  function binary_tournament (line 39) | def binary_tournament(pop, P, algorithm, **kwargs):
  class RankAndCrowdingSurvival (line 84) | class RankAndCrowdingSurvival(Survival):
    method __init__ (line 86) | def __init__(self) -> None:
    method _do (line 89) | def _do(self, pop, n_survive, D=None, **kwargs):
  function calc_crowding_distance (line 125) | def calc_crowding_distance(F):
  function nsganet (line 179) | def nsganet(

FILE: examples/Structural_Development/ELSM/spikes.py
  function randbool (line 21) | def randbool(size, p=0.5):
  function calc_f2 (line 24) | def calc_f2(con,device):

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/classifier.py
  class CosineClassifier (line 9) | class CosineClassifier(Module):
    method __init__ (line 10) | def __init__(self, in_features, n_classes, sigma=True):
    method reset_parameters (line 21) | def reset_parameters(self):
    method forward (line 27) | def forward(self, input):

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/imbalance.py
  class BiC (line 7) | class BiC(nn.Module):
    method __init__ (line 8) | def __init__(self, lr, scheduling, lr_decay_factor, weight_decay, batc...
    method reset (line 21) | def reset(self, lr=None, scheduling=None, lr_decay_factor=None, weight...
    method extract_preds_and_targets (line 42) | def extract_preds_and_targets(self, model, loader,taski,mask):
    method update (line 50) | def update(self, logger, task_size, model, loader, loss_criterion=None...
    method post_process (line 98) | def post_process(self, preds, task_size):
  class CR (line 108) | class CR(object):
    method __init__ (line 109) | def __init__(self):
    method update (line 113) | def update(self, classifier, task_size):
    method post_process (line 122) | def post_process(self, logits, task_size):
  class All_av (line 127) | class All_av(object):
    method __init__ (line 128) | def __init__(self):
    method update (line 132) | def update(self, classifier, task_size, classnum_list, taski):
    method post_process (line 142) | def post_process(self, logits, task_size, classnum_list, taski):

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/maskcl2.py
  function unit (line 8) | def unit(x):
  class Mask (line 24) | class Mask:
    method __init__ (line 25) | def __init__(self, model):
    method init_length (line 49) | def init_length(self,task=0,task_nn=None):
    method get_filter_reuse (line 74) | def get_filter_reuse(self,index,ww,task,epoch,c_index,cdim_before=None...
    method convert2tensor (line 106) | def convert2tensor(self, x):
    method init_mask (line 110) | def init_mask(self,task,epoch,dim_cur=None,task_nn=None,all_dist=None,...
    method do_mask (line 138) | def do_mask(self,task):
    method if_zero (line 145) | def if_zero(self):

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/network.py
  class BasicNet (line 16) | class BasicNet(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 107) | def forward(self, task,inputs,mask=None,classify=True):
    method caculate_dim (line 217) | def caculate_dim(self, x):
    method features_dim (line 232) | def features_dim(self,ntask):
    method freeze (line 238) | def freeze(self):
    method copy (line 244) | def copy(self):
    method add_classes (line 247) | def add_classes(self, n_classes,min_dist):
    method _add_classes_multi_fc (line 257) | def _add_classes_multi_fc(self, n_classes,min_dist):
    method _add_classes_single_fc (line 305) | def _add_classes_single_fc(self, n_classes):
    method _gen_classifier (line 321) | def _gen_classifier(self, in_features, n_classes):
    method resetsnn (line 335) | def resetsnn(self):

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/resnet.py
  function conv3x3 (line 20) | def conv3x3(in_planes, out_planes, stride=1):
  function conv1x1 (line 25) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 30) | class BasicBlock(nn.Module):
    method __init__ (line 33) | def __init__(self, inplanes, planes, stride=1, downsample=None, remove...
    method forward (line 44) | def forward(self, x):
  class Bottleneck (line 63) | class Bottleneck(nn.Module):
    method __init__ (line 66) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 78) | def forward(self, x):
  class ChannelAttention (line 101) | class ChannelAttention(nn.Module):
    method __init__ (line 102) | def __init__(self, in_planes, ratio=16):
    method forward (line 112) | def forward(self, x):
  class SpatialAttention (line 119) | class SpatialAttention(nn.Module):
    method __init__ (line 120) | def __init__(self, kernel_size=7):
    method forward (line 127) | def forward(self, x):
  class SEFeatureAt (line 134) | class SEFeatureAt(nn.Module):
    method __init__ (line 135) | def __init__(self, inplanes, type, at_res):
    method forward (line 150) | def forward(self, x):
  class ResNet (line 166) | class ResNet(nn.Module):
    method __init__ (line 167) | def __init__(self,
    method _make_layer (line 224) | def _make_layer(self, block, planes, blocks, remove_last_relu=False, s...
    method reset_bn (line 245) | def reset_bn(self):
    method forward (line 250) | def forward(self, x):
  function resnet18 (line 261) | def resnet18(pretrained=False, **kwargs):
  function resnet34 (line 271) | def resnet34(pretrained=False, **kwargs):
  function resnet50 (line 281) | def resnet50(pretrained=False, **kwargs):
  function resnet101 (line 291) | def resnet101(pretrained=False, **kwargs):
  function resnet152 (line 301) | def resnet152(pretrained=False, **kwargs):

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/sew_resnet.py
  function sew_function (line 31) | def sew_function(x: torch.Tensor, y: torch.Tensor, cnf:str):
  function conv3x3 (line 43) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 49) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 54) | class BasicBlock(nn.Module):
    method __init__ (line 57) | def __init__(self, inplanes, planes, planes_cur,stride=1, downsample=N...
    method forward (line 75) | def forward(self, x):
    method extra_repr (line 89) | def extra_repr(self) -> str:
  class SEWResNet (line 94) | class SEWResNet(BaseModule):
    method __init__ (line 95) | def __init__(self, block, layers, c_dim=[64,128,256,512], cdim_cur=[],...
    method _make_layer (line 161) | def _make_layer(self, block, planes, planes_cur,blocks, stride=1, dila...
    method forward_init (line 186) | def forward_init(self, inputs):
    method forward_impl (line 195) | def forward_impl(self, inputs):
  function _sew_resnet (line 205) | def _sew_resnet(arch, block, layers, c_dim,cdim_cur,pretrained, progress...
  function sew_resnet18 (line 214) | def sew_resnet18(c_dim=[64,128,256,512],cdim_cur=[],pretrained=False, pr...

FILE: examples/Structural_Development/SCA-SNN/inclearn/convnet/utils.py
  function finetune_last_layer (line 9) | def finetune_last_layer(
  function extract_features (line 84) | def extract_features(task_i,model, loader,mask=None):
  function calc_class_mean (line 98) | def calc_class_mean(network, loader, class_idx, metric):
  function update_classes_mean (line 109) | def update_classes_mean(network, inc_dataset, n_classes, task_size, shar...

FILE: examples/Structural_Development/SCA-SNN/inclearn/datasets/data.py
  function get_data_folder (line 25) | def get_data_folder(data_folder, dataset_name):
  class IncrementalDataset (line 29) | class IncrementalDataset:
    method __init__ (line 30) | def __init__(
    method n_tasks (line 96) | def n_tasks(self):
    method new_task (line 99) | def new_task(self,task_i):
    method _get_cur_step_data_for_raw_data (line 144) | def _get_cur_step_data_for_raw_data(self, task_i):
    method _setup_data (line 171) | def _setup_data(self, dataset):
    method _setup_data_for_raw_data (line 195) | def _setup_data_for_raw_data(self, dataset, train_dataset, test_datase...
    method _split_per_class (line 235) | def _split_per_class(x, y, validation_split=0.0):
    method _map_new_class_index (line 266) | def _map_new_class_index(y, order):
    method _select (line 270) | def _select(self, task_i,x, y, low_range=0, high_range=0):
    method get_datainc_loader (line 285) | def get_datainc_loader(self, mode='train'):
    method get_custom_loader_from_memory (line 290) | def get_custom_loader_from_memory(self, class_indexes, mode="test"):
    method _get_loader (line 307) | def _get_loader(self, x, y, share_memory=None, shuffle=True, mode="tra...
    method get_custom_loader (line 345) | def get_custom_loader(self, class_indexes, mode="test", data_source="t...
  class DummyDataset (line 379) | class DummyDataset(torch.utils.data.Dataset):
    method __init__ (line 380) | def __init__(self, x, y, trsf, trsf_type, share_memory_=None, dataset_...
    method __len__ (line 395) | def __len__(self):
    method __getitem__ (line 401) | def __getitem__(self, idx):

FILE: examples/Structural_Development/SCA-SNN/inclearn/datasets/dataset.py
  function get_datasets (line 13) | def get_datasets(dataset_names):
  function get_dataset (line 17) | def get_dataset(dataset_name):
  class DataHandler (line 28) | class DataHandler:
  class iCIFAR10 (line 35) | class iCIFAR10(DataHandler):
    method __init__ (line 50) | def __init__(self, data_folder, train, is_fine_label=False):
    method is_proc_inc_data (line 57) | def is_proc_inc_data(self):
    method class_order (line 61) | def class_order(cls, trial_i):
  class iCIFAR100 (line 65) | class iCIFAR100(iCIFAR10):
    method __init__ (line 92) | def __init__(self, data_folder, train, is_fine_label=False):
    method is_proc_inc_data (line 100) | def is_proc_inc_data(self):
    method class_order (line 104) | def class_order(cls, trial_i):
  class DataHandler (line 113) | class DataHandler:
  class iImageNet100 (line 120) | class iImageNet100(DataHandler):
    method __init__ (line 146) | def __init__(self, data_folder, train, is_fine_label=False):
    method is_proc_inc_data (line 158) | def is_proc_inc_data(self):
    method class_order (line 162) | def class_order(cls, trial_i):

FILE: examples/Structural_Development/SCA-SNN/inclearn/models/base.py
  class IncrementalLearner (line 11) | class IncrementalLearner(abc.ABC):
    method __init__ (line 22) | def __init__(self, *args, **kwargs):
    method set_task_info (line 26) | def set_task_info(self, task, total_n_classes, increment, n_train_data...
    method before_task (line 35) | def before_task(self, taski, inc_dataset,mask,min_dist,all_dist):
    method train_task (line 40) | def train_task(self, task_i,train_loader, val_loader,mask,min_dist,all...
    method after_task (line 45) | def after_task(self, taski, inc_dataset,mask):
    method eval_task (line 50) | def eval_task(self, task_i,data_loader,mask):
    method get_memory (line 55) | def get_memory(self):
    method eval (line 58) | def eval(self):
    method train (line 61) | def train(self):
    method _before_task (line 64) | def _before_task(self, data_loader):
    method _train_task (line 67) | def _train_task(self, train_loader, val_loader):
    method _after_task (line 70) | def _after_task(self, data_loader):
    method _eval_task (line 73) | def _eval_task(self, data_loader):
    method _new_task_index (line 77) | def _new_task_index(self):
    method _memory_per_class (line 81) | def _memory_per_class(self):
    method _after_epoch (line 85) | def _after_epoch(self, epoch, avg_loss, train_new_accu, train_old_accu...
    method _validation (line 105) | def _validation(self, val_loader, epoch):

FILE: examples/Structural_Development/SCA-SNN/inclearn/models/incmodel.py
  class IncModel (line 30) | class IncModel(IncrementalLearner):
    method __init__ (line 31) | def __init__(self, cfg, trial_i, _run, ex, tensorboard, inc_dataset):
    method eval (line 107) | def eval(self):
    method train (line 110) | def train(self):
    method _before_task (line 120) | def _before_task(self, taski, inc_dataset,mask,min_dist,all_dist):
    method set_optimizer (line 140) | def set_optimizer(self, lr=None):
    method _train_task (line 173) | def _train_task(self, task_i,train_loader, val_loader,mask,min_dist,al...
    method _forward_loss (line 287) | def _forward_loss(self, task_i,inputs, targets, old_classes, new_class...
    method cross_entropy (line 295) | def cross_entropy(self, outputs, targets, exp=1.0, size_average=True, ...
    method hcl (line 311) | def hcl(self, fstudent, fteacher, targets):
    method _compute_loss (line 365) | def _compute_loss(self, task_i, inputs, targets, outputs, old_classes,...
    method _after_task (line 427) | def _after_task(self, taski, inc_dataset,mask=None):
    method _eval_task (line 471) | def _eval_task(self,task_i, data_loader,mask):
    method _compute_accuracy_by_netout (line 494) | def _compute_accuracy_by_netout(self, task_i,data_loader,mask):
    method _compute_accuracy_by_ncm (line 530) | def _compute_accuracy_by_ncm(self, loader):
    method _update_postprocessor (line 543) | def _update_postprocessor(self, taski,inc_dataset,mask=None):
    method update_prototype (line 572) | def update_prototype(self):
    method build_exemplars (line 584) | def build_exemplars(self, task_i,inc_dataset, coreset_strategy,mask=No...
    method validate (line 623) | def validate(self, data_loader):
    method after_prune (line 631) | def after_prune(self, taski, inc_dataset):
  class DistillKL (line 651) | class DistillKL(nn.Module):
    method __init__ (line 653) | def __init__(self, T):
    method forward (line 657) | def forward(self, y_s, y_t):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/autoaugment_extra.py
  class ImageNetPolicy (line 6) | class ImageNetPolicy(object):
    method __init__ (line 17) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 165) | def __call__(self, img):
    method __repr__ (line 169) | def __repr__(self):
  class SubPolicy (line 173) | class SubPolicy(object):
    method __init__ (line 174) | def __init__(self, p1, operation1, magnitude_idx1, p2, operation2, mag...
    method __call__ (line 276) | def __call__(self, img):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/cutout.py
  class Cutout (line 4) | class Cutout(object):
    method __init__ (line 10) | def __init__(self, n_holes, length):
    method __call__ (line 14) | def __call__(self, img):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/data_utils.py
  function construct_balanced_subset (line 4) | def construct_balanced_subset(x, y):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/factory.py
  function get_optimizer (line 11) | def get_optimizer(params, optimizer, lr, weight_decay=0.0):
  function get_attention (line 19) | def get_attention(inplane, type, at_res):
  function get_convnet (line 22) | def get_convnet(convnet_type, c_dim=None,cdim_cur=None,**kwargs):
  function get_model (line 30) | def get_model(cfg, trial_i, _run, ex, tensorboard, inc_dataset):
  function get_data (line 37) | def get_data(cfg, trial_i):
  function set_device (line 54) | def set_device(cfg):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/memory.py
  class MemorySize (line 10) | class MemorySize:
    method __init__ (line 11) | def __init__(self, mode, inc_dataset, total_memory=None, fixed_memory_...
    method update_n_classes (line 20) | def update_n_classes(self, n_classes):
    method update_memory_per_cls_uniform (line 23) | def update_memory_per_cls_uniform(self, n_classes):
    method update_memory_per_cls (line 30) | def update_memory_per_cls(self, network, n_classes, task_size):
    method memsize (line 38) | def memsize(self):
  function compute_examplar_mean (line 45) | def compute_examplar_mean(feat_norm, feat_flip, herding_mat, nb_max):
  function select_examplars (line 65) | def select_examplars(features, nb_max):
  function random_selection (line 92) | def random_selection(n_classes, task_size, network, logger, inc_dataset,...
  function herding (line 112) | def herding(task_i,n_classes, task_size, network, herding_matrix, inc_da...

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/metrics.py
  class IncConfusionMeter (line 7) | class IncConfusionMeter:
    method __init__ (line 17) | def __init__(self, k, increments, normalized=False):
    method reset (line 25) | def reset(self):
    method add (line 28) | def add(self, predicted, target):
    method value (line 75) | def value(self):
  class ClassErrorMeter (line 99) | class ClassErrorMeter:
    method __init__ (line 100) | def __init__(self, topk=[1], accuracy=False):
    method reset (line 106) | def reset(self):
    method add (line 110) | def add(self, output, target):
    method value (line 143) | def value(self, k=-1):
  class AverageValueMeter (line 157) | class AverageValueMeter:
    method __init__ (line 158) | def __init__(self):
    method add (line 163) | def add(self, value, n=1):
    method value (line 181) | def value(self):
    method reset (line 184) | def reset(self):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/results_utils.py
  function get_template_results (line 12) | def get_template_results(cfg):
  function save_results (line 16) | def save_results(results, label):
  function compute_avg_inc_acc (line 28) | def compute_avg_inc_acc(results):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/scheduler.py
  class ConstantTaskLR (line 6) | class ConstantTaskLR:
    method __init__ (line 7) | def __init__(self, lr):
    method get_lr (line 10) | def get_lr(self, task_i):
  class CosineAnnealTaskLR (line 14) | class CosineAnnealTaskLR:
    method __init__ (line 15) | def __init__(self, lr_max, lr_min, task_max):
    method get_lr (line 20) | def get_lr(self, task_i):
  class GradualWarmupScheduler (line 24) | class GradualWarmupScheduler(_LRScheduler):
    method __init__ (line 34) | def __init__(self, optimizer, multiplier, total_epoch, after_scheduler...
    method get_lr (line 43) | def get_lr(self):
    method step_ReduceLROnPlateau (line 60) | def step_ReduceLROnPlateau(self, metrics, epoch=None):
    method step (line 77) | def step(self, epoch=None, metrics=None):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/similar.py
  class Appr (line 9) | class Appr(object):
    method __init__ (line 11) | def __init__(self, pretrained_feat_extractor, num_task, torc,device='c...
    method get_mean_cov_feats (line 29) | def get_mean_cov_feats(self,  taski, data, device):
    method after_get_mean_cov_feats (line 79) | def after_get_mean_cov_feats(self, taski, data, device):
    method add_mean_cov (line 120) | def add_mean_cov(self, taski,mean, cov=None):
    method task_relatedness_knnkl (line 124) | def task_relatedness_knnkl(self, task_id, p_task_id, all_feats):
    method get_relatedness (line 172) | def get_relatedness(self, task_id, feats):
    method strategy (line 191) | def strategy(self, task_id, num_train_samples):
    method learn (line 236) | def learn(self, task_id, valid_data, batch_size,device):
    method after_learn (line 264) | def after_learn(self, task_id, valid_data, batch_size,device):
  class ResNet_FE (line 275) | class ResNet_FE(nn.Module):
    method __init__ (line 280) | def __init__(self, resnet_model):
    method forward (line 286) | def forward(self, x):
  function get_pretrained_feat_extractor (line 289) | def get_pretrained_feat_extractor(name):
  function gaussian_mean_cov (line 301) | def gaussian_mean_cov(X):

FILE: examples/Structural_Development/SCA-SNN/inclearn/tools/utils.py
  function get_date (line 12) | def get_date():
  function to_onehot (line 16) | def to_onehot(targets, n_classes):
  function get_class_loss (line 24) | def get_class_loss(network, cur_n_cls, loader):
  function get_featnorm_grouped_by_class (line 41) | def get_featnorm_grouped_by_class(task_i,network, cur_n_cls, loader,m=No...
  function set_seed (line 64) | def set_seed(seed):
  function display_weight_norm (line 74) | def display_weight_norm(logger, network, increments, tag):
  function display_feature_norm (line 93) | def display_feature_norm(task_i,logger, network, loader, n_classes, incr...
  function check_loss (line 112) | def check_loss(loss):
  function class2task (line 115) | def class2task(class_form, classnum):
  function maskclass (line 123) | def maskclass(pred, target, classnum, type='new'):
  function compute_old_new_mix (line 163) | def compute_old_new_mix(ypred, ytrue, increments, n_classes, task_order):
  function compute_task_accuracy (line 196) | def compute_task_accuracy(ypred, ytrue, increments, n_classes, task_order):
  function compute_accuracy (line 208) | def compute_accuracy(ypred, ytrue, increments, n_classes):
  function make_logger (line 248) | def make_logger(log_name, savedir='.logs/'):

FILE: examples/Structural_Development/SCA-SNN/main.py
  function initialization (line 36) | def initialization(config, seed, mode, exp_id):
  function train (line 61) | def train(_run, _rnd, _seed):
  function _train (line 71) | def _train(cfg, _run, ex, tensorboard):

FILE: examples/Structural_Development/SD-SNN/main.py
  function train_epoch (line 90) | def train_epoch(
  function validate (line 138) | def validate(model, loader, loss_fn, amp_autocast=suppress, log_suffix=''):

FILE: examples/Structural_Development/SD-SNN/prun_and_generation.py
  class Mask (line 7) | class Mask:
    method __init__ (line 8) | def __init__(self, model,count_thre):
    method convert2tensor (line 58) | def convert2tensor(self, x):
    method init_length (line 62) | def init_length(self):
    method init_mask_dsd (line 110) | def init_mask_dsd(self):
    method get_range_weight (line 120) | def get_range_weight(self, weight_torch, length, i, count_thre):
    method do_mask_dsd (line 183) | def do_mask_dsd(self):
    method do_pruning_dsd (line 198) | def do_pruning_dsd(self,epoch):
    method cal_prune (line 238) | def cal_prune(self,index,epoch):
    method do_growth_ww (line 262) | def do_growth_ww(self,epoch):
    method if_zero (line 319) | def if_zero(self):

FILE: examples/Structural_Development/SD-SNN/snn_model.py
  class my_cifar_model (line 13) | class my_cifar_model(BaseModule):
    method __init__ (line 14) | def __init__(self,
    method _cflatten (line 42) | def _cflatten(self):
    method _create_fc_prun (line 48) | def _create_fc_prun(self):
    method _create_fc (line 54) | def _create_fc(self):
    method forward (line 60) | def forward(self, inputs):

FILE: examples/Structural_Development/SD-SNN/utils.py
  function unit (line 5) | def unit(x):
  function unit_tensor (line 19) | def unit_tensor(x):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/brid.py
  function randbool (line 25) | def randbool(size, p):
  class Evolve (line 28) | class Evolve(Problem):
    method __init__ (line 30) | def __init__(self, n_var=20, n_obj=1, n_constr=0, lb=None, ub=None):
    method _evaluate (line 37) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 54) | def do_every_generations(algorithm):
  function load_images (line 68) | def load_images():
  class Bird (line 90) | class Bird(pygame.sprite.Sprite):
    method __init__ (line 103) | def __init__(self, x, y, msec_to_climb, images):
    method update (line 111) | def update(self, action, state, delta_frames=1):
    method sink (line 130) | def sink(self, delta_frames=1):
    method image (line 134) | def image(self):
    method mask (line 141) | def mask(self):
    method rect (line 148) | def rect(self):
  class PipePair (line 152) | class PipePair(pygame.sprite.Sprite):
    method __init__ (line 162) | def __init__(self, pipe_end_img, pipe_body_img):
    method top_height_px (line 205) | def top_height_px(self):
    method bottom_height_px (line 209) | def bottom_height_px(self):
    method visible (line 213) | def visible(self):
    method rect (line 217) | def rect(self):
    method update (line 220) | def update(self, delta_frames=1):
    method collides_with (line 223) | def collides_with(self, bird):
  function judgeState (line 227) | def judgeState(bird, pipes, collide):
  function blankState (line 278) | def blankState(bird, center):
  function getReward (line 305) | def getReward(state, lastState, smallerError, isNewPipe):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/lsmmodel.py
  class SNN (line 20) | class SNN(BaseModule):
    method __init__ (line 21) | def __init__(self,
    method forward (line 64) | def forward(self, x):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/maze.py
  function randbool (line 20) | def randbool(size, p):
  class Evolve (line 23) | class Evolve(Problem):
    method __init__ (line 25) | def __init__(self, n_var=20, n_obj=1, n_constr=0, lb=None, ub=None):
    method _evaluate (line 32) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 48) | def do_every_generations(algorithm):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/tools/EnuGlobalNetwork.py
  class EnuGlobalNetwork (line 17) | class EnuGlobalNetwork(AbstractLayerBMM):
    method __init__ (line 20) | def __init__(self, n_offspring, n_pseudo_env, n_input_neurons, n_hidde...
    method dump_model (line 140) | def dump_model(self, e, exp_name):
    method restore_model (line 148) | def restore_model(self, e, exp_name):
    method plot_weights (line 161) | def plot_weights(e, exp_name):
    method dump_network_activity (line 192) | def dump_network_activity(self, e, exp_name):
    method print (line 197) | def print(self):
    method reset (line 203) | def reset(self):
    method forward (line 210) | def forward(self, X):
    method _track_vis_data (line 244) | def _track_vis_data(self, X, input_to_synapses_connected, input_to_neu...
    method plot_network_activity (line 250) | def plot_network_activity(e, exp_name):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/tools/ExperimentEnvGlobalNetworkSurvival.py
  class ExperimentEnvGlobalNetworkSurvival (line 8) | class ExperimentEnvGlobalNetworkSurvival:
    method __init__ (line 13) | def __init__(self, env, exp_name='maze'):
    method _convert_obs (line 21) | def _convert_obs(self, obs, rewards):
    method _convert_reward (line 33) | def _convert_reward(self, obs, actions, rewards, infos, dones):
    method step (line 42) | def step(self, y):
    method reset (line 64) | def reset(self):
    method render (line 78) | def render(self):
    method track_vis_data (line 82) | def track_vis_data(self, vis_data, model, X, y_est, t):
    method dump_vis_data (line 87) | def dump_vis_data(self, vis_data, fitness_per_offspring, e):
    method load_vis_data (line 92) | def load_vis_data(e, exp_name):
    method plot_vis_data (line 98) | def plot_vis_data(e, exp_name):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/tools/MazeTurnEnvVec.py
  class MazeTurnEnvVec (line 11) | class MazeTurnEnvVec:
    method __init__ (line 15) | def __init__(self, n_agents, n_steps):
    method step (line 33) | def step(self, actions):
    method _reset_pos (line 98) | def _reset_pos(self, idxs):
    method _reset_pos_pois (line 106) | def _reset_pos_pois(self, idxs):
    method _reset_food (line 111) | def _reset_food(self, idxs, prob=0.5):
    method reset (line 124) | def reset(self):
    method _get_obs_from_pos (line 167) | def _get_obs_from_pos(self):
    method render (line 209) | def render(self):
    method load_vis_data (line 247) | def load_vis_data(e, exp_name):
    method plot_vis_data (line 253) | def plot_vis_data(e, exp_name):
    method plot_rollout_data (line 302) | def plot_rollout_data(e, exp_name):

FILE: examples/Structure_Evolution/Adaptive_lsm/BrainCog-Version/tools/nsganet.py
  class NSGANet (line 24) | class NSGANet(GeneticAlgorithm):
    method __init__ (line 26) | def __init__(self, **kwargs):
  function binary_tournament (line 39) | def binary_tournament(pop, P, algorithm, **kwargs):
  class RankAndCrowdingSurvival (line 84) | class RankAndCrowdingSurvival(Survival):
    method __init__ (line 86) | def __init__(self) -> None:
    method _do (line 89) | def _do(self, pop, n_survive, D=None, **kwargs):
  function calc_crowding_distance (line 125) | def calc_crowding_distance(F):
  function nsganet (line 179) | def nsganet(

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/BCM.py
  function randbool (line 47) | def randbool(size, p):
  function fit (line 51) | def fit(agent):
  class SNN (line 68) | class SNN(BaseModule):
    method __init__ (line 69) | def __init__(self,
    method forward (line 108) | def forward(self, x):
  class REINFORCE (line 125) | class REINFORCE:
    method __init__ (line 126) | def __init__(self, lm):
    method select_action (line 131) | def select_action(self, state):
  class Evolve (line 143) | class Evolve(Problem):
    method __init__ (line 145) | def __init__(self, n_var=20, n_obj=1, n_constr=0, lb=None, ub=None):
    method _evaluate (line 152) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 196) | def do_every_generations(algorithm):

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/lstm.py
  class Policy (line 41) | class Policy(nn.Module):
    method __init__ (line 42) | def __init__(self, hidden_size, s_dim, a_dim):
    method forward (line 49) | def forward(self, x,hidden):
  class REINFORCE (line 55) | class REINFORCE:
    method __init__ (line 56) | def __init__(self, hidden_size, s_dim, a_dim):
    method select_action (line 63) | def select_action(self, state,hx,cx):
    method update_parameters (line 74) | def update_parameters(self, rewards, log_probs, entropies, gamma):# 更新参数

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/main.py
  class Policy (line 40) | class Policy(nn.Module):
    method __init__ (line 41) | def __init__(self, hidden_size, s_dim, a_dim):
    method forward (line 48) | def forward(self, x):
  class REINFORCE (line 53) | class REINFORCE:
    method __init__ (line 54) | def __init__(self, hidden_size, s_dim, a_dim):
    method select_action (line 62) | def select_action(self, state):
    method update_parameters (line 73) | def update_parameters(self, rewards, log_probs, entropies, gamma):

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/q_l.py
  class Agent (line 11) | class Agent(object):
    method __init__ (line 16) | def __init__(self, env,alpha=0.1, gamma=0.9):
    method choose_action (line 25) | def choose_action(self,state,epsilon=0.8):
    method update_q_value (line 40) | def update_q_value(self, state, action, next_state_reward, next_state_...
    method add_state (line 44) | def add_state(self,X_next):
    method learn (line 51) | def learn(self, env, episode=100, epsilon=0.8):
    method play (line 73) | def play(self, env):
  function QQ (line 108) | def QQ():

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/tools/EnuGlobalNetwork.py
  class EnuGlobalNetwork (line 17) | class EnuGlobalNetwork(AbstractLayerBMM):
    method __init__ (line 20) | def __init__(self, n_offspring, n_pseudo_env, n_input_neurons, n_hidde...
    method dump_model (line 140) | def dump_model(self, e, exp_name):
    method restore_model (line 148) | def restore_model(self, e, exp_name):
    method plot_weights (line 161) | def plot_weights(e, exp_name):
    method dump_network_activity (line 192) | def dump_network_activity(self, e, exp_name):
    method print (line 197) | def print(self):
    method reset (line 203) | def reset(self):
    method forward (line 210) | def forward(self, X):
    method _track_vis_data (line 244) | def _track_vis_data(self, X, input_to_synapses_connected, input_to_neu...
    method plot_network_activity (line 250) | def plot_network_activity(e, exp_name):

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/tools/ExperimentEnvGlobalNetworkSurvival.py
  class ExperimentEnvGlobalNetworkSurvival (line 8) | class ExperimentEnvGlobalNetworkSurvival:
    method __init__ (line 13) | def __init__(self, env, exp_name='maze'):
    method _convert_obs (line 21) | def _convert_obs(self, obs, rewards):
    method _convert_reward (line 33) | def _convert_reward(self, obs, actions, rewards, infos, dones):
    method step (line 42) | def step(self, y):
    method reset (line 64) | def reset(self):
    method render (line 78) | def render(self):
    method track_vis_data (line 82) | def track_vis_data(self, vis_data, model, X, y_est, t):
    method dump_vis_data (line 87) | def dump_vis_data(self, vis_data, fitness_per_offspring, e):
    method load_vis_data (line 92) | def load_vis_data(e, exp_name):
    method plot_vis_data (line 98) | def plot_vis_data(e, exp_name):

FILE: examples/Structure_Evolution/Adaptive_lsm/raw/tools/MazeTurnEnvVec.py
  class MazeTurnEnvVec (line 11) | class MazeTurnEnvVec:
    method __init__ (line 15) | def __init__(self, n_agents, n_steps):
    method step (line 33) | def step(self, actions):
    method _reset_pos (line 98) | def _reset_pos(self, idxs):
    method _reset_pos_pois (line 106) | def _reset_pos_pois(self, idxs):
    method _reset_food (line 111) | def _reset_food(self, idxs, prob=0.5):
    method reset (line 124) | def reset(self):
    method _get_obs_from_pos (line 167) | def _get_obs_from_pos(self):
    method render (line 209) | def render(self):
    method load_vis_data (line 247) | def load_vis_data(e, exp_name):
    method plot_vis_data (line 253) | def plot_vis_data(e, exp_name):
    method plot_rollout_data (line 302) | def plot_rollout_data(e, exp_name):

FILE: examples/Structure_Evolution/EB-NAS/acc_predictor/adaptive_switching.py
  class AdaptiveSwitching (line 6) | class AdaptiveSwitching:
    method __init__ (line 9) | def __init__(self, n_fold=10):
    method fit (line 17) | def fit(self, train_data, train_target):
    method _n_fold_validation (line 22) | def _n_fold_validation(self, train_data, train_target, n=10):
    method predict (line 56) | def predict(self, test_data):

FILE: examples/Structure_Evolution/EB-NAS/acc_predictor/carts.py
  class CART (line 8) | class CART:
    method __init__ (line 10) | def __init__(self, n_tree=1000):
    method _make_decision_trees (line 16) | def _make_decision_trees(train_data, train_label, n_tree):
    method fit (line 38) | def fit(self, train_data, train_label):
    method predict (line 41) | def predict(self, test_data):

FILE: examples/Structure_Evolution/EB-NAS/acc_predictor/factory.py
  function get_acc_predictor (line 1) | def get_acc_predictor(model, inputs, targets):

FILE: examples/Structure_Evolution/EB-NAS/acc_predictor/gp.py
  class GP (line 6) | class GP:
    method __init__ (line 8) | def __init__(self, regr='linear', corr='gauss'):
    method fit (line 14) | def fit(self, train_data, train_label):
    method predict (line 43) | def predict(self, test_data):

FILE: examples/Structure_Evolution/EB-NAS/acc_predictor/mlp.py
  class Net (line 8) | class Net(nn.Module):
    method __init__ (line 10) | def __init__(self, n_feature, n_layers=2, n_hidden=300, n_output=1, dr...
    method forward (line 24) | def forward(self, x):
    method init_weights (line 32) | def init_weights(m):
  class MLP (line 40) | class MLP:
    method __init__ (line 42) | def __init__(self, **kwargs):
    method fit (line 46) | def fit(self, **kwargs):
    method predict (line 49) | def predict(self, test_data, device='cpu'):
  function train (line 53) | def train(net, x, y, trn_split=0.8, pretrained=None, device='cpu',
  function train_one_epoch (line 104) | def train_one_epoch(net, data, target, criterion, optimizer, device):
  function infer (line 117) | def infer(net, data, target, criterion, device):
  function validate (line 128) | def validate(net, data, target, device):
  function predict (line 142) | def predict(net, query, device):

FILE: examples/Structure_Evolution/EB-NAS/acc_predictor/rbf.py
  class RBF (line 4) | class RBF:
    method __init__ (line 7) | def __init__(self, kernel='cubic', tail='linear'):
    method fit (line 13) | def fit(self, train_data, train_label):
    method predict (line 33) | def predict(self, test_data):

FILE: examples/Structure_Evolution/EB-NAS/cellmodel.py
  class EvoCell2 (line 15) | class EvoCell2(nn.Module):
    method __init__ (line 16) | def __init__(self,motif, C_prev_prev, C_prev, C, reduction, reduction_...
    method _compile (line 41) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 74) | def forward(self, s0, s1, drop_prob):
  class EvoCell3 (line 115) | class EvoCell3(nn.Module):
    method __init__ (line 116) | def __init__(self,motif, C_prev_prev_prev, C_prev_prev, C_prev, C, red...
    method _compile (line 149) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 182) | def forward(self, s0, s1, s2, drop_prob):
  class EvoCell4 (line 230) | class EvoCell4(nn.Module):
    method __init__ (line 231) | def __init__(self,motif, C_prev_prev_prev_prev,C_prev_prev_prev, C_pre...
    method _compile (line 277) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 310) | def forward(self, s0, s1, s2, s3, drop_prob):
  class NetworkCIFAR (line 371) | class NetworkCIFAR(BaseModule):
    method __init__ (line 373) | def __init__(self,
    method forward (line 492) | def forward(self, inputs):
  class NetworkCIFAR_ (line 563) | class NetworkCIFAR_(BaseModule):
    method __init__ (line 565) | def __init__(self,
    method forward (line 660) | def forward(self, inputs):
  function occumpy_mem (line 735) | def occumpy_mem(cuda_device):

FILE: examples/Structure_Evolution/EB-NAS/ebnas.py
  class NAS (line 368) | class NAS(Problem):
    method __init__ (line 370) | def __init__(self, args,n_var=20, n_obj=1, n_constr=0, lb=None, ub=None,
    method _evaluate (line 379) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 403) | def do_every_generations(algorithm):
  function _parse_args (line 418) | def _parse_args():

FILE: examples/Structure_Evolution/EB-NAS/micro_encoding.py
  function convert_cell (line 82) | def convert_cell(cell_bit_string):
  function filt (line 87) | def filt(sn):
  function shuffle_along_axis (line 100) | def shuffle_along_axis(a, axis):
  function sample (line 104) | def sample(pops, layers, bits , ):
  function reencode (line 125) | def reencode(sn,bigmotifs,pops):
  function convert (line 132) | def convert(mgenome, layers, bits):
  function convert_single (line 141) | def convert_single(mgenome, layers, bits):
  function c_single (line 149) | def c_single(mgenome, layers, bits):
  function decode (line 173) | def decode(genome):
  function decode_motif (line 198) | def decode_motif(layers,bits,genome):
  function compare_cell (line 232) | def compare_cell(cell_string1, cell_string2):
  function compare (line 248) | def compare(string1, string2):

FILE: examples/Structure_Evolution/EB-NAS/nsganet.py
  class NSGANet (line 23) | class NSGANet(GeneticAlgorithm):
    method __init__ (line 25) | def __init__(self, **kwargs):
  function binary_tournament (line 38) | def binary_tournament(pop, P, algorithm, **kwargs):
  class RankAndCrowdingSurvival (line 83) | class RankAndCrowdingSurvival(Survival):
    method __init__ (line 85) | def __init__(self) -> None:
    method _do (line 88) | def _do(self, pop, n_survive, D=None, **kwargs):
  function calc_crowding_distance (line 124) | def calc_crowding_distance(F):
  function nsganet (line 178) | def nsganet(

FILE: examples/Structure_Evolution/EB-NAS/operations.py
  function si_relu (line 15) | def si_relu(x, positive):
  class SiReLU (line 27) | class SiReLU(nn.Module):
    method __init__ (line 28) | def __init__(self, positive=0):
    method forward (line 32) | def forward(self, x):
  function weight_init (line 36) | def weight_init(m):
  class SiMLP (line 157) | class SiMLP(nn.Module):
    method __init__ (line 158) | def __init__(self, c_in, c_out, act_fun=nn.ReLU, positive=0, *args, **...
    method forward (line 166) | def forward(self, x):
  class DilConv (line 173) | class DilConv(nn.Module):
    method __init__ (line 178) | def __init__(self, C_in, C_out, kernel_size, stride, padding, dilation...
    method forward (line 192) | def forward(self, x):
  class SepConv (line 197) | class SepConv(nn.Module):
    method __init__ (line 199) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 218) | def forward(self, x):
  class Identity (line 223) | class Identity(nn.Module):
    method __init__ (line 225) | def __init__(self, positive=0):
    method forward (line 229) | def forward(self, x):
  class Zero (line 233) | class Zero(nn.Module):
    method __init__ (line 235) | def __init__(self, stride):
    method forward (line 239) | def forward(self, x):
  class FactorizedReduce (line 245) | class FactorizedReduce(nn.Module):
    method __init__ (line 247) | def __init__(self, C_in, C_out, affine=True, act_fun=nn.ReLU, positive...
    method forward (line 259) | def forward(self, x):
  class F0 (line 267) | class F0(nn.Module):
    method __init__ (line 269) | def __init__(self, C_in, C_out, affine=True, act_fun=nn.ReLU, positive...
    method forward (line 282) | def forward(self, x):
  class F1 (line 291) | class F1(nn.Module):
    method __init__ (line 293) | def __init__(self, C_in, C_out, affine=True, act_fun=nn.ReLU, positive...
    method forward (line 306) | def forward(self, x):
  class ReLUConvBN (line 315) | class ReLUConvBN(nn.Module):
    method __init__ (line 320) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 333) | def forward(self, x):
  class Attention (line 357) | class Attention(Module):
    method __init__ (line 362) | def __init__(self, dim, num_heads=4, attention_dropout=0.1, projection...
    method forward (line 373) | def forward(self, x):
  class TransformerEncoderLayer (line 389) | class TransformerEncoderLayer(Module):
    method __init__ (line 395) | def __init__(self, d_model, nhead=4, dim_feedforward=256, dropout=0.1,
    method forward (line 413) | def forward(self, src: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  function drop_path (line 426) | def drop_path(x, drop_prob: float = 0., training: bool = False):
  class DropPath (line 448) | class DropPath(Module):
    method __init__ (line 454) | def __init__(self, drop_prob=None):
    method forward (line 458) | def forward(self, x):

FILE: examples/Structure_Evolution/EB-NAS/single_genome.py
  function _parse_args (line 353) | def _parse_args():

FILE: examples/Structure_Evolution/EB-NAS/tm.py
  function train_motifs (line 43) | def train_motifs(args,gen,arch_dir,genome,_logger,args_text,devices,ms,g...
  function train_epoch (line 417) | def train_epoch(
  function validate (line 615) | def validate(epoch, model, loader, loss_fn, args, arch_dir,_logger,amp_a...
  function get_net_info (line 810) | def get_net_info(args, gen,genome,ms):

FILE: examples/Structure_Evolution/ELSM/evolve.py
  function _parse_args (line 40) | def _parse_args():
  function calc_f1 (line 45) | def calc_f1(dirs):
  function mul_f1 (line 60) | def mul_f1(pop,steps,rootdir):
  class Evolve (line 72) | class Evolve(Problem):
    method __init__ (line 74) | def __init__(self, args,n_var=20, n_obj=1, n_constr=0, lb=None, ub=None):
    method _evaluate (line 82) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 128) | def do_every_generations(algorithm):

FILE: examples/Structure_Evolution/ELSM/lsm.py
  function lr_scheduler (line 21) | def lr_scheduler(optimizer, epoch, init_lr=0.1, lr_decay_epoch=50):
  class LabelSmoothingBCEWithLogitsLoss (line 59) | class LabelSmoothingBCEWithLogitsLoss(nn.Module):
    method __init__ (line 61) | def __init__(self, smoothing=0.1):
    method forward (line 72) | def forward(self, x, target):

FILE: examples/Structure_Evolution/ELSM/model.py
  class nSNN (line 20) | class nSNN(BaseModule):
    method __init__ (line 21) | def __init__(self,
    method forward (line 61) | def forward(self, x):
  class mSNN (line 79) | class mSNN(BaseModule):
    method __init__ (line 80) | def __init__(self,
    method forward (line 122) | def forward(self, x):

FILE: examples/Structure_Evolution/ELSM/nsganet.py
  class NSGANet (line 24) | class NSGANet(GeneticAlgorithm):
    method __init__ (line 26) | def __init__(self, **kwargs):
  function binary_tournament (line 39) | def binary_tournament(pop, P, algorithm, **kwargs):
  class RankAndCrowdingSurvival (line 84) | class RankAndCrowdingSurvival(Survival):
    method __init__ (line 86) | def __init__(self) -> None:
    method _do (line 89) | def _do(self, pop, n_survive, D=None, **kwargs):
  function calc_crowding_distance (line 125) | def calc_crowding_distance(F):
  function nsganet (line 179) | def nsganet(

FILE: examples/Structure_Evolution/ELSM/spikes.py
  function randbool (line 21) | def randbool(size, p=0.5):
  function calc_f2 (line 24) | def calc_f2(con,device):

FILE: examples/Structure_Evolution/MSE-NAS/auto_augment.py
  class ImageNetPolicy (line 14) | class ImageNetPolicy(object):
    method __init__ (line 28) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 60) | def __call__(self, img):
    method __repr__ (line 64) | def __repr__(self):
  class CIFAR10Policy (line 68) | class CIFAR10Policy(object):
    method __init__ (line 82) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 114) | def __call__(self, img):
    method __repr__ (line 118) | def __repr__(self):
  class SVHNPolicy (line 122) | class SVHNPolicy(object):
    method __init__ (line 136) | def __init__(self, fillcolor=(128, 128, 128)):
    method __call__ (line 168) | def __call__(self, img):
    method __repr__ (line 172) | def __repr__(self):
  class SubPolicy (line 176) | class SubPolicy(object):
    method __init__ (line 178) | def __init__(self,
    method __call__ (line 269) | def __call__(self, img):

FILE: examples/Structure_Evolution/MSE-NAS/cellmodel.py
  class EvoCell2 (line 15) | class EvoCell2(nn.Module):
    method __init__ (line 16) | def __init__(self,motif, C_prev_prev, C_prev, C, reduction, reduction_...
    method _compile (line 41) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 74) | def forward(self, s0, s1, drop_prob):
  class EvoCell3 (line 115) | class EvoCell3(nn.Module):
    method __init__ (line 116) | def __init__(self,motif, C_prev_prev_prev, C_prev_prev, C_prev, C, red...
    method _compile (line 149) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 182) | def forward(self, s0, s1, s2, drop_prob):
  class EvoCell4 (line 230) | class EvoCell4(nn.Module):
    method __init__ (line 231) | def __init__(self,motif, C_prev_prev_prev_prev,C_prev_prev_prev, C_pre...
    method _compile (line 277) | def _compile(self, C, op_names, indices, concat, reduction):
    method forward (line 310) | def forward(self, s0, s1, s2, s3, drop_prob):
  class NetworkCIFAR (line 371) | class NetworkCIFAR(BaseModule):
    method __init__ (line 373) | def __init__(self,
    method forward (line 493) | def forward(self, inputs):
  class NetworkImageNet (line 588) | class NetworkImageNet(BaseModule):
    method __init__ (line 590) | def __init__(self,
    method forward (line 662) | def forward(self, inputs):

FILE: examples/Structure_Evolution/MSE-NAS/evolution.py
  function check_mem (line 368) | def check_mem(cuda_device):
  function occumpy_mem (line 373) | def occumpy_mem(cuda_device):
  class NAS (line 383) | class NAS(Problem):
    method __init__ (line 385) | def __init__(self, args,n_var=20, n_obj=1, n_constr=0, lb=None, ub=None,
    method _evaluate (line 394) | def _evaluate(self, x, out, *args, **kwargs):
  function do_every_generations (line 441) | def do_every_generations(algorithm):
  function _parse_args (line 456) | def _parse_args():

FILE: examples/Structure_Evolution/MSE-NAS/loss_f.py
  function psp (line 5) | def psp(inputs, n_steps,tau_s):
  class SpikeLoss (line 20) | class SpikeLoss(torch.nn.Module):
    method __init__ (line 24) | def __init__(self, desired_count,undesired_count):
    method spike_count (line 30) | def spike_count(self, outputs, target, desired_count,undesired_count):
    method spike_kernel (line 34) | def spike_kernel(self, outputs, target, desired_count,undesired_count):
    method spike_soft_max (line 38) | def spike_soft_max(self, outputs, target):
  class loss_count (line 43) | class loss_count(torch.autograd.Function):  # a and u is the incremnet o...
    method forward (line 45) | def forward(ctx, outputs, target, desired_count,undesired_count):
    method backward (line 65) | def backward(ctx, grad):
  class loss_kernel (line 69) | class loss_kernel(torch.autograd.Function):  # a and u is the incremnet ...
    method forward (line 71) | def forward(ctx, outputs, target, n_steps,tau_s):
    method backward (line 78) | def backward(ctx, grad):

FILE: examples/Structure_Evolution/MSE-NAS/micro_encoding.py
  function convert_cell (line 73) | def convert_cell(cell_bit_string):
  function convert (line 79) | def convert(bit_string):
  function decode (line 101) | def decode(genome):
  function decode_motif (line 126) | def decode_motif(layers,bits,genome):
  function compare_cell (line 163) | def compare_cell(cell_string1, cell_string2):
  function compare (line 179) | def compare(string1, string2):

FILE: examples/Structure_Evolution/MSE-NAS/nsganet.py
  class NSGANet (line 23) | class NSGANet(GeneticAlgorithm):
    method __init__ (line 25) | def __init__(self, **kwargs):
  function binary_tournament (line 38) | def binary_tournament(pop, P, algorithm, **kwargs):
  class RankAndCrowdingSurvival (line 83) | class RankAndCrowdingSurvival(Survival):
    method __init__ (line 85) | def __init__(self) -> None:
    method _do (line 88) | def _do(self, pop, n_survive, D=None, **kwargs):
  function calc_crowding_distance (line 124) | def calc_crowding_distance(F):
  function nsganet (line 178) | def nsganet(

FILE: examples/Structure_Evolution/MSE-NAS/obj.py
  function logdet (line 30) | def logdet(K):
  function LSP (line 35) | def LSP(args,genome,train_data):

FILE: examples/Structure_Evolution/MSE-NAS/operations.py
  function si_relu (line 15) | def si_relu(x, positive):
  class SiReLU (line 27) | class SiReLU(nn.Module):
    method __init__ (line 28) | def __init__(self, positive=0):
    method forward (line 32) | def forward(self, x):
  function weight_init (line 36) | def weight_init(m):
  class SiMLP (line 157) | class SiMLP(nn.Module):
    method __init__ (line 158) | def __init__(self, c_in, c_out, act_fun=nn.ReLU, positive=0, *args, **...
    method forward (line 166) | def forward(self, x):
  class DilConv (line 173) | class DilConv(nn.Module):
    method __init__ (line 178) | def __init__(self, C_in, C_out, kernel_size, stride, padding, dilation...
    method forward (line 192) | def forward(self, x):
  class SepConv (line 197) | class SepConv(nn.Module):
    method __init__ (line 199) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 218) | def forward(self, x):
  class Identity (line 223) | class Identity(nn.Module):
    method __init__ (line 225) | def __init__(self, positive=0):
    method forward (line 229) | def forward(self, x):
  class Zero (line 233) | class Zero(nn.Module):
    method __init__ (line 235) | def __init__(self, stride):
    method forward (line 239) | def forward(self, x):
  class FactorizedReduce (line 245) | class FactorizedReduce(nn.Module):
    method __init__ (line 247) | def __init__(self, C_in, C_out, affine=True, act_fun=nn.ReLU, positive...
    method forward (line 259) | def forward(self, x):
  class F0 (line 267) | class F0(nn.Module):
    method __init__ (line 269) | def __init__(self, C_in, C_out, affine=True, act_fun=nn.ReLU, positive...
    method forward (line 282) | def forward(self, x):
  class ReLUConvBN (line 292) | class ReLUConvBN(nn.Module):
    method __init__ (line 297) | def __init__(self, C_in, C_out, kernel_size, stride, padding, affine=T...
    method forward (line 310) | def forward(self, x):
  class Attention (line 334) | class Attention(Module):
    method __init__ (line 339) | def __init__(self, dim, num_heads=4, attention_dropout=0.1, projection...
    method forward (line 350) | def forward(self, x):
  class TransformerEncoderLayer (line 366) | class TransformerEncoderLayer(Module):
    method __init__ (line 372) | def __init__(self, d_model, nhead=4, dim_feedforward=256, dropout=0.1,
    method forward (line 390) | def forward(self, src: torch.Tensor, *args, **kwargs) -> torch.Tensor:
  function drop_path (line 403) | def drop_path(x, drop_prob: float = 0., training: bool = False):
  class DropPath (line 425) | class DropPath(Module):
    method __init__ (line 431) | def __init__(self, drop_prob=None):
    method forward (line 435) | def forward(self, x):

FILE: examples/Structure_Evolution/MSE-NAS/tm.py
  function train_motifs (line 44) | def train_motifs(args,gen,arch_dir,genome,_logger,args_text,devices,bits):
  function train_epoch (line 394) | def train_epoch(
  function validate (line 588) | def validate(epoch, model, loader, loss_fn, args,_logger, arch_dir,amp_a...

FILE: examples/Structure_Evolution/MSE-NAS/utils.py
  function drop_path (line 19) | def drop_path(x, drop_prob):
  class AvgrageMeter (line 28) | class AvgrageMeter(object):
    method __init__ (line 30) | def __init__(self):
    method reset (line 33) | def reset(self):
    method update (line 38) | def update(self, val, n=1):
  function accuracy (line 44) | def accuracy(output, target, topk=(1,)):
  class Cutout (line 64) | class Cutout(object):
    method __init__ (line 65) | def __init__(self, length):
    method __call__ (line 68) | def __call__(self, img):
  function _data_transforms_cifar (line 86) | def _data_transforms_cifar(args):
  function count_parameters_in_MB (line 119) | def count_parameters_in_MB(model):
  function save_checkpoint (line 123) | def save_checkpoint(state, is_best, save):
  function save (line 131) | def save(model, model_path):
  function load (line 135) | def load(model, model_path):
  function drop_path (line 139) | def drop_path(x, drop_prob):
  function create_exp_dir (line 149) | def create_exp_dir(path, scripts_to_save=None):
  function calc_time (line 161) | def calc_time(seconds):
  function save_file (line 168) | def save_file(recoder, path='./', back_connection=False):
  function data_transforms (line 192) | def data_transforms(args):

FILE: examples/TIM/main.py
  function _parse_args (line 349) | def _parse_args():
  function main (line 367) | def main():
  function train_epoch (line 738) | def train_epoch(
  function validate (line 888) | def validate(epoch, model, loader, loss_fn, args, amp_autocast=suppress,

FILE: examples/TIM/models/TIM.py
  class TIM (line 11) | class TIM(BaseModule):
    method __init__ (line 12) | def __init__(self,dim=256,encode_type='direct',in_channels=16,TIM_alph...
    method forward (line 25) | def forward(self, x):

FILE: examples/TIM/models/spikformer_braincog_DVS.py
  class MLP (line 17) | class MLP(BaseModule):
    method __init__ (line 18) | def __init__(self,in_features,step=10,encode_type='direct',hidden_feat...
    method forward (line 33) | def forward(self, x):
  class SSA (line 48) | class SSA(BaseModule):
    method __init__ (line 49) | def __init__(self,dim,step=10,encode_type='direct',num_heads=16,TIM_al...
    method forward (line 84) | def forward(self, x):
  class Block (line 122) | class Block(nn.Module):
    method __init__ (line 123) | def __init__(self, dim, num_heads, step=10,TIM_alpha=0.5, mlp_ratio=4....
    method forward (line 136) | def forward(self, x):
  class SPS (line 141) | class SPS(BaseModule):
    method __init__ (line 142) | def __init__(self, step=10, encode_type='direct', img_size_h=64, img_s...
    method forward (line 180) | def forward(self, x):
  class Spikformer (line 220) | class Spikformer(nn.Module):
    method __init__ (line 221) | def __init__(self, step=10,TIM_alpha=0.5,if_UCF=False,
    method _get_pos_embed (line 259) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 267) | def _init_weights(self, m):
    method forward_features (line 276) | def forward_features(self, x):
    method forward (line 287) | def forward(self, x):
  function spikformer_dvs (line 296) | def spikformer_dvs(pretrained=False, **kwargs):

FILE: examples/TIM/models/spikformer_braincog_SHD.py
  class MLP (line 17) | class MLP(BaseModule):
    method __init__ (line 18) | def __init__(self,in_features,step=10,encode_type='direct',hidden_feat...
    method forward (line 33) | def forward(self, x):
  class SSA (line 48) | class SSA(BaseModule):
    method __init__ (line 49) | def __init__(self,dim,step=10,encode_type='direct',num_heads=16,TIM_al...
    method forward (line 84) | def forward(self, x):
  class Block (line 122) | class Block(nn.Module):
    method __init__ (line 123) | def __init__(self, dim, num_heads, step=10,TIM_alpha=0.5, mlp_ratio=4....
    method forward (line 136) | def forward(self, x):
  class SPS (line 141) | class SPS(BaseModule):
    method __init__ (line 142) | def __init__(self, step=10, encode_type='direct', img_size_h=64, img_s...
    method forward (line 180) | def forward(self, x):
  class Spikformer (line 222) | class Spikformer(nn.Module):
    method __init__ (line 223) | def __init__(self, step=10,TIM_alpha=0.5,if_UCF=False,
    method _get_pos_embed (line 261) | def _get_pos_embed(self, pos_embed, patch_embed, H, W):
    method _init_weights (line 269) | def _init_weights(self, m):
    method forward_features (line 278) | def forward_features(self, x):
    method forward (line 289) | def forward(self, x):
  function spikformer_shd (line 298) | def spikformer_shd(pretrained=False, **kwargs):

FILE: examples/TIM/utils/MyGrad.py
  class MyGrad (line 6) | class MyGrad(SurrogateFunctionBase):
    method __init__ (line 7) | def __init__(self, alpha=4., requires_grad=False):
    method act_fun (line 11) | def act_fun(x, alpha):

FILE: examples/TIM/utils/MyNode.py
  class MyBaseNode (line 7) | class MyBaseNode(BaseNode):
    method __init__ (line 8) | def __init__(self,threshold=0.5,step=10,layer_by_layer=False,mem_detac...
    method rearrange2node (line 10) | def rearrange2node(self, inputs):
    method rearrange2op (line 37) | def rearrange2op(self, inputs):
  class MyNode (line 62) | class MyNode(MyBaseNode):
    method __init__ (line 63) | def __init__(self, threshold=1.,step=10,layer_by_layer=True,tau=2., ac...
    method integral (line 69) | def integral(self, inputs):
    method calc_spike (line 71) | def calc_spike(self):

FILE: examples/TIM/utils/datasets.py
  function unpack_mix_param (line 52) | def unpack_mix_param(args):
  function build_transform (line 65) | def build_transform(is_train, img_size):
  function build_dataset (line 109) | def build_dataset(is_train, img_size, dataset, path, same_da=False):
  class MNISTData (line 135) | class MNISTData(object):
    method __init__ (line 140) | def __init__(self,
    method get_data_loaders (line 157) | def get_data_loaders(self):
    method get_standard_data (line 171) | def get_standard_data(self):
  function get_mnist_data (line 182) | def get_mnist_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_fashion_data (line 228) | def get_fashion_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_cifar10_data (line 261) | def get_cifar10_data(batch_size, num_workers=8, same_da=False, **kwargs):
  function get_shd_data (line 304) | def get_shd_data(batch_size, step, **kwargs):
  function get_cifar100_data (line 346) | def get_cifar100_data(batch_size, num_workers=8, same_data=False, *args,...
  function get_imnet_data (line 389) | def get_imnet_data(args, _logger, data_config, num_aug_splits, **kwargs):
  function get_dvsg_data (line 481) | def get_dvsg_data(batch_size, step, **kwargs):
  function get_dvsc10_data (line 582) | def get_dvsc10_data(batch_size, step, **kwargs):
  function get_nmnist_data (line 704) | def get_nmnist_data(batch_size, step, **kwargs):
  function get_NCALTECH101_data (line 826) | def get_NCALTECH101_data(batch_size, step, **kwargs):
  function get_UCF101DVS_data (line 955) | def get_UCF101DVS_data(batch_size, step, **kwargs):
  function get_HMDBDVS_data (line 1061) | def get_HMDBDVS_data(batch_size, step, **kwargs):
  function get_nomni_data (line 1288) | def get_nomni_data(batch_size, train_portion=1., **kwargs):

FILE: examples/decision_making/BDM-SNN/BDM-SNN-UAV.py
  function chooseAct (line 22) | def chooseAct(Net,input,weight_trace_d1,weight_trace_d2):
  function updateNet (line 41) | def updateNet(Net,reward, action, state,weight_trace_d1,weight_trace_d2):

FILE: examples/decision_making/BDM-SNN/BDM-SNN-hh.py
  function load_images (line 18) | def load_images():
  class Bird (line 38) | class Bird(pygame.sprite.Sprite):
    method __init__ (line 51) | def __init__(self, x, y, msec_to_climb, images):
    method update (line 59) | def update(self, action,state,delta_frames=1):
    method sink (line 78) | def sink(self, delta_frames=1):
    method image (line 82) | def image(self):
    method mask (line 89) | def mask(self):
    method rect (line 96) | def rect(self):
  class PipePair (line 99) | class PipePair(pygame.sprite.Sprite):
    method __init__ (line 109) | def __init__(self, pipe_end_img, pipe_body_img):
    method top_height_px (line 152) | def top_height_px(self):
    method bottom_height_px (line 156) | def bottom_height_px(self):
    method visible (line 160) | def visible(self):
    method rect (line 164) | def rect(self):
    method update (line 167) | def update(self, delta_frames=1):
    method collides_with (line 170) | def collides_with(self, bird):
  function chooseAct (line 173) | def chooseAct(Net,input,weight_trace_d1,weight_trace_d2):
  function judgeState (line 192) | def judgeState(bird, pipes, collide):
  function blankState (line 242) | def blankState(bird, center):
  function getReward (line 268) | def getReward(state,lastState,smallerError,isNewPipe):
  function updateNet (line 307) | def updateNet(Net,reward, action, state,weight_trace_d1,weight_trace_d2):

FILE: examples/decision_making/BDM-SNN/BDM-SNN.py
  function load_images (line 17) | def load_images():
  class Bird (line 39) | class Bird(pygame.sprite.Sprite):
    method __init__ (line 52) | def __init__(self, x, y, msec_to_climb, images):
    method update (line 60) | def update(self, action, state, delta_frames=1):
    method sink (line 79) | def sink(self, delta_frames=1):
    method image (line 83) | def image(self):
    method mask (line 90) | def mask(self):
    method rect (line 97) | def rect(self):
  class PipePair (line 101) | class PipePair(pygame.sprite.Sprite):
    method __init__ (line 111) | def __init__(self, pipe_end_img, pipe_body_img):
    method top_height_px (line 154) | def top_height_px(self):
    method bottom_height_px (line 158) | def bottom_height_px(self):
    method visible (line 162) | def visible(self):
    method rect (line 166) | def rect(self):
    method update (line 169) | def update(self, delta_frames=1):
    method collides_with (line 172) | def collides_with(self, bird):
  function chooseAct (line 176) | def chooseAct(Net, input, weight_trace_d1, weight_trace_d2):
  function judgeState (line 196) | def judgeState(bird, pipes, collide):
  function blankState (line 247) | def blankState(bird, center):
  function getReward (line 274) | def getReward(state, lastState, smallerError, isNewPipe):
  function updateNet (line 314) | def updateNet(Net, reward, action, state, weight_trace_d1, weight_trace_...

FILE: examples/decision_making/BDM-SNN/decisionmaking.py
  class BDMSNN (line 24) | class BDMSNN(nn.Module):
    method __init__ (line 25) | def __init__(self, num_state, num_action, weight_exc, weight_inh, node...
    method forward (line 86) | def forward(self, input):
    method UpdateWeight (line 107) | def UpdateWeight(self, i, s, num_action, dw):
    method reset (line 131) | def reset(self):
    method getweight (line 141) | def getweight(self):
  function load_images (line 148) | def load_images():
  class Bird (line 188) | class Bird(pygame.sprite.Sprite):
    method __init__ (line 198) | def __init__(self, x, y, msec_to_climb, images):
    method update (line 206) | def update(self, action,state,delta_frames=1):
    method sink (line 219) | def sink(self, delta_frames=1):
    method image (line 223) | def image(self):
    method mask (line 230) | def mask(self):
    method rect (line 237) | def rect(self):
  class PipePair (line 240) | class PipePair(pygame.sprite.Sprite):
    method __init__ (line 247) | def __init__(self, pipe_end_img, pipe_body_img):
    method top_height_px (line 300) | def top_height_px(self):
    method bottom_height_px (line 305) | def bottom_height_px(self):
    method visible (line 310) | def visible(self):
    method rect (line 315) | def rect(self):
    method update (line 319) | def update(self, delta_frames=1):
    method collides_with (line 328) | def collides_with(self, bird):
  function chooseAct (line 337) | def chooseAct(Net,s,input,weight_trace_d1,weight_trace_d2):
  function judgeState (line 352) | def judgeState(bird, pipes, collide):
  function blankState (line 395) | def blankState(bird, center):  # judge the state before passing the pipe
  function getReward (line 415) | def getReward(state,lastState,smallerError,isNewPipe):
  function updateNet (line 446) | def updateNet(Net,reward, action, state,weight_trace_d1,weight_trace_d2):

FILE: examples/decision_making/RL/atari/atari_wrapper.py
  class NoopResetEnv (line 11) | class NoopResetEnv(gym.Wrapper):
    method __init__ (line 19) | def __init__(self, env, noop_max=30):
    method reset (line 25) | def reset(self):
  class MaxAndSkipEnv (line 35) | class MaxAndSkipEnv(gym.Wrapper):
    method __init__ (line 43) | def __init__(self, env, skip=4):
    method step (line 47) | def step(self, action):
  class EpisodicLifeEnv (line 62) | class EpisodicLifeEnv(gym.Wrapper):
    method __init__ (line 69) | def __init__(self, env):
    method step (line 74) | def step(self, action):
    method reset (line 88) | def reset(self):
  class FireResetEnv (line 102) | class FireResetEnv(gym.Wrapper):
    method __init__ (line 109) | def __init__(self, env):
    method reset (line 114) | def reset(self):
  class WarpFrame (line 119) | class WarpFrame(gym.ObservationWrapper):
    method __init__ (line 125) | def __init__(self, env):
    method observation (line 135) | def observation(self, frame):
  class ScaledFloatFrame (line 141) | class ScaledFloatFrame(gym.ObservationWrapper):
    method __init__ (line 147) | def __init__(self, env):
    method observation (line 157) | def observation(self, observation):
  class ClipRewardEnv (line 161) | class ClipRewardEnv(gym.RewardWrapper):
    method __init__ (line 167) | def __init__(self, env):
    method reward (line 171) | def reward(self, reward):
  class FrameStack (line 176) | class FrameStack(gym.Wrapper):
    method __init__ (line 183) | def __init__(self, env, n_frames):
    method reset (line 195) | def reset(self):
    method step (line 201) | def step(self, action):
    method _get_ob (line 206) | def _get_ob(self):
  function wrap_deepmind (line 212) | def wrap_deepmind(

FILE: examples/decision_making/RL/mcs-fqf/discrete.py
  class SpikePopEncodingNetwork (line 13) | class SpikePopEncodingNetwork(nn.Module):
    method __init__ (line 26) | def __init__(self, num_cosines: int, embedding_dim: int, device, time_...
    method reset (line 46) | def reset(self):
    method forward (line 51) | def forward(self, taus: torch.Tensor, time_window: int) -> torch.Tensor:
  class SpikeFractionProposalNetwork (line 68) | class SpikeFractionProposalNetwork(nn.Module):
    method __init__ (line 80) | def __init__(self, num_fractions: int, embedding_dim: int) -> None:
    method forward (line 88) | def forward(
  class MCQuantiles (line 105) | class MCQuantiles(nn.Module):
    method __init__ (line 106) | def __init__(self,
    method reset (line 126) | def reset(self):
    method forward (line 131) | def forward(self, state_embedding, tau_embedding):
  class SpikeFullQuantileFunction (line 165) | class SpikeFullQuantileFunction(nn.Module):
    method __init__ (line 185) | def __init__(
    method forward (line 205) | def forward(  # type: ignore

FILE: examples/decision_making/RL/mcs-fqf/main.py
  function get_args (line 17) | def get_args():
  function make_atari_env (line 67) | def make_atari_env(args):
  function make_atari_env_watch (line 71) | def make_atari_env_watch(args):
  function main (line 80) | def main(args=get_args()):

FILE: examples/decision_making/RL/mcs-fqf/network.py
  class SpikingDQN (line 11) | class SpikingDQN(nn.Module):
    method __init__ (line 18) | def __init__(
    method reset (line 80) | def reset(self):
    method forward (line 85) | def forward(

FILE: examples/decision_making/RL/mcs-fqf/policy.py
  class FQFPolicy (line 12) | class FQFPolicy(QRDQNPolicy):
    method __init__ (line 37) | def __init__(
    method _target_q (line 59) | def _target_q(self, buffer: ReplayBuffer, indices: np.ndarray) -> torc...
    method forward (line 74) | def forward(
    method learn (line 118) | def learn(self, batch: Batch, **kwargs: Any) -> Dict[str, float]:

FILE: examples/decision_making/RL/sdqn/main.py
  function get_args (line 27) | def get_args():
  function make_atari_env (line 77) | def make_atari_env(args):
  function make_atari_env_watch (line 81) | def make_atari_env_watch(args):
  function main (line 90) | def main(args=get_args()):

FILE: examples/decision_making/RL/sdqn/network.py
  class SpikingDQN (line 11) | class SpikingDQN(nn.Module):
    method __init__ (line 18) | def __init__(
    method reset (line 60) | def reset(self):
    method forward (line 65) | def forward(

FILE: examples/decision_making/RL/utils/normalization.py
  class PopNorm (line 15) | class PopNorm(Module):
    method __init__ (line 77) | def __init__(self, normalized_shape: _shape_t, threshold: float, v_res...
    method reset_parameters (line 95) | def reset_parameters(self) -> None:
    method forward (line 101) | def forward(self, input: Tensor) -> Tensor:
    method extra_repr (line 109) | def extra_repr(self) -> Tensor:
  class _NormBase (line 114) | class _NormBase(nn.Module):
    method __init__ (line 127) | def __init__(
    method reset_running_stats (line 167) | def reset_running_stats(self) -> None:
    method reset_parameters (line 175) | def reset_parameters(self) -> None:
    method _check_input_dim (line 182) | def _check_input_dim(self, input):
    method extra_repr (line 185) | def extra_repr(self):
    method _load_from_state_dict (line 191) | def _load_from_state_dict(
  class _BatchNorm (line 220) | class _BatchNorm(_NormBase):
    method __init__ (line 221) | def __init__(
    method forward (line 237) | def forward(self, input: Tensor) -> Tensor:
  class PDBatchNorm2d (line 286) | class PDBatchNorm2d(_BatchNorm):
    method _check_input_dim (line 353) | def _check_input_dim(self, input):

FILE: examples/decision_making/swarm/Collision-Avoidance.py
  function chooseAct (line 75) | def chooseAct(Net,input,explore):
  function update_boids (line 98) | def update_boids(xs, ys, xvs, yvs,frame):
  function animate (line 262) | def animate(frame):