SYMBOL INDEX (83 symbols across 7 files)

FILE: latent_interp.py
  function run (line 82) | def run(args):
  function main (line 122) | def main():

FILE: model.py
  class PixelNormLayer (line 18) | class PixelNormLayer(nn.Module):
    method __init__ (line 19) | def __init__(self):
    method forward (line 22) | def forward(self, x):
  class WScaleLayer (line 26) | class WScaleLayer(nn.Module):
    method __init__ (line 27) | def __init__(self, size):
    method forward (line 33) | def forward(self, x):
  class NormConvBlock (line 41) | class NormConvBlock(nn.Module):
    method __init__ (line 42) | def __init__(self, in_channels, out_channels, kernel_size, padding):
    method forward (line 49) | def forward(self, x):
  class NormUpscaleConvBlock (line 56) | class NormUpscaleConvBlock(nn.Module):
    method __init__ (line 57) | def __init__(self, in_channels, out_channels, kernel_size, padding):
    method forward (line 65) | def forward(self, x):
  class Generator (line 73) | class Generator(nn.Module):
    method __init__ (line 74) | def __init__(self):
    method forward (line 107) | def forward(self, x):

FILE: network.py
  function Tsum (line 39) | def Tsum    (*args, **kwargs): return T.sum (*args, dtype=theano.config....
  function Tmean (line 40) | def Tmean   (*args, **kwargs): return T.mean(*args, dtype=theano.config....
  function Tstd (line 41) | def Tstd    (*args, **kwargs): return T.std (*args, **kwargs)
  function Tstdeps (line 42) | def Tstdeps (val, **kwargs):   return T.sqrt(Tmean(T.square(val - Tmean(...
  function Downscale2DLayer (line 43) | def Downscale2DLayer(incoming, scale_factor, **kwargs): return Pool2DLay...
  class Network (line 48) | class Network(object):
    method __init__ (line 49) | def __init__(self, **build_func_spec):
    method eval (line 62) | def eval(self, *inputs, **kwargs): # eval(input) => output --OR-- eval...
    method eval_d (line 73) | def eval_d(self, *inputs, **kwargs):
    method eval_nd (line 76) | def eval_nd(self, *inputs, **kwargs):
    method eval_multi (line 79) | def eval_multi(self, *inputs, **kwargs): # eval(input_batch1, input_ba...
    method find_layer (line 90) | def find_layer(self, name):
    method trainable_params (line 96) | def trainable_params(self):
    method toplevel_params (line 99) | def toplevel_params(self): # returns dict(name=shared)
    method get_toplevel_param_values (line 102) | def get_toplevel_param_values(self): # returns dict(name=value)
    method set_toplevel_param_values (line 105) | def set_toplevel_param_values(self, value_dict): # accepts dict(name=v...
    method create_temporally_smoothed_version (line 110) | def create_temporally_smoothed_version(self, beta=0.99, explicit_updat...
    method _call_build_func (line 146) | def _call_build_func(self, module_globals):
    method _call_build_func_from_src (line 185) | def _call_build_func_from_src(self):
    method __getstate__ (line 191) | def __getstate__(self): # Pickle export.
    method __setstate__ (line 198) | def __setstate__(self, state): # Pickle import.
  function non_trainable (line 208) | def non_trainable(net):
  function resize_activations (line 216) | def resize_activations(v, si, so):
  class LODSelectLayer (line 244) | class LODSelectLayer(lasagne.layers.MergeLayer):
    method __init__ (line 245) | def __init__(self, incomings, cur_lod, first_incoming_lod=0, ref_idx=0...
    method get_output_shape_for (line 251) | def get_output_shape_for(self, input_shapes):
    method get_output_for (line 254) | def get_output_for(self, inputs, min_lod=None, max_lod=None, **kwargs):
  class PixelNormLayer (line 269) | class PixelNormLayer(lasagne.layers.Layer):
    method __init__ (line 270) | def __init__(self, incoming, **kwargs):
    method get_output_for (line 272) | def get_output_for(self, v, **kwargs):
  class WScaleLayer (line 278) | class WScaleLayer(lasagne.layers.Layer):
    method __init__ (line 279) | def __init__(self, incoming, **kwargs):
    method get_output_for (line 296) | def get_output_for(self, v, **kwargs):
  class MinibatchStatConcatLayer (line 308) | class MinibatchStatConcatLayer(lasagne.layers.Layer):
    method __init__ (line 309) | def __init__(self, incoming, func, averaging, **kwargs):
    method get_output_shape_for (line 314) | def get_output_shape_for(self, input_shape):
    method get_output_for (line 322) | def get_output_for(self, input, **kwargs):
  class GDropLayer (line 360) | class GDropLayer(lasagne.layers.Layer):
    method __init__ (line 361) | def __init__(self, incoming, mode='mul', strength=0.4, axes=(0,1), nor...
    method get_output_for (line 371) | def get_output_for(self, input, deterministic=False, **kwargs):
  class LayerNormLayer (line 406) | class LayerNormLayer(lasagne.layers.Layer):
    method __init__ (line 407) | def __init__(self, incoming, epsilon=1.0e-4, **kwargs):
    method get_output_for (line 422) | def get_output_for(self, v, **kwargs):
  function G_paper (line 435) | def G_paper(
  function D_paper (line 491) | def D_paper(
  function G_mnist_mode_recovery (line 544) | def G_mnist_mode_recovery(
  function D_mnist_mode_recovery (line 603) | def D_mnist_mode_recovery(
  function load_mnist_classifier (line 652) | def load_mnist_classifier(pkl_path):

FILE: predict.py
  function run (line 38) | def run(args):
  function main (line 68) | def main():

FILE: pygame_interp_demo.py
  function run (line 65) | def run(args):
  function main (line 114) | def main():

FILE: transfer_weights.py
  function init_model (line 41) | def init_model(model, conv_weights, wscale_weights, nin_weights,
  function compare_results (line 64) | def compare_results(model, G, use_cuda=False):
  function run (line 99) | def run(args):
  function main (line 136) | def main():

FILE: utils.py
  function scale_image (line 21) | def scale_image(image):
  function scale_image_paper (line 28) | def scale_image_paper(image, drange_in, drange_out):
  function save_images (line 39) | def save_images(images, output_dir, start_idx=0):
  function get_gaussian_latents (line 48) | def get_gaussian_latents(nb_latents, filter_latents):
  function slerp (line 57) | def slerp(val, low, high):
  function get_slerp_interp (line 69) | def get_slerp_interp(nb_latents, nb_interp):
  class LatentDataset (line 86) | class LatentDataset(Dataset):
    method __init__ (line 87) | def __init__(self, interp_type='gauss', nb_latents=1, filter_latents=3,
    method __getitem__ (line 95) | def __getitem__(self, index):
    method __len__ (line 98) | def __len__(self):