SYMBOL INDEX (155 symbols across 18 files)

FILE: datagen.py
  class ListDataset (line 11) | class ListDataset(data.Dataset):
    method __init__ (line 12) | def __init__(self, root, list_file, transform):
    method __getitem__ (line 34) | def __getitem__(self, idx):
    method __len__ (line 52) | def __len__(self):
  function test (line 56) | def test():

FILE: flops_counter_pytorch/ptflops/flops_counter.py
  function get_model_complexity_info (line 5) | def get_model_complexity_info(model, input_res, print_per_layer_stat=Tru...
  function flops_to_string (line 29) | def flops_to_string(flops, units='GMac', precision=12):
  function params_to_string (line 49) | def params_to_string(params_num):
  function print_model_with_flops (line 55) | def print_model_with_flops(model, units='GMac', precision=3):
  function get_model_parameters_number (line 92) | def get_model_parameters_number(model):
  function add_flops_counting_methods (line 96) | def add_flops_counting_methods(net_main_module):
  function compute_average_flops_cost (line 112) | def compute_average_flops_cost(self):
  function start_flops_count (line 130) | def start_flops_count(self):
  function stop_flops_count (line 143) | def stop_flops_count(self):
  function reset_flops_count (line 156) | def reset_flops_count(self):
  function add_flops_mask (line 168) | def add_flops_mask(module, mask):
  function remove_flops_mask (line 175) | def remove_flops_mask(module):
  function is_supported_instance (line 180) | def is_supported_instance(module):
  function empty_flops_counter_hook (line 190) | def empty_flops_counter_hook(module, input, output):
  function upsample_flops_counter_hook (line 194) | def upsample_flops_counter_hook(module, input, output):
  function relu_flops_counter_hook (line 203) | def relu_flops_counter_hook(module, input, output):
  function linear_flops_counter_hook (line 208) | def linear_flops_counter_hook(module, input, output):
  function pool_flops_counter_hook (line 214) | def pool_flops_counter_hook(module, input, output):
  function bn_flops_counter_hook (line 218) | def bn_flops_counter_hook(module, input, output):
  function conv_flops_counter_hook (line 227) | def conv_flops_counter_hook(conv_module, input, output):
  function batch_counter_hook (line 262) | def batch_counter_hook(module, input, output):
  function add_batch_counter_variables_or_reset (line 274) | def add_batch_counter_variables_or_reset(module):
  function add_batch_counter_hook_function (line 279) | def add_batch_counter_hook_function(module):
  function remove_batch_counter_hook_function (line 287) | def remove_batch_counter_hook_function(module):
  function add_flops_counter_variable_or_reset (line 293) | def add_flops_counter_variable_or_reset(module):
  function add_flops_counter_hook_function (line 298) | def add_flops_counter_hook_function(module):
  function remove_flops_counter_hook_function (line 322) | def remove_flops_counter_hook_function(module):
  function add_flops_mask_variable_or_reset (line 331) | def add_flops_mask_variable_or_reset(module):

FILE: loss.py
  class FIIQALoss (line 10) | class FIIQALoss(nn.Module):
    method __init__ (line 11) | def __init__(self):
    method forward (line 14) | def forward(self, fiiqa_preds, fiiqa_targets):

FILE: net.py
  class BasicBlock (line 8) | class BasicBlock(nn.Module):
    method __init__ (line 11) | def __init__(self, in_planes, planes, stride=1):
    method forward (line 25) | def forward(self, x):
    method freeze_bn (line 32) | def freeze_bn(self):
  class Bottleneck (line 38) | class Bottleneck(nn.Module):
    method __init__ (line 41) | def __init__(self, in_planes, planes, stride=1):
    method forward (line 57) | def forward(self, x):
  class ResNet (line 66) | class ResNet(nn.Module):
    method __init__ (line 67) | def __init__(self, block, num_blocks):
    method _make_layer (line 80) | def _make_layer(self, block, planes, num_blocks, stride):
    method forward (line 88) | def forward(self, x):
  function ResNet18 (line 97) | def ResNet18():
  function ResNet50 (line 100) | def ResNet50():
  function ResNet101 (line 103) | def ResNet101():
  class AGNet (line 107) | class AGNet(nn.Module):
    method __init__ (line 108) | def __init__(self):
    method _make_head (line 114) | def _make_head(self):
    method forward (line 123) | def forward(self, x):
  function test (line 134) | def test():

FILE: shufflenetv2.py
  function conv_bn (line 10) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 18) | def conv_1x1_bn(inp, oup):
  function channel_shuffle (line 26) | def channel_shuffle(x, groups):
  class InvertedResidual (line 42) | class InvertedResidual(nn.Module):
    method __init__ (line 43) | def __init__(self, inp, oup, stride, benchmodel):
    method _concat (line 94) | def _concat(x, out):
    method forward (line 98) | def forward(self, x):
  class ShuffleNetV2 (line 110) | class ShuffleNetV2(nn.Module):
    method __init__ (line 111) | def __init__(self, n_class=200, input_size=160, width_mult=1): #1,0
    method forward (line 163) | def forward(self, x):
  function shufflenetv2 (line 174) | def shufflenetv2(width_mult=1.):

FILE: summary/model_hook.py
  class CModelHook (line 12) | class CModelHook(object):
    method __init__ (line 13) | def __init__(self, model, input_size):
    method _register_buffer (line 26) | def _register_buffer(module):
    method _sub_module_call_hook (line 39) | def _sub_module_call_hook(self):
    method _hook_model (line 79) | def _hook_model(self):
    method _retrieve_leaf_modules (line 84) | def _retrieve_leaf_modules(model):
    method retrieve_leaf_modules (line 91) | def retrieve_leaf_modules(self):

FILE: summary/model_summary.py
  function get_parent_node (line 15) | def get_parent_node(root_node, summary_node_name):
  function convert_leaf_modules_to_summary_tree (line 28) | def convert_leaf_modules_to_summary_tree(leaf_modules):
  function get_collected_summary_nodes (line 53) | def get_collected_summary_nodes(root_node, query_granularity):
  function pretty_format (line 71) | def pretty_format(collected_nodes):
  function model_summary (line 110) | def model_summary(model, input_size, query_granularity=1):

FILE: summary/module_mac.py
  function compute_Conv2d_mac (line 9) | def compute_Conv2d_mac(module, inp, out):
  function compute_ConvTranspose2d_mac (line 32) | def compute_ConvTranspose2d_mac(module, inp, out):
  function compute_BatchNorm2d_mac (line 54) | def compute_BatchNorm2d_mac(module, inp, out):
  function compute_MaxPool2d_mac (line 67) | def compute_MaxPool2d_mac(module, inp, out):
  function compute_AvgPool2d_mac (line 80) | def compute_AvgPool2d_mac(module, inp, out):
  function compute_ReLU_mac (line 96) | def compute_ReLU_mac(module, inp, out):
  function compute_Softmax_mac (line 105) | def compute_Softmax_mac(module, inp, out):
  function compute_Linear_mac (line 118) | def compute_Linear_mac(module, inp, out):
  function compute_module_mac (line 131) | def compute_module_mac(module, inp, out):

FILE: summary/summary_tree.py
  class CSummaryTree (line 6) | class CSummaryTree(object):
    method __init__ (line 7) | def __init__(self, root_node):
    method get_same_level_max_node_depth (line 12) | def get_same_level_max_node_depth(self, query_node):
    method update_summary_nodes_granularity (line 18) | def update_summary_nodes_granularity(self):
    method get_collected_summary_nodes (line 27) | def get_collected_summary_nodes(self, query_granularity):
  class CSummaryNode (line 44) | class CSummaryNode(object):
    method __init__ (line 45) | def __init__(self, name=str(), parent=None):
    method name (line 61) | def name(self):
    method name (line 65) | def name(self, name):
    method granularity (line 69) | def granularity(self):
    method granularity (line 73) | def granularity(self, g):
    method depth (line 77) | def depth(self):
    method input_shape (line 84) | def input_shape(self):
    method input_shape (line 91) | def input_shape(self, input_shape):
    method output_shape (line 96) | def output_shape(self):
    method output_shape (line 103) | def output_shape(self, output_shape):
    method parameter_quantity (line 108) | def parameter_quantity(self):
    method parameter_quantity (line 116) | def parameter_quantity(self, parameter_quantity):
    method inference_memory (line 121) | def inference_memory(self):
    method inference_memory (line 128) | def inference_memory(self, inference_memory):
    method MAdd (line 132) | def MAdd(self):
    method MAdd (line 139) | def MAdd(self, MAdd):
    method duration (line 143) | def duration(self):
    method duration (line 150) | def duration(self, duration):
    method find_child_index (line 153) | def find_child_index(self, child_name):
    method add_child (line 162) | def add_child(self, node):

FILE: test/shufflenetv2.py
  function conv_bn (line 10) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 18) | def conv_1x1_bn(inp, oup):
  function channel_shuffle (line 26) | def channel_shuffle(x, groups):
  class InvertedResidual (line 42) | class InvertedResidual(nn.Module):
    method __init__ (line 43) | def __init__(self, inp, oup, stride, benchmodel):
    method _concat (line 94) | def _concat(x, out):
    method forward (line 98) | def forward(self, x):
  class ShuffleNetV2 (line 110) | class ShuffleNetV2(nn.Module):
    method __init__ (line 111) | def __init__(self, input_size, n_class=200,  width_mult=1): #1,0
    method forward (line 163) | def forward(self, x):
  function shufflenetv2 (line 174) | def shufflenetv2(width_mult=1.):

FILE: test_convert_to_caffe/shufflenetv2.py
  function conv_bn (line 10) | def conv_bn(inp, oup, stride):
  function conv_1x1_bn (line 18) | def conv_1x1_bn(inp, oup):
  function channel_shuffle (line 26) | def channel_shuffle(x, groups):
  class InvertedResidual (line 42) | class InvertedResidual(nn.Module):
    method __init__ (line 43) | def __init__(self, inp, oup, stride, benchmodel):
    method _concat (line 94) | def _concat(x, out):
    method forward (line 98) | def forward(self, x):
  class ShuffleNetV2 (line 110) | class ShuffleNetV2(nn.Module):
    method __init__ (line 111) | def __init__(self, input_size, n_class=200,  width_mult=1): #1,0
    method forward (line 163) | def forward(self, x):
  function shufflenetv2 (line 174) | def shufflenetv2(width_mult=1.):

FILE: test_convert_to_caffe/shufflenetv2_to_caffe.py
  function _channel_shuffle (line 23) | def _channel_shuffle(raw, input, groups):
  function parse (line 37) | def parse():
  function convert (line 46) | def convert(pytorch_net, caffe_prototxt, caffe_model_file, name):
  function test (line 54) | def test(caffe_prototxt, caffe_model_file, pytorch_net, topk=5):
  class SoftmaxWrapper (line 75) | class SoftmaxWrapper(nn.Module):
    method __init__ (line 76) | def __init__(self, net):
    method forward (line 80) | def forward(self, x):
  function shufflenetv2 (line 85) | def shufflenetv2(width_mult=1., pretrained=True):

FILE: test_convert_to_caffe/utils/get_topk.py
  function get_topk (line 4) | def get_topk(prob, k=5):

FILE: test_convert_to_caffe/utils/load.py
  function load_troch_model (line 5) | def load_troch_model(filename):
  function load_troch_model2 (line 18) | def load_troch_model2(filename):

FILE: test_convert_to_caffe/utils/load_test_image.py
  function load_test_image (line 11) | def load_test_image(filename='test_face.jpg', image_size=(3, 160, 160)):
  function load_test_image2 (line 26) | def load_test_image2(filename='cat_224x224.jpg', image_size=(3, 224, 224)):

FILE: test_model.py
  function write_csv (line 17) | def write_csv(header, write_data, filename):
  function test (line 27) | def test():

FILE: train.py
  function train (line 86) | def train(epoch):
  function test (line 110) | def test(epoch):
  function accuracy (line 153) | def accuracy(fiiqa_preds, fiiqa_targets):

FILE: train_affectnet.py
  function train (line 117) | def train(epoch):
  function test (line 147) | def test(epoch):