SYMBOL INDEX (451 symbols across 25 files)

FILE: 3DDFA_V2/demo.py
  function main (line 29) | def main(args,img, save_path, pose_path):
  function process_word (line 102) | def process_word(i):

FILE: 3DDFA_V2/utils/pose.py
  function P2sRt (line 18) | def P2sRt(P):
  function matrix2angle (line 39) | def matrix2angle(R):
  function angle2matrix (line 65) | def angle2matrix(theta):
  function angle2matrix_3ddfa (line 112) | def angle2matrix_3ddfa(angles):
  function calc_pose (line 140) | def calc_pose(param):
  function build_camera_box (line 150) | def build_camera_box(rear_size=90):
  function plot_pose_box (line 171) | def plot_pose_box(img, P, ver, color=(40, 255, 0), line_width=2):
  function viz_pose (line 201) | def viz_pose(img, param_lst, ver_lst, show_flag=False, wfp=None):
  function pose_6 (line 217) | def pose_6(param):
  function smooth_pose (line 231) | def smooth_pose(img, param_lst, ver_lst, pose_new, show_flag=False, wfp=...
  function get_pose (line 263) | def get_pose(img, param_lst, ver_lst, show_flag=False, wfp=None, wnp = N...

FILE: augmentation.py
  function crop_clip (line 20) | def crop_clip(clip, min_h, min_w, h, w):
  function pad_clip (line 34) | def pad_clip(clip, h, w):
  function resize_clip (line 42) | def resize_clip(clip, size, interpolation='bilinear'):
  function get_resize_sizes (line 81) | def get_resize_sizes(im_h, im_w, size):
  class RandomFlip (line 91) | class RandomFlip(object):
    method __init__ (line 92) | def __init__(self, time_flip=False, horizontal_flip=False):
    method __call__ (line 96) | def __call__(self, clip):
  class RandomResize (line 105) | class RandomResize(object):
    method __init__ (line 115) | def __init__(self, ratio=(3. / 4., 4. / 3.), interpolation='nearest'):
    method __call__ (line 119) | def __call__(self, clip):
  class RandomCrop (line 136) | class RandomCrop(object):
    method __init__ (line 143) | def __init__(self, size):
    method __call__ (line 149) | def __call__(self, clip):
  class MouthCrop (line 175) | class MouthCrop(object):
    method __init__ (line 182) | def __init__(self, center_x, center_y, mask_width, mask_height):
    method __call__ (line 190) | def __call__(self, clip):
  class RandomRotation (line 215) | class RandomRotation(object):
    method __init__ (line 224) | def __init__(self, degrees):
    method __call__ (line 237) | def __call__(self, clip):
  class RandomPerspective (line 256) | class RandomPerspective(object):
    method __init__ (line 265) | def __init__(self, pers_num, enlarge_num):
    method __call__ (line 269) | def __call__(self, clip):
  class ColorJitter (line 297) | class ColorJitter(object):
    method __init__ (line 310) | def __init__(self, brightness=0, contrast=0, saturation=0, hue=0):
    method get_params (line 316) | def get_params(self, brightness, contrast, saturation, hue):
    method __call__ (line 341) | def __call__(self, clip):
  class AllAugmentationTransform (line 403) | class AllAugmentationTransform:
    method __init__ (line 404) | def __init__(self, crop_mouth_param = None, resize_param=None, rotatio...
    method __call__ (line 427) | def __call__(self, clip):

FILE: demo.py
  function load_checkpoints (line 49) | def load_checkpoints(opt, checkpoint_path, audio_checkpoint_path, emo_ch...
  function normalize_kp (line 112) | def normalize_kp(kp_source, kp_driving, kp_driving_initial, adapt_moveme...
  function shape_to_np (line 134) | def shape_to_np(shape, dtype="int"):
  function get_aligned_image (line 146) | def get_aligned_image(driving_video, opt):
  function get_transformed_image (line 184) | def get_transformed_image(driving_video, opt):
  function make_animation_smooth (line 194) | def make_animation_smooth(source_image, driving_video, transformed_video...
  function test_auido (line 286) | def test_auido(example_image, audio_feature, all_pose, opt):
  function save (line 357) | def save(path, frames, format):
  class VideoWriter (line 370) | class VideoWriter(object):
    method __init__ (line 371) | def __init__(self, path, width, height, fps):
    method write_frame (line 376) | def write_frame(self, frame):
    method end (line 379) | def end(self):
  function concatenate (line 382) | def concatenate(number, imgs, save_path):
  function add_audio (line 427) | def add_audio(video_name=None, audio_dir = None):
  function crop_image (line 433) | def crop_image(source_image):
  function smooth_pose (line 456) | def smooth_pose(pose_file, pose_long):
  function test (line 467) | def test(opt, name):

FILE: filter1.py
  class LowPassFilter (line 13) | class LowPassFilter:
    method __init__ (line 14) | def __init__(self):
    method process (line 18) | def process(self, value, alpha):
  class OneEuroFilter (line 28) | class OneEuroFilter:
    method __init__ (line 29) | def __init__(self, mincutoff=1.0, beta=0.0, dcutoff=1.0, freq=30):
    method compute_alpha (line 37) | def compute_alpha(self, cutoff):
    method process (line 42) | def process(self, x):

FILE: frames_dataset.py
  function read_video (line 15) | def read_video(name, frame_shape):
  function get_list (line 55) | def get_list(ipath,base_name):
  class AudioDataset (line 75) | class AudioDataset(Dataset):
    method __init__ (line 83) | def __init__(self, name, root_dir, frame_shape=(256, 256, 3), id_sampl...
    method __len__ (line 132) | def __len__(self):
    method __getitem__ (line 135) | def __getitem__(self, idx):
  class VoxDataset (line 196) | class VoxDataset(Dataset):
    method __init__ (line 204) | def __init__(self, root_dir, frame_shape=(256, 256, 3), id_sampling=Fa...
    method __len__ (line 252) | def __len__(self):
    method __getitem__ (line 255) | def __getitem__(self, idx):
  class MeadDataset (line 328) | class MeadDataset(Dataset):
    method __init__ (line 336) | def __init__(self, root_dir, frame_shape=(256, 256, 3), id_sampling=Fa...
    method __len__ (line 378) | def __len__(self):
    method __getitem__ (line 381) | def __getitem__(self, idx):
  class DatasetRepeater (line 461) | class DatasetRepeater(Dataset):
    method __init__ (line 466) | def __init__(self, dataset, num_repeats=100):
    method __len__ (line 471) | def __len__(self):
    method __getitem__ (line 474) | def __getitem__(self, idx):
  class TestsetRepeater (line 481) | class TestsetRepeater(Dataset):
    method __init__ (line 486) | def __init__(self, dataset, num_repeats=100):
    method __len__ (line 491) | def __len__(self):
    method __getitem__ (line 494) | def __getitem__(self, idx):
  class PairedDataset (line 499) | class PairedDataset(Dataset):
    method __init__ (line 504) | def __init__(self, initial_dataset, number_of_pairs, seed=0):
    method __len__ (line 529) | def __len__(self):
    method __getitem__ (line 532) | def __getitem__(self, idx):

FILE: logger.py
  class Logger (line 13) | class Logger:
    method __init__ (line 14) | def __init__(self, log_dir, checkpoint_freq=100, visualizer_params=Non...
    method log_scores (line 29) | def log_scores(self, loss_names):
    method visualize_rec (line 39) | def visualize_rec(self, inp, out):
    method save_cpk (line 44) | def save_cpk(self, emergent=False):
    method load_cpk (line 53) | def load_cpk(checkpoint_path, generator=None, discriminator=None, kp_d...
    method __enter__ (line 83) | def __enter__(self):
    method __exit__ (line 86) | def __exit__(self, exc_type, exc_val, exc_tb):
    method log_iter (line 91) | def log_iter(self, losses):
    method log_epoch (line 97) | def log_epoch(self, epoch, step, models, inp, out):
  class Visualizer (line 107) | class Visualizer:
    method __init__ (line 108) | def __init__(self, kp_size=5, draw_border=False, colormap='gist_rainbo...
    method draw_image_with_kp (line 113) | def draw_image_with_kp(self, image, kp_array):
    method create_image_column_with_kp (line 123) | def create_image_column_with_kp(self, images, kp):
    method create_image_column (line 127) | def create_image_column(self, images):
    method create_image_grid (line 134) | def create_image_grid(self, *args):
    method visualize (line 143) | def visualize(self, driving, transformed_driving, source, out):

FILE: modules/dense_motion.py
  class DenseMotionNetwork (line 7) | class DenseMotionNetwork(nn.Module):
    method __init__ (line 12) | def __init__(self, block_expansion, num_blocks, max_features, num_kp, ...
    method create_heatmap_representations (line 32) | def create_heatmap_representations(self, source_image, kp_driving, kp_...
    method create_sparse_motions (line 47) | def create_sparse_motions(self, source_image, kp_driving, kp_source):
    method create_deformed_source_image (line 69) | def create_deformed_source_image(self, source_image, sparse_motions):
    method forward (line 81) | def forward(self, source_image, kp_driving, kp_source):

FILE: modules/discriminator.py
  class DownBlock2d (line 7) | class DownBlock2d(nn.Module):
    method __init__ (line 12) | def __init__(self, in_features, out_features, norm=False, kernel_size=...
    method forward (line 25) | def forward(self, x):
  class Discriminator (line 36) | class Discriminator(nn.Module):
    method __init__ (line 41) | def __init__(self, num_channels=3, block_expansion=64, num_blocks=4, m...
    method forward (line 59) | def forward(self, x, kp=None):
  class MultiScaleDiscriminator (line 74) | class MultiScaleDiscriminator(nn.Module):
    method __init__ (line 79) | def __init__(self, scales=(), **kwargs):
    method forward (line 87) | def forward(self, x, kp=None):

FILE: modules/function.py
  function calc_mean_std (line 12) | def calc_mean_std(feat, eps=1e-5):
  function adaptive_instance_normalization (line 23) | def adaptive_instance_normalization(content_feat, style_feat):
  function _calc_feat_flatten_mean_std (line 34) | def _calc_feat_flatten_mean_std(feat):
  function _mat_sqrt (line 44) | def _mat_sqrt(x):
  function coral (line 49) | def coral(source, target):

FILE: modules/generator.py
  class OcclusionAwareGenerator (line 8) | class OcclusionAwareGenerator(nn.Module):
    method __init__ (line 14) | def __init__(self, num_channels, num_kp, block_expansion, max_features...
    method deform_input (line 50) | def deform_input(self, inp, deformation):
    method forward (line 59) | def forward(self, source_image, kp_driving, kp_source):

FILE: modules/keypoint_detector.py
  class KPDetector (line 7) | class KPDetector(nn.Module):
    method __init__ (line 12) | def __init__(self, block_expansion, num_kp, num_channels, max_features,
    method gaussian2kp (line 40) | def gaussian2kp(self, heatmap):
    method audio_feature (line 52) | def audio_feature(self, x, heatmap):
    method forward (line 77) | def forward(self, x): #torch.Size([4, 3, H, W])
  class KPDetector_a (line 110) | class KPDetector_a(nn.Module):
    method __init__ (line 115) | def __init__(self, block_expansion, num_kp, num_channels,num_channels_...
    method gaussian2kp (line 143) | def gaussian2kp(self, heatmap):
    method audio_feature (line 155) | def audio_feature(self, x, heatmap):
    method forward (line 180) | def forward(self,  feature_map): #torch.Size([4, 3, H, W])
  class Audio_Feature (line 208) | class Audio_Feature(nn.Module):
    method __init__ (line 209) | def __init__(self):
    method forward (line 218) | def forward(self, x):

FILE: modules/model.py
  class Vgg19 (line 10) | class Vgg19(torch.nn.Module):
    method __init__ (line 14) | def __init__(self, requires_grad=False):
    method forward (line 42) | def forward(self, X):
  class ImagePyramide (line 53) | class ImagePyramide(torch.nn.Module):
    method __init__ (line 57) | def __init__(self, scales, num_channels):
    method forward (line 64) | def forward(self, x):
  class Transform (line 71) | class Transform:
    method __init__ (line 75) | def __init__(self, bs, **kwargs):
    method transform_frame (line 89) | def transform_frame(self, frame):
    method inverse_transform_frame (line 95) | def inverse_transform_frame(self, frame):
    method warp_coordinates (line 101) | def warp_coordinates(self, coordinates):
    method inverse_warp_coordinates (line 121) | def inverse_warp_coordinates(self, coordinates):
    method jacobian (line 146) | def jacobian(self, coordinates):
  function detach_kp (line 155) | def detach_kp(kp):
  class TrainPart1Model (line 158) | class TrainPart1Model(torch.nn.Module):
    method __init__ (line 163) | def __init__(self, kp_extractor, kp_extractor_a, audio_feature, genera...
    method forward (line 187) | def forward(self, x):
  class TrainPart2Model (line 282) | class TrainPart2Model(torch.nn.Module):
    method __init__ (line 287) | def __init__(self, kp_extractor, emo_feature, kp_extractor_a, audio_fe...
    method forward (line 312) | def forward(self, x):
  class GeneratorFullModel (line 416) | class GeneratorFullModel(torch.nn.Module):
    method __init__ (line 421) | def __init__(self, kp_extractor, kp_extractor_a, audio_feature, genera...
    method forward (line 447) | def forward(self, x):
  class DiscriminatorFullModel (line 557) | class DiscriminatorFullModel(torch.nn.Module):
    method __init__ (line 562) | def __init__(self, kp_extractor, generator, discriminator, train_params):
    method forward (line 575) | def forward(self, x, generated):

FILE: modules/model_delta_map.py
  class Vgg19 (line 10) | class Vgg19(torch.nn.Module):
    method __init__ (line 14) | def __init__(self, requires_grad=False):
    method forward (line 42) | def forward(self, X):
  class ImagePyramide (line 53) | class ImagePyramide(torch.nn.Module):
    method __init__ (line 57) | def __init__(self, scales, num_channels):
    method forward (line 64) | def forward(self, x):
  class Transform (line 71) | class Transform:
    method __init__ (line 75) | def __init__(self, bs, **kwargs):
    method transform_frame (line 89) | def transform_frame(self, frame):
    method inverse_transform_frame (line 95) | def inverse_transform_frame(self, frame):
    method warp_coordinates (line 101) | def warp_coordinates(self, coordinates):
    method inverse_warp_coordinates (line 121) | def inverse_warp_coordinates(self, coordinates):
    method jacobian (line 146) | def jacobian(self, coordinates):
  function detach_kp (line 155) | def detach_kp(kp):
  class TrainFullModel (line 158) | class TrainFullModel(torch.nn.Module):
    method __init__ (line 163) | def __init__(self, kp_extractor, emo_feature, kp_extractor_a, audio_fe...
    method forward (line 192) | def forward(self, x):
  class GeneratorFullModel (line 325) | class GeneratorFullModel(torch.nn.Module):
    method __init__ (line 330) | def __init__(self, kp_extractor, kp_extractor_a, audio_feature, genera...
    method forward (line 356) | def forward(self, x):
  class DiscriminatorFullModel (line 466) | class DiscriminatorFullModel(torch.nn.Module):
    method __init__ (line 471) | def __init__(self, kp_extractor, generator, discriminator, train_params):
    method forward (line 484) | def forward(self, x, generated):

FILE: modules/model_gen.py
  class Vgg19 (line 10) | class Vgg19(torch.nn.Module):
    method __init__ (line 14) | def __init__(self, requires_grad=False):
    method forward (line 42) | def forward(self, X):
  class ImagePyramide (line 53) | class ImagePyramide(torch.nn.Module):
    method __init__ (line 57) | def __init__(self, scales, num_channels):
    method forward (line 64) | def forward(self, x):
  class Transform (line 71) | class Transform:
    method __init__ (line 75) | def __init__(self, bs, **kwargs):
    method transform_frame (line 89) | def transform_frame(self, frame):
    method inverse_transform_frame (line 95) | def inverse_transform_frame(self, frame):
    method warp_coordinates (line 101) | def warp_coordinates(self, coordinates):
    method inverse_warp_coordinates (line 121) | def inverse_warp_coordinates(self, coordinates):
    method jacobian (line 146) | def jacobian(self, coordinates):
  function detach_kp (line 155) | def detach_kp(kp):
  class TrainFullModel (line 158) | class TrainFullModel(torch.nn.Module):
    method __init__ (line 163) | def __init__(self, kp_extractor, emo_feature, kp_extractor_a, audio_fe...
    method forward (line 192) | def forward(self, x):
  class GeneratorFullModel (line 341) | class GeneratorFullModel(torch.nn.Module):
    method __init__ (line 346) | def __init__(self, kp_extractor, kp_extractor_a, audio_feature, genera...
    method forward (line 372) | def forward(self, x):
  class DiscriminatorFullModel (line 482) | class DiscriminatorFullModel(torch.nn.Module):
    method __init__ (line 487) | def __init__(self, kp_extractor, generator, discriminator, train_params):
    method forward (line 500) | def forward(self, x, generated):

FILE: modules/ops.py
  function linear (line 8) | def linear(channel_in, channel_out,
  function conv2d (line 21) | def conv2d(channel_in, channel_out,
  function conv_transpose2d (line 37) | def conv_transpose2d(channel_in, channel_out,
  function nn_conv2d (line 53) | def nn_conv2d(channel_in, channel_out,
  function _apply (line 71) | def _apply(layer, activation, normalizer, channel_out=None):

FILE: modules/stylegan2.py
  function fused_leaky_relu (line 25) | def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):
  class FusedLeakyReLU (line 29) | class FusedLeakyReLU(nn.Module):
    method __init__ (line 30) | def __init__(self, channel, negative_slope=0.2, scale=2 ** 0.5):
    method forward (line 36) | def forward(self, input):
  function upfirdn2d_native (line 45) | def upfirdn2d_native(
  function upfirdn2d (line 82) | def upfirdn2d(input, kernel, up=1, down=1, pad=(0, 0)):
  class PixelNorm (line 86) | class PixelNorm(nn.Module):
    method __init__ (line 87) | def __init__(self):
    method forward (line 90) | def forward(self, input):
  function make_kernel (line 94) | def make_kernel(k):
  class Upsample (line 105) | class Upsample(nn.Module):
    method __init__ (line 106) | def __init__(self, kernel, factor=2):
    method forward (line 120) | def forward(self, input):
  class Downsample (line 126) | class Downsample(nn.Module):
    method __init__ (line 127) | def __init__(self, kernel, factor=2):
    method forward (line 141) | def forward(self, input):
  class Blur (line 147) | class Blur(nn.Module):
    method __init__ (line 148) | def __init__(self, kernel, pad, upsample_factor=1):
    method forward (line 160) | def forward(self, input):
  class EqualConv2d (line 166) | class EqualConv2d(nn.Module):
    method __init__ (line 167) | def __init__(
    method forward (line 186) | def forward(self, input):
    method __repr__ (line 199) | def __repr__(self):
  class EqualLinear (line 206) | class EqualLinear(nn.Module):
    method __init__ (line 207) | def __init__(
    method forward (line 225) | def forward(self, input):
    method __repr__ (line 237) | def __repr__(self):
  class ScaledLeakyReLU (line 243) | class ScaledLeakyReLU(nn.Module):
    method __init__ (line 244) | def __init__(self, negative_slope=0.2):
    method forward (line 249) | def forward(self, input):
  class ModulatedConv2d (line 255) | class ModulatedConv2d(nn.Module):
    method __init__ (line 256) | def __init__(
    method __repr__ (line 305) | def __repr__(self):
    method forward (line 311) | def forward(self, input, style):
  class NoiseInjection (line 358) | class NoiseInjection(nn.Module):
    method __init__ (line 359) | def __init__(self):
    method forward (line 364) | def forward(self, image, noise=None):
  class ConstantInput (line 372) | class ConstantInput(nn.Module):
    method __init__ (line 373) | def __init__(self, channel, size=4):
    method forward (line 378) | def forward(self, input):
  class StyledConv (line 385) | class StyledConv(nn.Module):
    method __init__ (line 386) | def __init__(
    method forward (line 415) | def forward(self, input, style=None, noise=None):
  class ToRGB (line 425) | class ToRGB(nn.Module):
    method __init__ (line 426) | def __init__(self, in_channel, style_dim, upsample=True, blur_kernel=[...
    method forward (line 435) | def forward(self, input, style, skip=None):
  class Generator (line 447) | class Generator(nn.Module):
    method __init__ (line 448) | def __init__(
    method make_noise (line 533) | def make_noise(self):
    method mean_latent (line 544) | def mean_latent(self, n_latent):
    method get_latent (line 552) | def get_latent(self, input):
    method forward (line 555) | def forward(
  class ConvLayer (line 630) | class ConvLayer(nn.Sequential):
    method __init__ (line 631) | def __init__(
  class ResBlock (line 679) | class ResBlock(nn.Module):
    method __init__ (line 680) | def __init__(self, in_channel, out_channel, blur_kernel=[1, 3, 3, 1], ...
    method forward (line 694) | def forward(self, input):
  class StyleGAN2Discriminator (line 704) | class StyleGAN2Discriminator(nn.Module):
    method __init__ (line 705) | def __init__(self, input_nc, ndf=64, n_layers=3, no_antialias=False, s...
    method forward (line 761) | def forward(self, input, get_minibatch_features=False):
  class TileStyleGAN2Discriminator (line 795) | class TileStyleGAN2Discriminator(StyleGAN2Discriminator):
    method forward (line 796) | def forward(self, input):
  class StyleGAN2Encoder (line 806) | class StyleGAN2Encoder(nn.Module):
    method __init__ (line 807) | def __init__(self, input_nc, output_nc, ngf=64, use_dropout=False, n_b...
    method forward (line 843) | def forward(self, input, layers=[], get_features=False):
  class StyleGAN2Decoder (line 860) | class StyleGAN2Decoder(nn.Module):
    method __init__ (line 861) | def __init__(self, input_nc, output_nc, ngf=64, use_dropout=False, n_b...
    method forward (line 902) | def forward(self, input):
  class StyleGAN2Generator (line 906) | class StyleGAN2Generator(nn.Module):
    method __init__ (line 907) | def __init__(self, input_nc, output_nc, ngf=64, use_dropout=False, n_b...
    method forward (line 913) | def forward(self, input, layers=[], encode_only=False):

FILE: modules/util.py
  class InstanceNorm (line 26) | class InstanceNorm(nn.Module):
    method __init__ (line 27) | def __init__(self, epsilon=1e-8):
    method forward (line 35) | def forward(self, x):
  class ApplyStyle (line 41) | class ApplyStyle(nn.Module):
    method __init__ (line 45) | def __init__(self, latent_size, channels, use_wscale):
    method forward (line 52) | def forward(self, x, latent):
  class FC (line 60) | class FC(nn.Module):
    method __init__ (line 61) | def __init__(self,
    method forward (line 87) | def forward(self, x):
  class Embedder (line 97) | class Embedder:
    method __init__ (line 98) | def __init__(self, **kwargs):
    method create_embedding_fn (line 102) | def create_embedding_fn(self):
    method embed (line 126) | def embed(self, inputs):
  function get_embedder (line 130) | def get_embedder(multires, i=0):
  function draw_heatmap (line 148) | def draw_heatmap(landmark, width, height):
  class NA_net (line 175) | class NA_net(nn.Module):
    method __init__ (line 176) | def __init__(self):
    method forward (line 195) | def forward(self, neutral):
  class AT_net (line 203) | class AT_net(nn.Module):
    method __init__ (line 204) | def __init__(self):
    method forward (line 270) | def forward(self, example_image, audio, pose, jaco_net):
  class Classify (line 306) | class Classify(nn.Module):
    method __init__ (line 307) | def __init__(self):
    method forward (line 314) | def forward(self, feature):
  class TF_net (line 321) | class TF_net(nn.Module):
    method __init__ (line 322) | def __init__(self):
    method adain_forward (line 391) | def adain_forward(self, example_image, audio, pose, jaco_net, emo_feat...
    method adain_feature2 (line 434) | def adain_feature2(self, example_image, audio, pose, jaco_net, emo_fea...
    method forward (line 477) | def forward(self, example_image, audio, pose, jaco_net, emo_features):
  class AT_net2 (line 514) | class AT_net2(nn.Module):
    method __init__ (line 515) | def __init__(self):
    method forward (line 580) | def forward(self, example_image, audio, pose, jaco_net, weight):
  class Ct_encoder (line 618) | class Ct_encoder(nn.Module):
    method __init__ (line 619) | def __init__(self):
    method forward (line 638) | def forward(self, audio):
  class EmotionNet (line 647) | class EmotionNet(nn.Module):
    method __init__ (line 648) | def __init__(self):
    method forward (line 697) | def forward(self, mfcc):
  class AF2F (line 715) | class AF2F(nn.Module):
    method __init__ (line 716) | def __init__(self):
    method forward (line 736) | def forward(self, content,emotion):
  class AF2F_s (line 745) | class AF2F_s(nn.Module):
    method __init__ (line 746) | def __init__(self):
    method forward (line 766) | def forward(self, content):
  class A2I (line 776) | class A2I(nn.Module):
    method __init__ (line 777) | def __init__(self):
    method forward (line 804) | def forward(self, mfcc):
  function kp2gaussian (line 815) | def kp2gaussian(kp, spatial_size, kp_variance):
  function make_coordinate_grid (line 839) | def make_coordinate_grid(spatial_size, type):
  class ResBlock2d (line 858) | class ResBlock2d(nn.Module):
    method __init__ (line 863) | def __init__(self, in_features, kernel_size, padding):
    method forward (line 872) | def forward(self, x):
  class UpBlock2d (line 883) | class UpBlock2d(nn.Module):
    method __init__ (line 888) | def __init__(self, in_features, out_features, kernel_size=3, padding=1...
    method forward (line 895) | def forward(self, x):
  class DownBlock2d (line 903) | class DownBlock2d(nn.Module):
    method __init__ (line 908) | def __init__(self, in_features, out_features, kernel_size=3, padding=1...
    method forward (line 915) | def forward(self, x):
  class SameBlock2d (line 923) | class SameBlock2d(nn.Module):
    method __init__ (line 928) | def __init__(self, in_features, out_features, groups=1, kernel_size=3,...
    method forward (line 934) | def forward(self, x):
  class Encoder (line 941) | class Encoder(nn.Module):
    method __init__ (line 946) | def __init__(self, block_expansion, in_features, num_blocks=3, max_fea...
    method forward (line 956) | def forward(self, x):
  class Decoder (line 963) | class Decoder(nn.Module):
    method __init__ (line 968) | def __init__(self, block_expansion, in_features, num_blocks=3, max_fea...
    method forward (line 981) | def forward(self, x):
  class Hourglass (line 990) | class Hourglass(nn.Module):
    method __init__ (line 995) | def __init__(self, block_expansion, in_features, num_blocks=3, max_fea...
    method forward (line 1001) | def forward(self, x):
  class AntiAliasInterpolation2d (line 1005) | class AntiAliasInterpolation2d(nn.Module):
    method __init__ (line 1009) | def __init__(self, channels, scale):
    method forward (line 1044) | def forward(self, input):
  function sigmoid (line 1054) | def sigmoid(x):
  function norm_angle (line 1058) | def norm_angle(angle):
  function conv3x3 (line 1063) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 1069) | class BasicBlock(nn.Module):
    method __init__ (line 1072) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 1082) | def forward(self, x):
  class Bottleneck (line 1101) | class Bottleneck(nn.Module):
    method __init__ (line 1104) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 1117) | def forward(self, x):
  class EmDetector (line 1139) | class EmDetector(nn.Module):
    method __init__ (line 1144) | def __init__(self, block_expansion,  num_channels, max_features,
    method _make_layer (line 1170) | def _make_layer(self, block, planes, blocks, stride=1):
    method adain_feature (line 1187) | def adain_feature(self, x): #torch.Size([4, 3, H, W])
    method forward (line 1197) | def forward(self, x): #torch.Size([4, 3, H, W])
  class Emotion_k (line 1223) | class Emotion_k(nn.Module):
    method __init__ (line 1228) | def __init__(self, block_expansion,  num_channels, max_features,
    method _make_layer (line 1316) | def _make_layer(self, block, planes, blocks, stride=1):
    method linear_10 (line 1333) | def linear_10(self, x, value, jacobian): #torch.Size([4, 3, H, W])
    method linear_4 (line 1364) | def linear_4(self, x, value, jacobian): #torch.Size([4, 3, H, W])
    method linear_np_10 (line 1396) | def linear_np_10(self, x, value, jacobian): #torch.Size([4, 3, H, W])
    method linear_np_4 (line 1427) | def linear_np_4(self, x, value, jacobian): #torch.Size([4, 3, H, W])
    method emotion_feature (line 1459) | def emotion_feature(self, feature, value, jacobian): #torch.Size([4, 3...
    method feature (line 1477) | def feature(self, x): #torch.Size([4, 3, H, W])
    method forward (line 1498) | def forward(self, x, value, jacobian): #torch.Size([4, 3, H, W])
  class Emotion_map (line 1529) | class Emotion_map(nn.Module):
    method __init__ (line 1534) | def __init__(self, block_expansion,  num_channels, max_features,
    method _make_layer (line 1607) | def _make_layer(self, block, planes, blocks, stride=1):
    method gaussian2kp (line 1624) | def gaussian2kp(self, heatmap):
    method map_4 (line 1636) | def map_4(self, x, value, jacobian): #torch.Size([4, 3, H, W])
    method forward (line 1687) | def forward(self, x, value, jacobian): #torch.Size([4, 3, H, W])
  function conv2d (line 1740) | def conv2d(channel_in, channel_out,
  function _apply (line 1755) | def _apply(layer, activation, normalizer, channel_out=None):

FILE: ops.py
  class ResidualBlock (line 8) | class ResidualBlock(nn.Module):
    method __init__ (line 9) | def __init__(self, channel_in, channel_out):
    method forward (line 19) | def forward(self, x):
  function linear (line 27) | def linear(channel_in, channel_out,
  function conv2d (line 40) | def conv2d(channel_in, channel_out,
  function conv_transpose2d (line 56) | def conv_transpose2d(channel_in, channel_out,
  function nn_conv2d (line 72) | def nn_conv2d(channel_in, channel_out,
  function _apply (line 90) | def _apply(layer, activation, normalizer, channel_out=None):

FILE: process_data.py
  function save (line 29) | def save(path, frames, format):
  function crop_image (line 44) | def crop_image(image_path, out_path):
  function shape_to_np (line 70) | def shape_to_np(shape, dtype="int"):
  function crop_image_tem (line 85) | def crop_image_tem(video_path, out_path):
  function proc_audio (line 124) | def proc_audio(src_mouth_path, dst_audio_path):
  function audio2mfcc (line 130) | def audio2mfcc(audio_file, save, name):

FILE: sync_batchnorm/batchnorm.py
  function _sum_ft (line 24) | def _sum_ft(tensor):
  function _unsqueeze_ft (line 29) | def _unsqueeze_ft(tensor):
  class _SynchronizedBatchNorm (line 38) | class _SynchronizedBatchNorm(_BatchNorm):
    method __init__ (line 39) | def __init__(self, num_features, eps=1e-5, momentum=0.1, affine=True):
    method forward (line 48) | def forward(self, input):
    method __data_parallel_replicate__ (line 80) | def __data_parallel_replicate__(self, ctx, copy_id):
    method _data_parallel_master (line 90) | def _data_parallel_master(self, intermediates):
    method _compute_mean_std (line 113) | def _compute_mean_std(self, sum_, ssum, size):
  class SynchronizedBatchNorm1d (line 128) | class SynchronizedBatchNorm1d(_SynchronizedBatchNorm):
    method _check_input_dim (line 184) | def _check_input_dim(self, input):
  class SynchronizedBatchNorm2d (line 191) | class SynchronizedBatchNorm2d(_SynchronizedBatchNorm):
    method _check_input_dim (line 247) | def _check_input_dim(self, input):
  class SynchronizedBatchNorm3d (line 254) | class SynchronizedBatchNorm3d(_SynchronizedBatchNorm):
    method _check_input_dim (line 311) | def _check_input_dim(self, input):

FILE: sync_batchnorm/comm.py
  class FutureResult (line 18) | class FutureResult(object):
    method __init__ (line 21) | def __init__(self):
    method put (line 26) | def put(self, result):
    method get (line 32) | def get(self):
  class SlavePipe (line 46) | class SlavePipe(_SlavePipeBase):
    method run_slave (line 49) | def run_slave(self, msg):
  class SyncMaster (line 56) | class SyncMaster(object):
    method __init__ (line 67) | def __init__(self, master_callback):
    method __getstate__ (line 78) | def __getstate__(self):
    method __setstate__ (line 81) | def __setstate__(self, state):
    method register_slave (line 84) | def register_slave(self, identifier):
    method run_master (line 102) | def run_master(self, master_msg):
    method nr_slaves (line 136) | def nr_slaves(self):

FILE: sync_batchnorm/replicate.py
  class CallbackContext (line 23) | class CallbackContext(object):
  function execute_replication_callbacks (line 27) | def execute_replication_callbacks(modules):
  class DataParallelWithCallback (line 50) | class DataParallelWithCallback(DataParallel):
    method replicate (line 64) | def replicate(self, module, device_ids):
  function patch_replication_callback (line 70) | def patch_replication_callback(data_parallel):

FILE: sync_batchnorm/unittest.py
  function as_numpy (line 17) | def as_numpy(v):
  class TorchTestCase (line 23) | class TorchTestCase(unittest.TestCase):
    method assertTensorClose (line 24) | def assertTensorClose(self, a, b, atol=1e-3, rtol=1e-3):

FILE: train.py
  function train_part1 (line 18) | def train_part1(config, generator, discriminator, kp_detector, kp_detect...
  function train_part1_fine_tune (line 133) | def train_part1_fine_tune(config, generator, discriminator, kp_detector,...
  function train_part2 (line 273) | def train_part2(config, generator, discriminator, kp_detector, emo_detec...