SYMBOL INDEX (50 symbols across 11 files)

FILE: generate_imagery.py
  class GenerationMode (line 18) | class GenerationMode(enum.Enum):
  function postprocess_generated_img (line 24) | def postprocess_generated_img(generated_img_tensor):
  function generate_from_random_latent_vector (line 42) | def generate_from_random_latent_vector(generator, cgan_digit=None):
  function generate_from_specified_numpy_latent_vector (line 56) | def generate_from_specified_numpy_latent_vector(generator, latent_vector):
  function linear_interpolation (line 64) | def linear_interpolation(t, p0, p1):
  function spherical_interpolation (line 68) | def spherical_interpolation(t, p0, p1):
  function display_vector_arithmetic_results (line 96) | def display_vector_arithmetic_results(imgs_to_display):
  function generate_new_images (line 121) | def generate_new_images(model_name, cgan_digit=None, generation_mode=Tru...

FILE: models/definitions/conditional_gan.py
  class ConditionalGeneratorNet (line 18) | class ConditionalGeneratorNet(torch.nn.Module):
    method __init__ (line 33) | def __init__(self, img_shape=(MNIST_IMG_SIZE, MNIST_IMG_SIZE)):
    method forward (line 48) | def forward(self, latent_vector_batch, one_hot_conditioning_vector_bat...
  class ConditionalDiscriminatorNet (line 54) | class ConditionalDiscriminatorNet(torch.nn.Module):
    method __init__ (line 64) | def __init__(self, img_shape=(MNIST_IMG_SIZE, MNIST_IMG_SIZE)):
    method forward (line 75) | def forward(self, img_batch, one_hot_conditioning_vector_batch):

FILE: models/definitions/dcgan.py
  function dcgan_upsample_block (line 24) | def dcgan_upsample_block(in_channels, out_channels, normalize=True, acti...
  class ConvolutionalGenerativeNet (line 35) | class ConvolutionalGenerativeNet(nn.Module):
    method __init__ (line 37) | def __init__(self):
    method forward (line 54) | def forward(self, latent_vector_batch):
  function dcgan_downsample_block (line 63) | def dcgan_downsample_block(in_channels, out_channels, normalize=True, ac...
  class ConvolutionalDiscriminativeNet (line 71) | class ConvolutionalDiscriminativeNet(nn.Module):
    method __init__ (line 73) | def __init__(self):
    method forward (line 89) | def forward(self, img_batch):
  function weights_init_normal (line 95) | def weights_init_normal(m):

FILE: models/definitions/vanilla_gan.py
  function vanilla_block (line 17) | def vanilla_block(in_feat, out_feat, normalize=True, activation=None):
  class GeneratorNet (line 26) | class GeneratorNet(torch.nn.Module):
    method __init__ (line 41) | def __init__(self, img_shape=(MNIST_IMG_SIZE, MNIST_IMG_SIZE)):
    method forward (line 53) | def forward(self, latent_vector_batch):
  class DiscriminatorNet (line 59) | class DiscriminatorNet(torch.nn.Module):
    method __init__ (line 69) | def __init__(self, img_shape=(MNIST_IMG_SIZE, MNIST_IMG_SIZE)):
    method forward (line 79) | def forward(self, img_batch):

FILE: playground.py
  function understand_adversarial_loss (line 12) | def understand_adversarial_loss():

FILE: train_cgan.py
  function train_cgan (line 27) | def train_cgan(training_config):

FILE: train_dcgan.py
  function train_dcgan (line 27) | def train_dcgan(training_config):

FILE: train_vanilla_gan.py
  function train_vanilla_gan (line 17) | def train_vanilla_gan(training_config):

FILE: utils/constants.py
  class GANType (line 23) | class GANType(enum.Enum):

FILE: utils/utils.py
  function load_image (line 25) | def load_image(img_path, target_shape=None):
  function save_and_maybe_display_image (line 45) | def save_and_maybe_display_image(dump_dir, dump_img, out_res=(256, 256),...
  function get_available_file_name (line 64) | def get_available_file_name(input_dir):
  function get_available_binary_name (line 79) | def get_available_binary_name(gan_type_enum=GANType.VANILLA):
  function get_gan_data_transform (line 96) | def get_gan_data_transform():
  function get_mnist_dataset (line 105) | def get_mnist_dataset():
  function get_mnist_data_loader (line 110) | def get_mnist_data_loader(batch_size):
  function download_and_prepare_celeba (line 116) | def download_and_prepare_celeba(celeba_path):
  function get_celeba_data_loader (line 159) | def get_celeba_data_loader(batch_size):
  function get_gaussian_latent_batch (line 169) | def get_gaussian_latent_batch(batch_size, device):
  function get_gan (line 173) | def get_gan(device, gan_type_name):
  function get_optimizers (line 194) | def get_optimizers(d_net, g_net):
  function get_training_state (line 200) | def get_training_state(generator_net, gan_type_name):
  function print_training_info_to_console (line 209) | def print_training_info_to_console(training_config):

FILE: utils/video_utils.py
  function create_gif (line 12) | def create_gif(frames_dir, out_path, downsample=1, img_width=None):