Functions — github.com/carpedm20/BEGAN-tensorflow

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Functions60 in github.com/carpedm20/BEGAN-tensorflow

⨍ Functions 60 ◇ Types & classes 6

↓ 10 callersFunctionsave_image

(tensor, filename, nrow=8, padding=2, normalize=False, scale_each=False)

↓ 4 callersFunctionadd_argument_group

↓ 3 callersMethodautoencode

(self, inputs, path, idx=None, x_fake=None)

↓ 3 callersFunctioncheck_link

(in_dir, basename, out_dir)

↓ 3 callersFunctiondenorm_img

(norm, data_format)

↓ 3 callersMethodgenerate

(self, inputs, root_path=None, path=None, idx=None, save=True)

↓ 3 callersMethodget_image_from_loader

↓ 2 callersFunctionGeneratorCNN

(z, hidden_num, output_num, repeat_num, data_format, reuse)

↓ 2 callersMethodencode

↓ 2 callersFunctionget_conv_shape

(tensor, data_format)

↓ 2 callersFunctionnchw_to_nhwc

↓ 2 callersFunctionreshape

(x, h, w, c, data_format)

↓ 2 callersFunctionslerp

Code from https://github.com/soumith/dcgan.torch/issues/14

↓ 2 callersFunctionto_nhwc

(image, data_format)

↓ 2 callersFunctionunboxn

vin = (batch, h, w, depth), returns vout = (batch, n*h, n*w, depth), each pixel is duplicated.

↓ 2 callersFunctionupscale

(x, scale, data_format)

↓ 1 callersFunctionDiscriminatorCNN

(x, input_channel, z_num, repeat_num, hidden_num, data_format)

↓ 1 callersFunctionadd_splits

↓ 1 callersMethodbuild_model

↓ 1 callersMethodbuild_test_model

↓ 1 callersMethoddecode

↓ 1 callersFunctiondownload_celeb_a

↓ 1 callersFunctiondownload_file_from_google_drive

(id, destination)

↓ 1 callersFunctionget_config

↓ 1 callersFunctionget_confirm_token

↓ 1 callersFunctionget_loader

(root, batch_size, scale_size, data_format, split=None, is_grayscale=False, seed=None)

data_loader.py:6

↓ 1 callersFunctionget_time

↓ 1 callersFunctionint_shape

↓ 1 callersMethodinterpolate_G

(self, real_batch, step=0, root_path='.', train_epoch=0)

↓ 1 callersFunctionis_image_file

↓ 1 callersFunctionmain

↓ 1 callersFunctionmake_dataset

↓ 1 callersFunctionmake_grid

Code based on https://github.com/pytorch/vision/blob/master/torchvision/utils.py

↓ 1 callersFunctionnhwc_to_nchw

↓ 1 callersFunctionnorm_img

(image, data_format=None)

↓ 1 callersFunctionprepare_data_dir

(path = './data')

↓ 1 callersFunctionprepare_dirs_and_logger

↓ 1 callersFunctionresize_nearest_neighbor

(x, new_size, data_format)

↓ 1 callersFunctionsave_config

↓ 1 callersFunctionsave_response_content

(response, destination, chunk_size=32*1024)

↓ 1 callersMethodtest

↓ 1 callersFunctionto_nchw_numpy

↓ 1 callersMethodtrain

(self, vin, carry=0, train=True)

(self, data, carry, train=True)

Method__getitem__

w = (wy, wx), n = (n_in, n_out)

(self, name, n, width, colors, depth, scales, nl=lambda x, y: x + y, data_format="NCHW")

(self, name, n, width, colors, depth, scales, nl=lambda x, y: x + y, data_format="NCHW")

(self, root, transform=None, target_transform=None, loader=default_loader)

(self, config, data_loader)

vin = (batch, h, w, depth), returns vout = (batch, h//n, w//n, depth), each pixel is averaged.

Functiondefault_loader

Methodinterpolate_D

(self, real1_batch, real2_batch, step=0, root_path=".")

Functionstr2bool