Functions — github.com/bingchenlll/FastGAN-pytorch

hub / github.com/bingchenlll/FastGAN-pytorch / functions

Functions177 in github.com/bingchenlll/FastGAN-pytorch

⨍ Functions 177◇ Types & classes 43

↓ 23 callersFunctionconv2d

(*args, **kwargs)

models.py:21

↓ 11 callersFunctionbatchNorm2d

(*args, **kwargs)

models.py:27

↓ 9 callersMethod__init__

(self, shape)

models.py:38

↓ 8 callersFunctionload_params

(model, new_param)

operation.py:44

↓ 5 callersMethod__init__

(self, pnet_type='vgg', pnet_rand=False, pnet_tune=False, use_dropout=True, spatial=False, version='0.1', lpip

lpips/networks_basic.py:28

↓ 4 callersFunctionUpBlock

(in_planes, out_planes)

models.py:99

↓ 4 callersFunctionUpBlockComp

(in_planes, out_planes)

models.py:108

↓ 4 callersMethod__init__

Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return feature

benchmarking/benchmark.py:39

↓ 4 callersMethod__init__

Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return featur

benchmarking/inception.py:31

↓ 4 callersFunctioncopy_G_params

(model)

operation.py:39

↓ 4 callersMethodforward

(self, in0, in1, retPerLayer=None)

lpips/networks_basic.py:152

↓ 4 callersMethodsave

(self, path, label)

lpips/dist_model.py:195

↓ 3 callersMethod__init__

(self, requires_grad=False, pretrained=True)

lpips/pretrained_networks.py:99

↓ 3 callersMethodforward

Function computes the distance between image patches in0 and in1 INPUTS in0, in1 - torch.Tensor object of shape Nx3xXxY - image p

lpips/dist_model.py:109

↓ 3 callersFunctionget_dir

(args)

operation.py:49

↓ 3 callersFunctionget_late_features

(net, im_size, feat_64, feat_8, feat_16, feat_32)

scripts/style_mix.py:69

↓ 3 callersFunctionnet_generate

(netG, z, model_type='freeform', im_size=1024)

scripts/generate_video.py:63

↓ 3 callersMethodsave_network

(self, network, path, network_label, epoch_label)

lpips/base_model.py:37

↓ 2 callersFunctionDiffAugment

(x, policy='', channels_first=True)

diffaug.py:9

↓ 2 callersFunctionbatch_generate_and_save

(netG, zs, folder_name, batch_size=8, model_type='freeform', im_size=1024)

scripts/generate_video.py:79

↓ 2 callersFunctionextract_feature_from_generator_fn

(generator_fn, inception, device='cuda', total=1000)

benchmarking/benchmark.py:394

↓ 2 callersFunctionextract_features

(loader, inception, device)

benchmarking/fid.py:18

↓ 2 callersFunctionget_early_features

(net, noise)

scripts/style_mix.py:61

↓ 2 callersFunctionim2tensor

(image, imtype=np.uint8, cent=1., factor=255./2.)

lpips/__init__.py:119

↓ 2 callersFunctioninterpolate_ease_inout

(z1, z2, num_interp, ease_fn, model_type='freeform')

scripts/generate_video.py:35

↓ 2 callersFunctionload_patched_inception_v3

()

benchmarking/calc_inception.py:50

↓ 2 callersFunctionnp2tensor

(np_obj)

lpips/__init__.py:74

↓ 2 callersFunctionread_img_and_make_video

(dist, video_name, fps)

scripts/generate_video.py:113

↓ 2 callersFunctionreal_image_loader

(dataloader, n_batches=10)

benchmarking/benchmark.py:489

↓ 2 callersMethodsave

(self, label)

lpips/base_model.py:33

↓ 2 callersFunctionspatial_average

(in_tens, keepdim=True)

lpips/networks_basic.py:17

↓ 2 callersFunctiontrain_d

Train function of discriminator

train.py:35

↓ 2 callersFunctionupsample

(in_tens, out_H=64)

lpips/networks_basic.py:20

↓ 1 callersFunctionInfiniteSampler

Data sampler

operation.py:11

↓ 1 callersMethod_parse_frame

(self)

operation.py:82

↓ 1 callersMethodbackward_train

(self)

lpips/dist_model.py:162

↓ 1 callersFunctioncalc_fid

(sample_features, real_features=None, real_mean=None, real_cov=None, eps=1e-6)

benchmarking/benchmark.py:404

↓ 1 callersFunctioncalc_fid

(sample_mean, sample_cov, real_mean, real_cov, eps=1e-6)

benchmarking/fid.py:33

↓ 1 callersMethodclamp_weights

(self)

lpips/dist_model.py:127

↓ 1 callersMethodcompute_accuracy

d0, d1 are Variables, judge is a Tensor

lpips/dist_model.py:165

↓ 1 callersFunctionconvTranspose2d

(*args, **kwargs)

models.py:24

↓ 1 callersFunctioncrop_image_by_part

(image, part)

train.py:24

↓ 1 callersFunctionextract_features

(loader, inception, device)

benchmarking/calc_inception.py:60

↓ 1 callersFunctionfid_inception_v3

Build pretrained Inception model for FID computation The Inception model for FID computation uses a different set of weights and has a slightl

benchmarking/benchmark.py:171

↓ 1 callersFunctionfid_inception_v3

Build pretrained Inception model for FID computation The Inception model for FID computation uses a different set of weights and has a slight

benchmarking/inception.py:166

↓ 1 callersFunctionfind_closest

(the_image)

scripts/find_nearest_neighbor.py:52

↓ 1 callersMethodforward_train

(self)

lpips/dist_model.py:148

↓ 1 callersMethodinitialize

INPUTS model - ['net-lin'] for linearly calibrated network ['net'] for off-the-shelf network

lpips/dist_model.py:28

↓ 1 callersFunctioninterpolate

(z1, z2, netG, img_name, step=8)

scripts/train_backtracking_one.py:53

↓ 1 callersFunctioninterpolate

(z1, z2, netG, img_name, step=8)

scripts/train_backtracking_all.py:53

↓ 1 callersFunctionload_patched_inception_v3

()

benchmarking/benchmark.py:349

↓ 1 callersMethodname

(self)

lpips/dist_model.py:25

↓ 1 callersFunctionrandom_crop

(image, size)

models.py:346

↓ 1 callersFunctionresize

(img,size=256)

eval.py:21

↓ 1 callersFunctiontensor2im

(image_tensor, imtype=np.uint8, cent=1., factor=255./2.)

lpips/__init__.py:114

↓ 1 callersFunctiontensor2np

(tensor_obj)

lpips/__init__.py:70

↓ 1 callersFunctiontrain

(args)

train.py:53

↓ 1 callersFunctiontrain

(args)

scripts/train_backtracking_one.py:60

↓ 1 callersFunctiontrain

(args)

scripts/train_backtracking_all.py:60

(self, root, transform=None)

operation.py:75

Method__init__

(self, path, transform, resolution=256)

(self, ch_in, ch_out)

(self, ngf=64, nz=100, nc=3, im_size=1024)

models.py:123

Method__init__

(self, in_planes, out_planes)

models.py:184

Method__init__

(self, in_planes, out_planes)

models.py:197

Method__init__

(self, ndf=64, nc=3, im_size=512)

models.py:217

Method__init__

(self, nfc_in=64, nc=3)

models.py:318

Method__init__

(self, ndf=64, nc=3, im_size=512)

models.py:353

Method__init__

(self)

lpips/base_model.py:8

Method__init__

(self, model='net-lin', net='alex', colorspace='rgb', spatial=False, use_gpu=True, gpu_ids=[0])

lpips/__init__.py:22

Method__init__

(self, requires_grad=False, pretrained=True)

lpips/pretrained_networks.py:8

Method__init__

(self, requires_grad=False, pretrained=True)

lpips/pretrained_networks.py:59

Method__init__

(self, requires_grad=False, pretrained=True, num=18)

lpips/pretrained_networks.py:141

Method__init__

(self)

lpips/networks_basic.py:95

Method__init__

(self, chn_in, chn_out=1, use_dropout=False)

lpips/networks_basic.py:106

Method__init__

(self, chn_mid=32, use_sigmoid=True)

lpips/networks_basic.py:116

Method__init__

(self, chn_mid=32)

lpips/networks_basic.py:132

Method__init__

(self, use_gpu=True, colorspace='Lab')

lpips/networks_basic.py:145

Method__init__

(self, in_channels, pool_features)

benchmarking/benchmark.py:198

Method__init__

(self, in_channels, channels_7x7)

benchmarking/benchmark.py:223

Method__init__

(self, in_channels)

benchmarking/benchmark.py:251

Method__init__

(self, in_channels)

benchmarking/benchmark.py:284

Method__init__

(self, in_channels, pool_features)

benchmarking/inception.py:195

Method__init__

(self, in_channels, channels_7x7)

benchmarking/inception.py:220

Method__init__

(self, in_channels)

benchmarking/inception.py:248

Method__init__

(self, in_channels)

benchmarking/inception.py:281

Functionbatch_generate

(zs, netG, batch=8)

eval.py:24

Functionbatch_save

(images, folder_name)

eval.py:33

Functionbatch_save

(images, folder_name, start_num=0)

scripts/generate_video.py:105

Functioncrop_image_by_part

(image, part)

scripts/train_backtracking_one.py:24

Functioncrop_image_by_part

(image, part)

scripts/train_backtracking_all.py:24

next →1–100 of 177, ranked by callers