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Types & classes52 in github.com/ajbrock/BigGAN-PyTorch

↓ 22 callersClassGBlock
TFHub/biggan_v1.py:131
↓ 20 callersClassSpectralNorm
TFHub/biggan_v1.py:27
↓ 4 callersClassSelfAttention
Self Attention Layer
TFHub/biggan_v1.py:81
↓ 3 callersClassDistribution
utils.py:1059
↓ 2 callersClassConditionalBatchNorm2d
TFHub/biggan_v1.py:115
↓ 2 callersClassmyBN
layers.py:212
↓ 1 callersClassCallbackContext
sync_batchnorm/replicate.py:23
↓ 1 callersClassCenterCropLongEdge
Crops the given PIL Image on the long edge. Args: size (sequence or int): Desired output size of the crop. If size is an int instead
utils.py:434
↓ 1 callersClassDBlock
BigGANdeep.py:283
↓ 1 callersClassFutureResult
A thread-safe future implementation. Used only as one-to-one pipe.
sync_batchnorm/comm.py:18
↓ 1 callersClassGBlock
BigGANdeep.py:23
↓ 1 callersClassMultiEpochSampler
r"""Samples elements randomly over multiple epochs Arguments: data_source (Dataset): dataset to sample from num_epochs (int) : Number o
utils.py:481
↓ 1 callersClassRandomCropLongEdge
Crops the given PIL Image on the long edge with a random start point. Args: size (sequence or int): Desired output size of the crop. If size i
utils.py:453
↓ 1 callersClassSlavePipe
Pipe for master-slave communication.
sync_batchnorm/comm.py:46
↓ 1 callersClassSyncMaster
An abstract `SyncMaster` object. - During the replication, as the data parallel will trigger an callback of each module, all slave devices should
sync_batchnorm/comm.py:56
↓ 1 callersClassTFHub2Pytorch
TFHub/converter.py:80
↓ 1 callersClassWrapInception
inception_utils.py:27
ClassAdam16
utils.py:1128
ClassAttention
layers.py:144
ClassBatchNorm2dReimpl
A re-implementation of batch normalization, used for testing the numerical stability. Author: acgtyrant See also: https://github
sync_batchnorm/batchnorm_reimpl.py:18
ClassCIFAR10
datasets.py:243
ClassCIFAR100
datasets.py:351
ClassDBlock
layers.py:412
ClassDataParallelWithCallback
Data Parallel with a replication callback. An replication callback `__data_parallel_replicate__` of each module will be invoked after being
sync_batchnorm/replicate.py:50
ClassDiscriminator
BigGAN.py:283
ClassDiscriminator
BigGANdeep.py:359
ClassDiscriminator
TFHub/biggan_v1.py:339
ClassGBlock
layers.py:375
ClassG_D
BigGAN.py:408
ClassG_D
BigGANdeep.py:492
ClassGenerator
BigGAN.py:54
ClassGenerator
BigGANdeep.py:96
ClassGenerator128
TFHub/biggan_v1.py:197
ClassGenerator256
TFHub/biggan_v1.py:244
ClassGenerator512
TFHub/biggan_v1.py:290
ClassILSVRC_HDF5
datasets.py:184
ClassImageFolder
A generic data loader where the images are arranged in this way: :: root/dogball/xxx.png root/dogball/xxy.png root/dogball/xxz.
datasets.py:82
ClassMetricsLogger
utils.py:744
ClassMyLogger
utils.py:771
ClassSN
layers.py:60
ClassSNConv2d
layers.py:103
ClassSNEmbedding
layers.py:128
ClassSNLinear
layers.py:116
ClassSynchronizedBatchNorm1d
r"""Applies Synchronized Batch Normalization over a 2d or 3d input that is seen as a mini-batch. .. math:: y = \frac{x - mean[x]}{ \
sync_batchnorm/batchnorm.py:162
ClassSynchronizedBatchNorm2d
r"""Applies Batch Normalization over a 4d input that is seen as a mini-batch of 3d inputs .. math:: y = \frac{x - mean[x]}{ \sqrt{Va
sync_batchnorm/batchnorm.py:225
ClassSynchronizedBatchNorm3d
r"""Applies Batch Normalization over a 5d input that is seen as a mini-batch of 4d inputs .. math:: y = \frac{x - mean[x]}{ \sqrt{Va
sync_batchnorm/batchnorm.py:288
ClassTorchTestCase
sync_batchnorm/unittest.py:15
Class_SynchronizedBatchNorm
sync_batchnorm/batchnorm.py:38
Classbn
layers.py:333
Classccbn
layers.py:278
Classema
utils.py:614
Classidentity
layers.py:54