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Types & classes95 in github.com/NVlabs/few-shot-vid2vid

↓ 15 callersClassResample2d
models/networks/flownet2_pytorch/networks/resample2d_package/resample2d.py:38
↓ 8 callersClasstofp16
models/networks/flownet2_pytorch/networks/submodules.py:40
↓ 8 callersClasstofp32
models/networks/flownet2_pytorch/networks/submodules.py:48
↓ 6 callersClassSPADEConv2d
models/networks/architecture.py:57
↓ 5 callersClassStaticCenterCrop
models/networks/flownet2_pytorch/datasets.py:23
↓ 5 callersClassStaticRandomCrop
models/networks/flownet2_pytorch/datasets.py:13
↓ 3 callersClassChannelNorm
models/networks/flownet2_pytorch/networks/channelnorm_package/channelnorm.py:31
↓ 3 callersClassLabelEmbedder
models/networks/generator.py:506
↓ 2 callersClassCorrelation
models/networks/flownet2_pytorch/networks/correlation_package/correlation.py:55
↓ 2 callersClassFlowGenerator
models/networks/generator.py:456
↓ 2 callersClassL1
models/networks/flownet2_pytorch/losses.py:14
↓ 2 callersClassL2
models/networks/flownet2_pytorch/losses.py:21
↓ 2 callersClassNLayerDiscriminator
models/networks/discriminator.py:61
↓ 2 callersClassSPADEResnetBlock
models/networks/architecture.py:71
↓ 2 callersClassSynchronizedBatchNorm2d
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
models/networks/sync_batchnorm/batchnorm.py:191
↓ 2 callersClassVisualizer
util/visualizer.py:19
↓ 1 callersClassAdaptiveDiscriminator
models/networks/discriminator.py:104
↓ 1 callersClassCallbackContext
models/networks/sync_batchnorm/replicate.py:30
↓ 1 callersClassColorize
util/util.py:208
↓ 1 callersClassCustomDatasetDataLoader
data/custom_dataset_data_loader.py:12
↓ 1 callersClassDataParallelWithCallback
Data Parallel with a replication callback. An replication callback `__data_parallel_replicate__` of each module will be invoked after being
models/networks/sync_batchnorm/replicate.py:57
↓ 1 callersClassFaceRefineModel
models/face_refiner.py:12
↓ 1 callersClassFewShotGenerator
models/networks/generator.py:20
↓ 1 callersClassFlowNet
models/flownet.py:15
↓ 1 callersClassFutureResult
A thread-safe future implementation. Used only as one-to-one pipe.
models/networks/sync_batchnorm/comm.py:18
↓ 1 callersClassHTML
util/html.py:13
↓ 1 callersClassImagePool
util/image_pool.py:10
↓ 1 callersClassLossCollector
models/loss_collector.py:15
↓ 1 callersClassModelAndLoss
models/networks/flownet2_pytorch/main.py:161
↓ 1 callersClassMultiscaleDiscriminator
models/networks/discriminator.py:16
↓ 1 callersClassMyDict
models/networks/flownet2_pytorch/models.py:19
↓ 1 callersClassMyModel
models/models.py:79
↓ 1 callersClassMyPlaylist
data/preprocess/download_youTube_playlist.py:6
↓ 1 callersClassSlavePipe
Pipe for master-slave communication.
models/networks/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
models/networks/sync_batchnorm/comm.py:56
↓ 1 callersClassTestOptions
options/test_options.py:9
↓ 1 callersClassTrainOptions
options/train_options.py:9
↓ 1 callersClassTrainer
models/trainer.py:22
↓ 1 callersClassVGG_Activations
models/networks/vgg.py:45
↓ 1 callersClassVid2VidModel
models/vid2vid_model.py:20
ClassAdaptiveConv2d
models/networks/architecture.py:31
ClassBaseDataLoader
data/base_data_loader.py:7
ClassBaseDataset
data/base_dataset.py:12
ClassBaseModel
models/base_model.py:15
ClassBaseNetwork
models/networks/base_network.py:73
ClassBaseOptions
options/base_options.py:17
ClassChairsSDHom
models/networks/flownet2_pytorch/datasets.py:250
ClassChairsSDHomTest
models/networks/flownet2_pytorch/datasets.py:316
ClassChairsSDHomTrain
models/networks/flownet2_pytorch/datasets.py:312
ClassChannelNormFunction
models/networks/flownet2_pytorch/networks/channelnorm_package/channelnorm.py:5
ClassConvN
models/networks/discriminator.py:171
ClassCorrelationFunction
models/networks/flownet2_pytorch/networks/correlation_package/correlation.py:6
ClassDataParallel
models/networks/sync_batchnorm/replicate.py:24
ClassFewshotFaceDataset
data/fewshot_face_dataset.py:17
ClassFewshotPoseDataset
data/fewshot_pose_dataset.py:19
ClassFewshotStreetDataset
data/fewshot_street_dataset.py:16
ClassFlowNet2
models/networks/flownet2_pytorch/models.py:22
ClassFlowNet2C
models/networks/flownet2_pytorch/models.py:184
ClassFlowNet2CS
models/networks/flownet2_pytorch/models.py:350
ClassFlowNet2CSS
models/networks/flownet2_pytorch/models.py:415
ClassFlowNet2S
models/networks/flownet2_pytorch/models.py:252
ClassFlowNet2SD
models/networks/flownet2_pytorch/models.py:298
ClassFlowNetC
models/networks/flownet2_pytorch/networks/FlowNetC.py:13
ClassFlowNetFusion
models/networks/flownet2_pytorch/networks/FlowNetFusion.py:11
ClassFlowNetS
models/networks/flownet2_pytorch/networks/FlowNetS.py:15
ClassFlowNetSD
models/networks/flownet2_pytorch/networks/FlowNetSD.py:11
ClassFlyingChairs
models/networks/flownet2_pytorch/datasets.py:114
ClassFlyingThings
models/networks/flownet2_pytorch/datasets.py:175
ClassFlyingThingsClean
models/networks/flownet2_pytorch/datasets.py:242
ClassFlyingThingsFinal
models/networks/flownet2_pytorch/datasets.py:246
ClassGANLoss
models/networks/loss.py:17
ClassImageFolder
data/image_folder.py:92
ClassImagesFromFolder
models/networks/flownet2_pytorch/datasets.py:320
ClassIteratorTimer
models/networks/flownet2_pytorch/utils/tools.py:98
ClassKLDLoss
models/networks/loss.py:140
ClassL1Loss
models/networks/flownet2_pytorch/losses.py:28
ClassL2Loss
models/networks/flownet2_pytorch/losses.py:40
ClassLMDBDataset
data/lmdb_dataset.py:16
ClassMaskedL1Loss
models/networks/loss.py:130
ClassMpiSintel
models/networks/flownet2_pytorch/datasets.py:30
ClassMpiSintelClean
models/networks/flownet2_pytorch/datasets.py:106
ClassMpiSintelFinal
models/networks/flownet2_pytorch/datasets.py:110
ClassMultiScale
models/networks/flownet2_pytorch/losses.py:52
ClassNormalConv2d
models/networks/architecture.py:20
ClassNormalConvTranspose2d
models/networks/architecture.py:25
ClassNormalNorm
models/networks/architecture.py:50
ClassResample2dFunction
models/networks/flownet2_pytorch/networks/resample2d_package/resample2d.py:5
ClassSPADE
models/networks/normalization.py:18
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]}{ \
models/networks/sync_batchnorm/batchnorm.py:128
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
models/networks/sync_batchnorm/batchnorm.py:254
ClassTimerBlock
models/networks/flownet2_pytorch/utils/tools.py:24
ClassTorchTestCase
models/networks/sync_batchnorm/unittest.py:23
ClassVGGLoss
models/networks/loss.py:107
ClassVgg19
models/networks/vgg.py:13
Class_SynchronizedBatchNorm
models/networks/sync_batchnorm/batchnorm.py:38