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Types & classes139 in github.com/VITA-Group/TransGAN

⨍ Functions 560◇ Types & classes 139
↓ 18 callersClassDropPath
Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
models_search/ViT_helper.py:22
↓ 6 callersClassStageBlock
models_search/ViT_custom_local544444_256_rp_noise.py:163
↓ 6 callersClassStageBlock
models_search/ViT_custom_local544444_256_rp.py:156
↓ 5 callersClassCustomNorm
models_search/ViT_custom_scale2.py:145
↓ 5 callersClassCustomNorm
models_search/ViT_custom_rp.py:121
↓ 5 callersClassCustomNorm
models_search/Celeba256_dis.py:161
↓ 5 callersClassCustomNorm
models_search/ViT_scale3_local_new_rp.py:145
↓ 5 callersClassCustomNorm
models_search/ViT_custom_scale2_rp_noise.py:148
↓ 5 callersClassCustomNorm
models_search/ViT_custom_local544444_256_rp_noise.py:124
↓ 5 callersClassCustomNorm
models_search/ViT_custom_local544444_256_rp.py:117
↓ 5 callersClassCustomNorm
models_search/Celeba256_gen.py:169
↓ 5 callersClassCustomNorm
models_search/ViT_custom.py:101
↓ 5 callersClassDisBlock
models_search/ViT_scale3_local_new_rp.py:388
↓ 5 callersClassStageBlock
models_search/Celeba256_gen.py:220
↓ 4 callersClassDisBlock
models_search/Celeba256_dis.py:404
↓ 4 callersClassDisBlock
models_search/ViT_custom_local544444_256_rp_noise.py:456
↓ 4 callersClassDisBlock
models_search/ViT_custom_local544444_256_rp.py:449
↓ 4 callersClassDisBlock
models_search/Celeba256_gen.py:533
↓ 4 callersClassFIDInceptionC
InceptionC block patched for FID computation
utils/inception_model.py:214
↓ 4 callersClassFIDInceptionC
InceptionC block patched for FID computation
utils/inception.py:215
↓ 3 callersClassDisBlock
models_search/ViT_custom_scale2.py:388
↓ 3 callersClassDisBlock
models_search/ViT_custom_scale2_rp_noise.py:395
↓ 3 callersClassFIDInceptionA
InceptionA block patched for FID computation
utils/inception_model.py:188
↓ 3 callersClassFIDInceptionA
InceptionA block patched for FID computation
utils/inception.py:189
↓ 3 callersClassStageBlock
models_search/ViT_custom_scale2.py:218
↓ 3 callersClassStageBlock
models_search/ViT_custom_rp.py:162
↓ 3 callersClassStageBlock
models_search/Celeba256_dis.py:234
↓ 3 callersClassStageBlock
models_search/ViT_scale3_local_new_rp.py:218
↓ 3 callersClassStageBlock
models_search/ViT_custom_scale2_rp_noise.py:221
↓ 3 callersClassStageBlock
models_search/ViT_custom.py:142
↓ 2 callersClassAdamW
r"""Implements AdamW algorithm. The original Adam algorithm was proposed in `Adam: A Method for Stochastic Optimization`_. The AdamW variant
adamw.py:9
↓ 2 callersClassAttention
models_search/ViT_custom_scale2.py:95
↓ 2 callersClassAttention
models_search/ViT_custom_rp.py:71
↓ 2 callersClassAttention
models_search/Celeba256_dis.py:97
↓ 2 callersClassAttention
models_search/ViT_scale3_local_new_rp.py:95
↓ 2 callersClassAttention
models_search/ViT_custom_scale2_rp_noise.py:95
↓ 2 callersClassAttention
models_search/ViT_custom_local544444_256_rp_noise.py:70
↓ 2 callersClassAttention
models_search/ViT_custom_local544444_256_rp.py:66
↓ 2 callersClassAttention
models_search/Celeba256_gen.py:115
↓ 2 callersClassAttention
models_search/ViT_custom.py:71
↓ 2 callersClassBlock
models_search/Celeba256_dis.py:215
↓ 2 callersClassBlock
models_search/ViT_custom_local544444_256_rp_noise.py:146
↓ 2 callersClassBlock
models_search/ViT_custom_local544444_256_rp.py:139
↓ 2 callersClassBlock
models_search/Celeba256_gen.py:191
↓ 2 callersClassLinearLrDecay
functions.py:397
↓ 2 callersClassMlp
models_search/ViT_custom_scale2.py:76
↓ 2 callersClassMlp
models_search/ViT_custom_rp.py:52
↓ 2 callersClassMlp
models_search/Celeba256_dis.py:78
↓ 2 callersClassMlp
models_search/ViT_scale3_local_new_rp.py:76
↓ 2 callersClassMlp
models_search/ViT_custom_scale2_rp_noise.py:76
↓ 2 callersClassMlp
models_search/ViT_custom_local544444_256_rp_noise.py:47
↓ 2 callersClassMlp
models_search/ViT_custom_local544444_256_rp.py:47
↓ 2 callersClassMlp
models_search/Celeba256_gen.py:50
↓ 2 callersClassMlp
models_search/ViT_custom.py:52
↓ 2 callersClassmatmul
models_search/Celeba256_gen.py:10
↓ 2 callersClasssuppress_tracer_warnings
torch_utils/misc.py:69
↓ 1 callersClassBlock
models_search/ViT_custom_scale2.py:199
↓ 1 callersClassBlock
models_search/ViT_custom_rp.py:143
↓ 1 callersClassBlock
models_search/ViT_scale3_local_new_rp.py:199
↓ 1 callersClassBlock
models_search/ViT_custom_scale2_rp_noise.py:202
↓ 1 callersClassBlock
models_search/ViT_custom.py:123
↓ 1 callersClassCrossAttention
models_search/Celeba256_gen.py:71
↓ 1 callersClassCustomAct
models_search/ViT_custom_scale2.py:65
↓ 1 callersClassCustomAct
models_search/ViT_custom_rp.py:41
↓ 1 callersClassCustomAct
models_search/Celeba256_dis.py:67
↓ 1 callersClassCustomAct
models_search/ViT_scale3_local_new_rp.py:65
↓ 1 callersClassCustomAct
models_search/ViT_custom_scale2_rp_noise.py:65
↓ 1 callersClassCustomAct
models_search/ViT_custom_local544444_256_rp_noise.py:36
↓ 1 callersClassCustomAct
models_search/ViT_custom_local544444_256_rp.py:36
↓ 1 callersClassCustomAct
models_search/Celeba256_gen.py:39
↓ 1 callersClassCustomAct
models_search/ViT_custom.py:41
↓ 1 callersClassDisBlock
models_search/ViT_custom_rp.py:322
↓ 1 callersClassDisBlock
models_search/ViT_custom.py:298
↓ 1 callersClassFIDInceptionE_1
First InceptionE block patched for FID computation
utils/inception_model.py:243
↓ 1 callersClassFIDInceptionE_1
First InceptionE block patched for FID computation
utils/inception.py:244
↓ 1 callersClassFIDInceptionE_2
Second InceptionE block patched for FID computation
utils/inception_model.py:277
↓ 1 callersClassFIDInceptionE_2
Second InceptionE block patched for FID computation
utils/inception.py:278
↓ 1 callersClassInceptionV3
Pretrained InceptionV3 network returning feature maps
utils/inception.py:16
↓ 1 callersClassPixelNorm
models_search/ViT_custom_scale2.py:47
↓ 1 callersClassPixelNorm
models_search/ViT_custom_rp.py:23
↓ 1 callersClassPixelNorm
models_search/Celeba256_dis.py:49
↓ 1 callersClassPixelNorm
models_search/ViT_scale3_local_new_rp.py:47
↓ 1 callersClassPixelNorm
models_search/ViT_custom_scale2_rp_noise.py:47
↓ 1 callersClassPixelNorm
models_search/ViT_custom_local544444_256_rp_noise.py:22
↓ 1 callersClassPixelNorm
models_search/ViT_custom_local544444_256_rp.py:22
↓ 1 callersClassPixelNorm
models_search/Celeba256_gen.py:22
↓ 1 callersClassPixelNorm
models_search/ViT_custom.py:23
↓ 1 callersClassmatmul
models_search/ViT_custom_scale2.py:34
↓ 1 callersClassmatmul
models_search/ViT_custom_rp.py:10
↓ 1 callersClassmatmul
models_search/Celeba256_dis.py:36
↓ 1 callersClassmatmul
models_search/ViT_scale3_local_new_rp.py:34
↓ 1 callersClassmatmul
models_search/ViT_custom_scale2_rp_noise.py:34
↓ 1 callersClassmatmul
models_search/ViT_custom_local544444_256_rp_noise.py:10
↓ 1 callersClassmatmul
models_search/ViT_custom_local544444_256_rp.py:10
↓ 1 callersClassmatmul
models_search/ViT_custom.py:10
ClassBiasActCuda
torch_utils/ops/bias_act.py:145
ClassBiasActCudaGrad
torch_utils/ops/bias_act.py:178
ClassCelebA
pyTorch Dataset wrapper for the generic flat directory images dataset
celeba.py:18
ClassCollector
r"""Collects the scalars broadcasted by `report()` and `report0()` and computes their long-term averages (mean and standard deviation) over us
torch_utils/training_stats.py:113
ClassConv2d
torch_utils/ops/conv2d_gradfix.py:107
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