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Functions197 in github.com/HobbitLong/PyContrast

⨍ Functions 197◇ Types & classes 47
Method__init__
(self, inplanes, planes, stride=1, downsample=None, groups=1, base_width=64, dilation=1, norm
pycontrast/networks/resnet.py:89
Method__init__
(self, K=65536, T=0.07, m=0.5)
pycontrast/memory/mem_bank.py:9
Method__init__
(self, n_dim, n_data, K=65536, T=0.07, m=0.5)
pycontrast/memory/mem_bank.py:95
Method__init__
(self, probs)
pycontrast/memory/alias_multinomial.py:8
Method__init__
(self, K=65536, T=0.07)
pycontrast/memory/mem_moco.py:8
Method__init__
(self, n_dim, K=65536, T=0.07)
pycontrast/memory/mem_moco.py:93
Method__init__
(self)
pycontrast/options/base_options.py:7
Method__init__
(self, root, transform=None, target_transform=None, two_crop=False, jigsaw_transform=None)
pycontrast/datasets/dataset.py:11
Method__init__
(self, transform)
pycontrast/datasets/util.py:18
Method__init__
(self, n_grid=3, img_size=255, crop_size=64)
pycontrast/datasets/util.py:27
Method__init__
(self, angles=[0, 90, 180, 270])
pycontrast/datasets/util.py:52
Method__init__
(self, kernel_size)
pycontrast/datasets/util.py:126
Method__init__
(self, kernel_size, use_cuda=False, p=0.5)
pycontrast/datasets/util.py:176
Method__init__
(self, name, prob=0.5, magnitude=10, hparams=None)
pycontrast/datasets/RandAugment.py:283
Method__init__
(self, ops, num_layers=2, choice_weights=None)
pycontrast/datasets/RandAugment.py:391
Method__init__
(self, args)
pycontrast/learning/base_trainer.py:14
Method__init__
(self, args)
pycontrast/learning/contrast_trainer.py:21
Method__init__
(self, args)
pycontrast/learning/linear_trainer.py:16
Method__init__
(self)
pycontrast/learning/util.py:8
Function_enhance_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:178
Function_posterize_original_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:204
Function_posterize_research_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:210
Function_posterize_tpu_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:216
Function_rotate_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:171
Function_shear_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:183
Function_solarize_add_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:227
Function_solarize_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:222
Function_translate_abs_level_to_arg
(level, hparams)
pycontrast/datasets/RandAugment.py:190
Function_translate_rel_level_to_arg
(level, _hparams)
pycontrast/datasets/RandAugment.py:197
Methodacc
(l, t)
pycontrast/learning/contrast_trainer.py:212
Functionauto_contrast
(img, **__)
pycontrast/datasets/RandAugment.py:109
Functionbrightness
(img, factor, **__)
pycontrast/datasets/RandAugment.py:158
Functioncolor
(img, factor, **__)
pycontrast/datasets/RandAugment.py:154
Functionequalize
(img, **__)
pycontrast/datasets/RandAugment.py:121
Methodforward
(self, x)
pycontrast/networks/resnest.py:52
Methodforward
(self, inputs)
pycontrast/networks/resnest.py:92
Methodforward
(self, x)
pycontrast/networks/resnest.py:162
Methodforward
(self, x)
pycontrast/networks/resnest.py:355
Methodforward
(self, x, mode=0)
pycontrast/networks/build_backbone.py:43
Methodforward
(self, x, x_jig=None, mode=0)
pycontrast/networks/build_backbone.py:63
Methodforward
(self, x, mode=0)
pycontrast/networks/build_backbone.py:127
Methodforward
(self, x, x_jig=None, mode=0)
pycontrast/networks/build_backbone.py:153
Methodforward
(self, x)
pycontrast/networks/util.py:11
Methodforward
(self, x)
pycontrast/networks/util.py:34
Methodforward
(self, x)
pycontrast/networks/resnet_cmc.py:31
Methodforward
(self, x)
pycontrast/networks/resnet_cmc.py:50
Methodforward
(self, x)
pycontrast/networks/resnet_cmc.py:85
Methodforward
(self, x)
pycontrast/networks/resnet_cmc.py:154
Methodforward
(self, x)
pycontrast/networks/resnet.py:61
Methodforward
(self, x)
pycontrast/networks/resnet.py:106
Methodforward
(self, x)
pycontrast/networks/resnet.py:209
Methodforward
Args: x: feat on current node y: index on current node x_jig: jigsaw feat on current node all_x: gath
pycontrast/memory/mem_bank.py:55
Methodforward
Args: x1: feat of modal 1 x2: feat of modal 2 y: index on current node x1_jig: jigsaw feat of modal1
pycontrast/memory/mem_bank.py:107
Methodforward
Args: q: query on current node k: key on current node q_jig: jigsaw query all_k: gather of feats acro
pycontrast/memory/mem_moco.py:60
Methodforward
Args: q1: q of modal 1 k1: k of modal 1 q2: q of modal 2 k2: k of modal 2 q1_jig: q jig of
pycontrast/memory/mem_moco.py:101
Functionidentity
(img, **__)
pycontrast/datasets/RandAugment.py:117
Methodinitialize
(self, parser)
pycontrast/options/train_options.py:8
Methodinitialize
(self, parser)
pycontrast/options/test_options.py:7
Functioninvert
(img, **__)
pycontrast/datasets/RandAugment.py:113
Functionmain_worker
(gpu, ngpus_per_node, args)
pycontrast/main_contrast.py:31
Functionmain_worker
(gpu, ngpus_per_node, args)
pycontrast/main_linear.py:30
Methodmodify_options
(self, opt)
pycontrast/options/train_options.py:24
Methodmodify_options
(self, opt)
pycontrast/options/test_options.py:28
Functionposterize
(img, bits_to_keep, **__)
pycontrast/datasets/RandAugment.py:144
Functionresnest101
(pretrained=False, **kwargs)
pycontrast/networks/resnest.py:386
Functionresnest200
(pretrained=False, **kwargs)
pycontrast/networks/resnest.py:396
Functionresnest269
(pretrained=False, **kwargs)
pycontrast/networks/resnest.py:406
Functionresnest50
(pretrained=False, **kwargs)
pycontrast/networks/resnest.py:376
Functionresnet101
Constructs a ResNet-101 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet
pycontrast/networks/resnet_cmc.py:209
Functionresnet101
r"""ResNet-101 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b
pycontrast/networks/resnet.py:268
Functionresnet152
Constructs a ResNet-152 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet
pycontrast/networks/resnet_cmc.py:220
Functionresnet152
r"""ResNet-152 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (b
pycontrast/networks/resnet.py:279
Functionresnet18
Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet
pycontrast/networks/resnet_cmc.py:176
Functionresnet18
r"""ResNet-18 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (bo
pycontrast/networks/resnet.py:235
Functionresnet34
Constructs a ResNet-34 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet
pycontrast/networks/resnet_cmc.py:187
Functionresnet34
r"""ResNet-34 model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (bo
pycontrast/networks/resnet.py:246
Functionresnet50
Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet
pycontrast/networks/resnet_cmc.py:198
Functionresnext101_32x4d
r"""ResNeXt-101 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:303
Functionresnext101_32x8d
r"""ResNeXt-101 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:316
Functionresnext101_64x4d
r"""ResNeXt-101 64x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:329
Functionresnext152_32x4d
r"""ResNeXt-152 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:342
Functionresnext152_32x8d
r"""ResNeXt-152 32x8d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:355
Functionresnext152_64x4d
r"""ResNeXt-152 64x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:368
Functionresnext50_32x4d
r"""ResNeXt-50 32x4d model from `"Aggregated Residual Transformation for Deep Neural Networks" <https://arxiv.org/pdf/1611.05431.pdf>`_ Args:
pycontrast/networks/resnet.py:290
Functionrotate
(img, degrees, **kwargs)
pycontrast/datasets/RandAugment.py:77
Methodset_bn_train
(m)
pycontrast/learning/contrast_trainer.py:230
Functionsharpness
(img, factor, **__)
pycontrast/datasets/RandAugment.py:162
Functionshear_x
(img, factor, **kwargs)
pycontrast/datasets/RandAugment.py:45
Functionshear_y
(img, factor, **kwargs)
pycontrast/datasets/RandAugment.py:50
Functionsolarize
(img, thresh, **__)
pycontrast/datasets/RandAugment.py:125
Functionsolarize_add
(img, add, thresh=128, **__)
pycontrast/datasets/RandAugment.py:129
Functiontranslate_x_abs
(img, pixels, **kwargs)
pycontrast/datasets/RandAugment.py:67
Functiontranslate_x_rel
(img, pct, **kwargs)
pycontrast/datasets/RandAugment.py:55
Functiontranslate_y_abs
(img, pixels, **kwargs)
pycontrast/datasets/RandAugment.py:72
Functiontranslate_y_rel
(img, pct, **kwargs)
pycontrast/datasets/RandAugment.py:61
Functionwide_resnet101_2
r"""Wide ResNet-101-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ The model is the same as ResNet except for
pycontrast/networks/resnet.py:397
Functionwide_resnet50_2
r"""Wide ResNet-50-2 model from `"Wide Residual Networks" <https://arxiv.org/pdf/1605.07146.pdf>`_ The model is the same as ResNet except for
pycontrast/networks/resnet.py:381
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