MCPcopy Create free account

hub / github.com/Sirwenhao/Deep-Learning-Notes / functions

Functions321 in github.com/Sirwenhao/Deep-Learning-Notes

⨍ Functions 321◇ Types & classes 74
↓ 24 callersFunction_mcfg
(**kwargs)
CV/Pytorch_classification/RegNet/model.py:20
↓ 14 callersMethodupdate
(self, preds, labels)
CV/Pytorch_classification/ConfusionMatrix/main.py:18
↓ 11 callersMethodbackward
(ctx, grad_output)
CV/Pytorch_classification/CRNN_PyTorch/warpctc_pytorch.py:42
↓ 7 callersMethodcomplexity
(self, cx)
CV/Pytorch_classification/model_complexity/model.py:200
↓ 5 callersMethod__init__
(self, kernel_size: int, input_c: int, out_c: int,
CV/Pytorch_classification/model_complexity/model.py:134
↓ 5 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
CV/Pytorch_classification/vision_transformer/vit_model.py:85
↓ 5 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
CV/Pytorch_classification/grad_cam/vit_model.py:77
↓ 5 callersMethod__init__
(self, cfg: dict, in_c: int = 3, num_classes: int = 1000,
CV/Pytorch_classification/RegNet/model.py:226
↓ 4 callersMethod__init__
(self, drop_prob=None)
CV/Pytorch_classification/EfficientNet/model.py:51
↓ 4 callersMethod_make_layer
(self, block, channel, block_num, stride=1)
CV/Pytorch_classification/ResNet/model.py:117
↓ 4 callersFunctioncreate_co_matrix
(corpus, vocab_size, window_size=1)
NLP/Deep_Learning_Advanced_NLP/chap02_002_co_matrix.py:6
↓ 4 callersFunctionmk_file
(file_path: str)
CV/data_set/split_data.py:6
↓ 4 callersFunctionresnet34
(num_classes=1000, include_top=True)
CV/Pytorch_classification/ResNet/model.py:159
↓ 3 callersMethod__init__
(self, growth_rate=32, block_config=(6, 12, 24, 16), num_init_features=64, bn_size=4, drop_ra
CV/Pytorch_classification/DenseNet/model.py:98
↓ 3 callersMethod__init__
(self, in_planes: int, out_planes: int, kernrlz_size: int = 3
CV/Pytorch_classification/MobileNet/ model_v3.py:26
↓ 3 callersMethod__init__
(self, num_classes=1000, aux_logits=True, init_weights=True)
CV/Pytorch_classification/GoogleNet/model.py:9
↓ 3 callersFunction_assert_no_grad
(tensor)
CV/Pytorch_classification/CRNN_PyTorch/warpctc_pytorch.py:10
↓ 3 callersFunction_make_divisible
This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be seen
CV/Pytorch_classification/MobileNet/model_v2.py:8
↓ 3 callersFunction_make_divisible
(ch, divisor=8, min_ch=None)
CV/Pytorch_classification/ConfusionMatrix/model.py:5
↓ 3 callersMethodadjust_channels
(channels: int, width_multi: float)
CV/Pytorch_classification/MobileNet/ model_v3.py:83
↓ 3 callersFunctionconv2d_cx
(cx, in_c, out_c, k, *, stride=1, groups=1, bias=False, trainable=True)
CV/Pytorch_classification/model_complexity/utils.py:2
↓ 3 callersFunctiondensenet121
(**kwargs)
CV/Pytorch_classification/DenseNet/model.py:147
↓ 3 callersMethodparse_xml_to_dict
将xml文件解析成字典形式
CV/Pytorch_objection_detection/Faster RCNN/my_dataset.py:97
↓ 3 callersFunctionpreprocess
(text)
NLP/Deep_Learning_Advanced_NLP/chap02_001_preprocess.py:6
↓ 2 callersMethod__init__
(self, block, blocks_num, num_classes=1000, i
CV/Pytorch_classification/ResNet/model.py:86
↓ 2 callersMethod__init__
(self, in_channel, out_channel, kernel_size=3, stride=1, groups=1)
CV/Pytorch_classification/MobileNet/model_v2.py:24
↓ 2 callersMethod__init__
(self, in_channel, out_channel, kernel_size=3, stride=1, groups=1)
CV/Pytorch_classification/ConfusionMatrix/model.py:14
↓ 2 callersMethodbn_function
(self, inputs)
CV/Pytorch_classification/DenseNet/model.py:22
↓ 2 callersFunctioncos_similarity
(x, y, eps=1e-8)
NLP/Deep_Learning_Advanced_NLP/chap02_003_similarity.py:16
↓ 2 callersFunctioncreate_regnet
(model_name="RegNetX_200MF", num_classes=1000)
CV/Pytorch_classification/RegNet/model.py:288
↓ 2 callersMethoddepthwise_conv
(input_c, output_c, kernel_s, stride=1, padding=0, bias=False)
CV/Pytorch_classification/ShuffleNet/model.py:61
↓ 2 callersFunctionevaluate
(model, data_loader, device)
CV/Pytorch_classification/DenseNet/utils.py:133
↓ 2 callersFunctiongap2d_cx
Accumulates complexity of gap2d into cx = (h, w, flops, params, acts).
CV/Pytorch_classification/model_complexity/utils.py:39
↓ 2 callersFunctionload_state_dict
(model, weights_path)
CV/Pytorch_classification/DenseNet/model.py:179
↓ 2 callersFunctionread_split_data
(root, val_rate=0.2)
CV/Pytorch_classification/DenseNet/utils.py:11
↓ 2 callersFunctionshufflenet_v2_x1_0
Constructs a ShuffleNetV2 with 1.0x output channels, as described in `"ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Des
CV/Pytorch_classification/ShuffleNet/model.py:149
↓ 2 callersFunctiontrain_one_epoch
(model, optimizer, data_loader, device, epoch)
CV/Pytorch_classification/DenseNet/utils.py:104
↓ 2 callersFunctionvgg
(model_name="vgg16", **kwargs)
CV/Pytorch_classification/VGGNet/model.py:75
↓ 1 callersMethod__init__
(self, imgH, nc, nclass, nh, n_rnn=2, leakyRelu=False)
CV/Pytorch_classification/CRNN_PyTorch/crnn.py:23
↓ 1 callersMethod__init__
(self, stages_repeats, stages_out_channels, num_classes=1000, inverted_residual=InvertedResidual)
CV/Pytorch_classification/ShuffleNet/model.py:75
↓ 1 callersMethod_build_stage_info
(cfg: dict)
CV/Pytorch_classification/RegNet/model.py:270
↓ 1 callersMethod_forward_impl
(self, x: Tensor)
CV/Pytorch_classification/EfficientNet/model.py:276
↓ 1 callersMethod_forward_impl
(self, x: Tensor)
CV/Pytorch_classification/MobileNet/ model_v3.py:197
↓ 1 callersMethod_forward_impl
(self, x)
CV/Pytorch_classification/ShuffleNet/model.py:118
↓ 1 callersMethod_initialize_weights
(self)
CV/Pytorch_classification/GoogleNet/model.py:92
↓ 1 callersMethod_initialize_weights
(self)
CV/Pytorch_classification/VGGNet/model.py:41
↓ 1 callersMethod_initialize_weights
(self)
CV/Pytorch_classification/AlexNet/model.py:42
↓ 1 callersFunction_make_divisible
This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be seen
CV/Pytorch_classification/EfficientNet/model.py:13
↓ 1 callersFunction_make_divisible
This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be seen
CV/Pytorch_classification/MobileNet/ model_v3.py:10
↓ 1 callersMethodadjust_channels
(channels: int, width_coefficient: float)
CV/Pytorch_classification/EfficientNet/model.py:125
↓ 1 callersFunctionadjust_width_groups_comp
(widths, gtoups)
CV/Pytorch_classification/RegNet/model.py:65
↓ 1 callersMethodany_requires_grad
(self, inputs)
CV/Pytorch_classification/DenseNet/model.py:28
↓ 1 callersMethodcall_checkpoint_bottleneck
(self, inputs)
CV/Pytorch_classification/DenseNet/model.py:36
↓ 1 callersFunctionchannel_shuffule
(x: Tensor, groups: int)
CV/Pytorch_classification/ShuffleNet/model.py:9
↓ 1 callersMethodcreate_position_encoding
(self, max_len, embed_size)
NLP/Transformer/Embedding_layer.py:19
↓ 1 callersFunctiondrop_path
Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks). "Deep Networks with Stochastic Depth", https://arxiv
CV/Pytorch_classification/EfficientNet/model.py:28
↓ 1 callersFunctiondrop_path
Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks). "Deep Networks with Stochastic Depth", https://arxiv
CV/Pytorch_classification/model_complexity/model.py:12
↓ 1 callersFunctiondrop_path
(x, drop_prob=0., training=False)
CV/Pytorch_classification/vision_transformer/vit_model.py:9
↓ 1 callersFunctiondrop_path
(x, drop_prob=0., training=False)
CV/Pytorch_classification/grad_cam/vit_model.py:9
↓ 1 callersFunctionefficientnetv2_s
EfficientNetV2 https://arxiv.org/abs/2104.00298
CV/Pytorch_classification/model_complexity/model.py:390
↓ 1 callersFunctionevaluate
(model, data_loader, device)
CV/Pytorch_classification/EfficientNet/utils.py:128
↓ 1 callersFunctionevaluate
(model, data_loader, device, epoch)
CV/Pytorch_classification/vision_transformer/utils.py:132
↓ 1 callersFunctionevaluate
(model, data_loader, device)
CV/Pytorch_classification/ShuffleNet/utils.py:146
↓ 1 callersFunctionevaluate
(model, data_loader, device)
CV/Pytorch_classification/RegNet/utils.py:148
↓ 1 callersMethodforward_features
(self, x)
CV/Pytorch_classification/vision_transformer/vit_model.py:172
↓ 1 callersMethodforward_features
(self, x)
CV/Pytorch_classification/grad_cam/vit_model.py:191
↓ 1 callersFunctiongenerate_width_depth
(wa, w0, wm, depth, q=8)
CV/Pytorch_classification/RegNet/model.py:53
↓ 1 callersFunctionlinear_cx
Accumulates complexity of linear into cx = (h, w, flops, params, acts).
CV/Pytorch_classification/model_complexity/utils.py:46
↓ 1 callersFunctionmain
()
CV/data_set/split_data.py:13
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/DenseNet/predict.py:11
↓ 1 callersFunctionmain
(args)
CV/Pytorch_classification/DenseNet/train.py:16
↓ 1 callersFunctionmain
(args)
CV/Pytorch_classification/DenseNet/train_old.py:18
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/ResNet/predict.py:13
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/ResNet/train.py:15
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/ResNet/load_weights.py:8
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/ResNet/batch_predict.py:12
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/EfficientNet/predict.py:13
↓ 1 callersFunctionmain
(args)
CV/Pytorch_classification/EfficientNet/train.py:16
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/MobileNet/predict.py:11
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/MobileNet/train.py:15
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/model_complexity/main.py:8
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/GoogleNet/predict.py:12
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/vision_transformer/flops.py:5
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/vision_transformer/predict.py:11
↓ 1 callersFunctionmain
(args)
CV/Pytorch_classification/vision_transformer/train.py:16
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/ShuffleNet/predict.py:11
↓ 1 callersFunctionmain
(args)
CV/Pytorch_classification/ShuffleNet/train.py:16
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/VGGNet/predict.py:13
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/VGGNet/train.py:16
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/RegNet/predict.py:9
↓ 1 callersFunctionmain
(args)
CV/Pytorch_classification/RegNet/train.py:16
↓ 1 callersFunctionmain
()
CV/Pytorch_classification/RegNet/pretrain_weights.py:32
↓ 1 callersFunctionmake_features
(cfg: list)
CV/Pytorch_classification/VGGNet/model.py:54
↓ 1 callersFunctionmost_similar
(query, word_to_id, id_to_word, word_matrix, top=5)
NLP/Deep_Learning_Advanced_NLP/chap02_004_most_similar.py:13
↓ 1 callersFunctionnorm2d_cx
Accumulates complexity of norm2d into cx = (h, w, flops, params, acts).
CV/Pytorch_classification/model_complexity/utils.py:28
↓ 1 callersMethodplot
(self)
CV/Pytorch_classification/ConfusionMatrix/main.py:45
↓ 1 callersFunctionppmi
(C, verbose=False, eps=1e-8)
NLP/Deep_Learning_Advanced_NLP/chap02_005_ppmi.py:5
↓ 1 callersFunctionread_split_data
(root: str, val_rate: float = 0.2)
CV/Pytorch_classification/EfficientNet/utils.py:12
↓ 1 callersFunctionread_split_data
(root, val_rate = 0.2)
CV/Pytorch_classification/vision_transformer/utils.py:10
↓ 1 callersFunctionread_split_data
(root, val_rate = 0.2)
CV/Pytorch_classification/ShuffleNet/utils.py:11
next →1–100 of 321, ranked by callers