Functions — github.com/Sirwenhao/Deep-Learning-Notes

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

⨍ Functions 321◇ Types & classes 74

↓ 1 callersFunctionread_split_data

(root: str, val_rate: float = 0.2)

CV/Pytorch_classification/RegNet/utils.py:13

↓ 1 callersMethodsummary

(self)

CV/Pytorch_classification/ConfusionMatrix/main.py:22

↓ 1 callersFunctiontrainBatch

(net, ctiterion, optimizer)

CV/Pytorch_classification/CRNN_PyTorch/train.py:173

↓ 1 callersFunctiontrain_one_epoch

(model, optimizer, data_loader, device, epoch)

CV/Pytorch_classification/EfficientNet/utils.py:101

↓ 1 callersFunctiontrain_one_epoch

(model, optimizer, data_loader, device, epoch)

CV/Pytorch_classification/vision_transformer/utils.py:99

↓ 1 callersFunctiontrain_one_epoch

(model, optimizer, data_loader, device, epoch)

CV/Pytorch_classification/ShuffleNet/utils.py:116

↓ 1 callersFunctiontrain_one_epoch

(model, optimizer, data_loader, device, epoch)

CV/Pytorch_classification/RegNet/utils.py:118

↓ 1 callersFunctionval

(net, dataset, criterion, max_iter=100)

CV/Pytorch_classification/CRNN_PyTorch/train.py:127

↓ 1 callersMethodzero_init_last_bn

(self)

CV/Pytorch_classification/RegNet/model.py:175

Function__call__

(self, x)

CV/Pytorch_classification/grad_cam/utils.py:37

Method__call__

(self, img)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:74

Method__call__

(self, batch)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:112

Function__del__

(self)

CV/Pytorch_classification/grad_cam/utils.py:140

Function__enter__

()

CV/Pytorch_classification/grad_cam/utils.py:143

Function__exit__

(self)

CV/Pytorch_classification/grad_cam/utils.py:146

Method__getitem__

(self, index)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:40

Method__getitem__

(self, item)

CV/Pytorch_classification/EfficientNet/my_dataset.py:18

Method__getitem__

(self, item)

CV/Pytorch_classification/vision_transformer/my_dataset.py:16

Method__getitem__

(self, item)

CV/Pytorch_classification/ShuffleNet/my_dataset.py:17

Method__getitm__

(self, idx)

CV/Pytorch_objection_detection/Faster RCNN/my_dataset.py:39

Method__gettiem__

(self, item)

CV/Pytorch_classification/DenseNet/my_dataset.py:17

Function__init__

(self, model, target_layers, reshape_transform=None, use_cuda=False)

CV/Pytorch_classification/grad_cam/utils.py:47

Method__init__

(self, voc_root, transforms, train_set=True)

CV/Pytorch_objection_detection/Faster RCNN/my_dataset.py:12

Method__init__

(self, blank=0, size_average=False, length_average=False)

CV/Pytorch_classification/CRNN_PyTorch/warpctc_pytorch.py:48

Method__init__

(self, nIn, nHidden, nOut)

CV/Pytorch_classification/CRNN_PyTorch/crnn.py:6

Method__init__

(self, root=None, transform=None, target_transform=None)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:23

Method__init__

(self, size, interpolation=Image.BILINEAR)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:69

Method__init__

(self, data_source, batch_size)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:81

Method__init__

(self, imgH=32, imgW=100, keep_ratio=False, min_ratio=1)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:106

Method__init__

(self, images_path, images_class, transform=None)

CV/Pytorch_classification/DenseNet/my_dataset.py:9

Method__init__

(self, input_c, growth_rate, bn_size, drop_rate, memory_efficient=False)

CV/Pytorch_classification/DenseNet/model.py:12

Method__init__

(self, num_layers, input_c, bn_size, growth_rate, drop_rate, memory_efficient=False)

CV/Pytorch_classification/DenseNet/model.py:63

Method__init__

(self, input_c, output_c)

CV/Pytorch_classification/DenseNet/model.py:76

Method__init__

(self, in_channel, out_channel, stride=1, downsample=None, **kwargs)

CV/Pytorch_classification/ResNet/model.py:12

Method__init__

(self, in_channel, out_channel, stride=1, downsample=None, groups=1, width_per_group=64)

CV/Pytorch_classification/ResNet/model.py:43

Method__init__

(self, imgaes_path: list, images_class: list, transform=None)

CV/Pytorch_classification/EfficientNet/my_dataset.py:10

Method__init__

(self, in_planes: int, out_planes: int, kernel_size: int =

CV/Pytorch_classification/EfficientNet/model.py:60

Method__init__

(self, input_c: int, expand_c: int, squeeze_factor: int = 4

CV/Pytorch_classification/EfficientNet/model.py:85

Method__init__

(self, kernel: int, input_c: int, out_c: int,

CV/Pytorch_classification/EfficientNet/model.py:106

Method__init__

(self, cnf: InvertedResidualConfig, norm_layer: Callable[..., nn.Module])

CV/Pytorch_classification/EfficientNet/model.py:130

Method__init__

(self, width_coefficient: float, depth_coefficient: float, num

CV/Pytorch_classification/EfficientNet/model.py:187

Method__init__

(self, input_c: int, sequeeze_factor: int = 4)

CV/Pytorch_classification/MobileNet/ model_v3.py:50

Method__init__

(self, input_c: int, kernel: int, expanded_c: int,

CV/Pytorch_classification/MobileNet/ model_v3.py:65

Method__init__

(self, cnf: InvertedResidualConfig, norm_layer: Callable[..., nn.Module])

CV/Pytorch_classification/MobileNet/ model_v3.py:88

Method__init__

(self, inverted_residual_setting: List[InvertedResidualConfig], last

CV/Pytorch_classification/MobileNet/ model_v3.py:135

Method__init__

(self, in_channel, out_channel, stride, expand_ratio)

CV/Pytorch_classification/MobileNet/model_v2.py:34

Method__init__

(self, num_classes=1000, alpha=1.0, round_nearest=8)

CV/Pytorch_classification/MobileNet/model_v2.py:62

Method__init__

(self, num_classes, labels)

CV/Pytorch_classification/ConfusionMatrix/main.py:13

Method__init__

(self, in_channel, out_channel, stride, expand_ratio)

CV/Pytorch_classification/ConfusionMatrix/model.py:23

Method__init__

(self, num_classes=1000, alpha=1.0, round_nearest=8)

CV/Pytorch_classification/ConfusionMatrix/model.py:46

Method__init__

(self, drop_prob=None)

CV/Pytorch_classification/model_complexity/model.py:36

Method__init__

(self, in_planes: int, out_planes: int, kernel_size: int =

CV/Pytorch_classification/model_complexity/model.py:45

Method__init__

(self, input_c: int, # block input channel expand_c: int, # block expand

CV/Pytorch_classification/model_complexity/model.py:94

Method__init__

(self, kernel_size: int, input_c: int, out_c: int,

CV/Pytorch_classification/model_complexity/model.py:210

Method__init__

(self, model_cnf: list, num_classes: int = 1000, num_featur

CV/Pytorch_classification/model_complexity/model.py:289

Method__init__

(self, in_channels, ch1x1, ch3x3red, ch3x3, ch5x5red, ch5x5, pool_proj)

CV/Pytorch_classification/GoogleNet/model.py:103

Method__init__

(self, in_channels, num_classes)

CV/Pytorch_classification/GoogleNet/model.py:133

Method__init__

(self, in_channels, out_channels, **kwargs)

CV/Pytorch_classification/GoogleNet/model.py:157

Method__init__

(self, drop_prob=None)

CV/Pytorch_classification/vision_transformer/vit_model.py:20

Method__init__

(self, img_size=224, patch_size=16, in_c=3, embed_dim=768, norm_layer=None)

CV/Pytorch_classification/vision_transformer/vit_model.py:28

Method__init__

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop_ratio=0., proj_drop_ratio=0.)

CV/Pytorch_classification/vision_transformer/vit_model.py:49

Method__init__

(self, dim, num_heads, mlp_ratio=4, qkv_bias=False, qk_scale=None, drop_ratio=0., attn_drop_ratio=0., drop_pat

CV/Pytorch_classification/vision_transformer/vit_model.py:104

Method__init__

(self, img_size=224, patch_size=16, in_c=3, num_classes=1000, embed_dim=768, depth=12, num_he

CV/Pytorch_classification/vision_transformer/vit_model.py:121

Method__init__

(self, images_path, images_class, transform)

CV/Pytorch_classification/vision_transformer/my_dataset.py:8

Method__init__

(self, images_path: list, images_class: list, transform=None)

CV/Pytorch_classification/ShuffleNet/my_dataset.py:9

Method__init__

(self, input_c, output_c, stride)

CV/Pytorch_classification/ShuffleNet/model.py:26

Method__init__

(self, features, num_classes=1000, init_weights=False)

CV/Pytorch_classification/VGGNet/model.py:17

Method__init__

(self, drop_path=None)

CV/Pytorch_classification/grad_cam/vit_model.py:21

Method__init__

(self, img_size=224, patch_size=16, in_c=3, embed_dim=768, norm_layer=None)

CV/Pytorch_classification/grad_cam/vit_model.py:29

Method__init__

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop_ratio=0., proj_drop_ratio=0.)

CV/Pytorch_classification/grad_cam/vit_model.py:51

Method__init__

(self, dim, num_heads, mlp_ratio=4, qkv_bi

CV/Pytorch_classification/grad_cam/vit_model.py:95

Method__init__

Args: img_size (int, tuple): input image size patch_size (int, tuple): patch size in_c (int): number of i

CV/Pytorch_classification/grad_cam/vit_model.py:121

Method__init__

(self, model, target_layers, reshape_transform)

CV/Pytorch_classification/grad_cam/utils.py:5

Method__init__

(self, in_c, out_c, kernel_s = 1, stride =

CV/Pytorch_classification/RegNet/model.py:71

Method__init__

(self, in_unit = 368, out_init = 1000, output_size = (1, 1)

CV/Pytorch_classification/RegNet/model.py:99

Method__init__

(self, input_c, expand_c, se_ratio = 0.25)

CV/Pytorch_classification/RegNet/model.py:123

Method__init__

(self, in_c, out_c, stride = 1, group_widt

CV/Pytorch_classification/RegNet/model.py:140

Method__init__

(self, in_c, out_c, depth, group_width,

CV/Pytorch_classification/RegNet/model.py:195

Method__init__

(self, num_classes = 1000, init_weights = False)

CV/Pytorch_classification/AlexNet/model.py:6

Method__init__

(self, dim_embed, epsilon=1e-6)

NLP/Transformer/LayerNormalization.py:5

Method__init__

(self, max_positions, dim_embed, drop_prob)

NLP/Transformer/PositionalEncoding.py:9

Method__init__

(self, vocab_size, embed_size, max_len)

NLP/Transformer/Embedding_layer.py:9

Method__iter__

(self)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:85

Method__len__

(self)

CV/Pytorch_objection_detection/Faster RCNN/my_dataset.py:36

Method__len__

(self)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:37

Method__len__

(self)

CV/Pytorch_classification/CRNN_PyTorch/dataset.py:102

Method__len__

(self)

CV/Pytorch_classification/DenseNet/my_dataset.py:14

Method__len__

(self)

CV/Pytorch_classification/EfficientNet/my_dataset.py:15

Method__len__

(self)

CV/Pytorch_classification/vision_transformer/my_dataset.py:13

Method__len__

(self)

CV/Pytorch_classification/ShuffleNet/my_dataset.py:14

Function_init_vit_weights

(m)

CV/Pytorch_classification/vision_transformer/vit_model.py:198

Function_make_divisible

(ch, divisor=8, min_ch=None)

CV/Pytorch_classification/RegNet/model.py:11

Functionaggregate_multi_layers

(self, cam_per_target_layer)

CV/Pytorch_classification/grad_cam/utils.py:99

Functionattention

(query, key, value, mask)

NLP/Transformer/scaled_dot_product_attention.py:8

Functioncenter_crop_img

(img, size)

CV/Pytorch_classification/grad_cam/utils.py:165

Methodclosure

(*inp)

CV/Pytorch_classification/DenseNet/model.py:37

Methodcoco_index

该方法是专门为pycocotools统计标签信息准备，不对图像和标签作任何处理由于不用去读取图片，可大幅缩减统计时间 Args: idx: 输入需要获取图像的索引

CV/Pytorch_objection_detection/Faster RCNN/my_dataset.py:114

Methodcollate_fn

(batch)

CV/Pytorch_objection_detection/Faster RCNN/my_dataset.py:162

Methodcollate_fn

(batch)

CV/Pytorch_classification/DenseNet/my_dataset.py:28

Methodcollate_fn

(batch)

CV/Pytorch_classification/EfficientNet/my_dataset.py:31

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