“Pytorch”的版本间差异
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无编辑摘要 |
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*torch.clamp(input, min=None, max=None, *, out=None) → Tensor |
*torch.clamp(input, min=None, max=None, *, out=None) → Tensor |
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:Clamps all elements in input into the range [ min, max ]. Letting min_value and max_value be min and max, respectively |
:Clamps all elements in input into the range [ min, max ]. Letting min_value and max_value be min and max, respectively |
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*torch.eye(n, m=None, out=None) |
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:返回一个2维张量，对角线位置全1，其它位置全0 |
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==Tensor== |
==Tensor== |
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2021年10月17日 (日) 08:26的版本
网络初始化
- Xavier and Kaiming initialization [4]
函数
- torch.clamp(input, min=None, max=None, *, out=None) → Tensor
- Clamps all elements in input into the range [ min, max ]. Letting min_value and max_value be min and max, respectively
- torch.eye(n, m=None, out=None)
- 返回一个2维张量，对角线位置全1，其它位置全0
Tensor
- cpu() numpy() detach() item() [5]
- 注意cuda上面的变量类型只能是tensor，不能是其他
torchvision
- PyTorch框架中有一个非常重要且好用的包：torchvision，该包主要由3个子包组成，分别是：torchvision.datasets、torchvision.models、torchvision.transforms [6]
- __all__ = ["Compose", "ToTensor", "ToPILImage", "Normalize", "Resize",
"Scale", "CenterCrop", "Pad", "Lambda", "RandomCrop", "RandomHorizontalFlip", "RandomVerticalFlip", "RandomResizedCrop", "RandomSizedCrop", "FiveCrop", "TenCrop","LinearTransformation", "ColorJitter", "RandomRotation", "Grayscale", "RandomGrayscale"]