Pytorch
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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
- torch.view()
- 相当于numpy的reshape,某个维度上等于-1,就是让计算机自己算一下这一维度上应该有多少
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"]