1 官方文档介绍

1.1 torch.argmax()介绍

 返回最大值的索引下标

函数：
     torch.argmax(input, dim, keepdim=False) → LongTensor

返回值：
     Returns the indices of the maximum values of a tensor across a dimension.

参数：
	input (Tensor) – the input tensor.
	dim (int) – the dimension to reduce. If None, the argmax of the flattened input is returned.
	keepdim (bool) – whether the output tensor has dim retained or not. Ignored if dim=None.

1.2 torch.argmin()介绍

 返回最小值的索引下标

函数：
     torch.argmin(input, dim, keepdim=False) → LongTensor

返回值：
     Returns the indices of the mimimum values of a tensor across a dimension.

参数：
	input (Tensor) – the input tensor.
	dim (int) – the dimension to reduce. If None, the argmax of the flattened input is returned.
	keepdim (bool) – whether the output tensor has dim retained or not. Ignored if dim=None.

2 代码示例

2.1 torch.argmax()代码示例

>>> import torch
>>> Matrix = torch.randn(2,2,2)
>>> print(Matrix)
tensor([[[ 0.3772, -0.1143],
         [ 0.2217, -0.1897]],

        [[ 0.1488, -0.8758],
         [ 1.7734, -0.5929]]])
>>> print(Matrix.argmax(dim=0))
tensor([[0, 0],
        [1, 0]])
>>> print(Matrix.argmax(dim=1))
tensor([[0, 0],
        [1, 1]])
>>> print(Matrix.argmax(dim=2))
tensor([[0, 0],
        [0, 0]])
>>> print(Matrix.argmax())
tensor(6)

2.2 torch.argmin()代码示

>>> import torch
>>> Matrix = torch.randn(2,2,2)
>>> print(Matrix)
tensor([[[ 0.5821,  0.2889],
         [ 0.4669, -0.3135]],

        [[-0.4567,  0.2975],
         [-1.5084,  0.7320]]])
>>> print(Matrix.argmin(dim=0))
tensor([[1, 0],
        [1, 0]])
>>> print(Matrix.argmin(dim=1))
tensor([[1, 1],
        [1, 0]])
>>> print(Matrix.argmin(dim=2))
tensor([[1, 1],
        [0, 0]])
>>> print(Matrix.argmin())
tensor(6)