Pytorch疑难小实验:Torch.max() Torch.min()在不同维度上的解释

简介: Pytorch疑难小实验:Torch.max() Torch.min()在不同维度上的解释
import torch
torch.manual_seed(2)
Tensor_data = torch.rand((3,3,3))
print(Tensor_data)
enc_opt0_min = Tensor_data.min(dim=0)[0].unsqueeze(2) #取最小值张量 索引舍弃
print("min:",enc_opt0_min)
enc_opt0_max = Tensor_data.max(dim=0)[0].unsqueeze(2)
print("max:",enc_opt0_max)


tensor([[[0.6147, 0.3810, 0.6371],
         [0.4745, 0.7136, 0.6190],
         [0.4425, 0.0958, 0.6142]],
        [[0.0573, 0.5657, 0.5332],
         [0.3901, 0.9088, 0.5334],
         [0.7073, 0.7116, 0.2050]],
        [[0.3078, 0.9809, 0.0103],
         [0.4660, 0.4604, 0.8547],
         [0.4525, 0.6317, 0.4760]]])
min: tensor([[[0.0573],[0.3810],[0.0103]],
      [[0.3901],[0.4604],[0.5334]],
      [[0.4425],[0.0958],[0.2050]]])
max: tensor([[[0.6147],[0.9809],[0.6371]],
          [[0.4745], [0.9088],[0.8547]],
          [[0.7073],[0.7116],[0.6142]]])


import torch
torch.manual_seed(2)
Tensor_data = torch.rand((3,3,3))
print(Tensor_data)
enc_opt0_min = Tensor_data.min(dim=1)[0].unsqueeze(2) #取最小值张量 索引舍弃
print("min:",enc_opt0_min)
enc_opt0_max = Tensor_data.max(dim=1)[0].unsqueeze(2)
print("max:",enc_opt0_max)


tensor([[[0.6147, 0.3810, 0.6371],
         [0.4745, 0.7136, 0.6190],
         [0.4425, 0.0958, 0.6142]],
        [[0.0573, 0.5657, 0.5332],
         [0.3901, 0.9088, 0.5334],
         [0.7073, 0.7116, 0.2050]],
        [[0.3078, 0.9809, 0.0103],
         [0.4660, 0.4604, 0.8547],
         [0.4525, 0.6317, 0.4760]]])
min: tensor([[[0.4425],[0.0958],[0.6142]],
      [[0.0573],[0.5657],[0.2050]],
      [[0.3078], [0.4604],[0.0103]]])
max: tensor([[[0.6147],[0.7136],[0.6371]],
      [[0.7073],[0.9088],[0.5334]],
      [[0.4660],[0.9809],[0.8547]]])


import torch
torch.manual_seed(2)
Tensor_data = torch.rand((3,3,3))
print(Tensor_data)
enc_opt0_min = Tensor_data.min(dim=2)[0].unsqueeze(2) #取最小值张量 索引舍弃
print("min:",enc_opt0_min)
enc_opt0_max = Tensor_data.max(dim=2)[0].unsqueeze(2)
print("max:",enc_opt0_max)


tensor([[[0.6147, 0.3810, 0.6371],
         [0.4745, 0.7136, 0.6190],
         [0.4425, 0.0958, 0.6142]],
        [[0.0573, 0.5657, 0.5332],
         [0.3901, 0.9088, 0.5334],
         [0.7073, 0.7116, 0.2050]],
        [[0.3078, 0.9809, 0.0103],
         [0.4660, 0.4604, 0.8547],
         [0.4525, 0.6317, 0.4760]]])
min: tensor([[[0.3810],[0.4745],[0.0958]],
      [[0.0573],[0.3901],[0.2050]],
      [[0.0103],[0.4604],[0.4525]]])
max: tensor([[[0.6371],[0.7136],[0.6142]],
      [[0.5657],[0.9088],[0.7116]],
      [[0.9809],[0.8547],[0.6317]]])
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