技術標籤：pytorch

import  torch
a=torch.tensor([[[ 0.0402, -0.1184, -0.7499,   -0.3347, -0.7184, -0.7137],
         [ 0.0829, -0.3118, -0.2069,  -0.8267, -0.6034, -0.1528],
         [ 0.2082, -0.1497, -0.3795,   -0.2937, -0.5613, -0.0673],
         [ 0.3715, -0.0893, -0.0470, -0.3137, -0.4161, -0.0860],
         [ 0.2035,  0.0389,  0.1358,  -
 
0.0482, -0.6119, -0.1137],
         [-0.1657,  0.0381,  0.2353,  0.1406, -0.3886, -0.4558]]])
print(a.shape)
# torch.Size([1, 6, 6])

print("a[1:]",a[1:],a[1:].shape)
#a[1:] tensor([], size=(0, 6, 6)) torch.Size([0, 6, 6])

print("a[0:]",a[0:],a[0:].shape)
#a[0:] tensor([[[ 0.0402, -0.1184, -0.7499, -0.3347, -0.7184, -0.7137],
 

        # [ 0.0829, -0.3118, -0.2069, -0.8267, -0.6034, -0.1528],
        # [ 0.2082, -0.1497, -0.3795, -0.2937, -0.5613, -0.0673],
        # [ 0.3715, -0.0893, -0.0470, -0.3137, -0.4161, -0.0860],
        # [ 0.2035,  0.0389,  0.1358, -0.0482, -0.6119, -0.1137],
        # [-0.1657,  0.0381,  0.2353,  0.1406, -0.3886, -0.4558]]]) 
 #torch.Size([1, 6, 6])
 


print("a[0]",a[0],a[0].shape)
#a[0] tensor([[ 0.0402, -0.1184, -0.7499, -0.3347, -0.7184, -0.7137],
        #[ 0.0829, -0.3118, -0.2069, -0.8267, -0.6034, -0.1528],
        #[ 0.2082, -0.1497, -0.3795, -0.2937, -0.5613, -0.0673],
        #[ 0.3715, -0.0893, -0.0470, -0.3137, -0.4161, -0.0860],
        #[ 0.2035,  0.0389,  0.1358, -0.0482, -0.6119, -0.1137],
        #[-0.1657,  0.0381,  0.2353,  0.1406, -0.3886, -0.4558]]) 
#torch.Size([6, 6])

a=torch.tensor([[[ 0.0402, -0.1184, -0.7499,   -0.3347, -0.7184, -0.7137],
         [ 0.0829, -0.3118, -0.2069,  -0.8267, -0.6034, -0.1528],
         [ 0.2082, -0.1497, -0.3795,   -0.2937, -0.5613, -0.0673]],

         [[ 0.3715, -0.0893, -0.0470, -0.3137, -0.4161, -0.0860],
         [ 0.2035,  0.0389,  0.1358,  -0.0482, -0.6119, -0.1137],
         [-0.1657,  0.0381,  0.2353,  0.1406, -0.3886, -0.4558]]])
print("a[0]",a[0,2],a[0,2].shape)# 提取第1組資料的第三行資料

a[0] tensor([ 0.2082, -0.1497, -0.3795, -0.2937, -0.5613, -0.0673]) torch.Size([6])