一. torch.cat（）函數(shù)解析

1. 函數(shù)說明

1.1 官網(wǎng)：torch.cat()，函數(shù)定義及參數(shù)說明如下圖所示：

1.2 函數(shù)功能

函數(shù)將兩個張量（tensor）按指定維度拼接在一起，注意：除拼接維數(shù)dim數(shù)值可不同外其余維數(shù)數(shù)值需相同，方能對齊，如下面例子所示。torch.cat()函數(shù)不會新增維度，而torch.stack()函數(shù)會新增一個維度，相同的是兩個都是對張量進(jìn)行拼接

2. 代碼舉例

2.1 輸入兩個二維張量（dim=0）：dim=0對行進(jìn)行拼接

a = torch.randn(2,3)
b =  torch.randn(3,3)
c = torch.cat((a,b),dim=0)
a,b,c

輸出結(jié)果如下：
(tensor([[-0.90, -0.37, ?1.96],
? ? ? ? ?[-2.65, -0.60, ?0.05]]),
?tensor([[ 1.30, ?0.24, ?0.27],
? ? ? ? ?[-1.99, -1.09, ?1.67],
? ? ? ? ?[-1.62, ?1.54, -0.14]]),
?tensor([[-0.90, -0.37, ?1.96],
? ? ? ? ?[-2.65, -0.60, ?0.05],
? ? ? ? ?[ 1.30, ?0.24, ?0.27],
? ? ? ? ?[-1.99, -1.09, ?1.67],
? ? ? ? ?[-1.62, ?1.54, -0.14]]))

2.2 輸入兩個二維張量（dim=1）: dim=1對列進(jìn)行拼接

a = torch.randn(2,3)
b =  torch.randn(2,4)
c = torch.cat((a,b),dim=1)
a,b,c

輸出結(jié)果如下：
(tensor([[-0.55, -0.84, -1.60],
? ? ? ? ?[ 0.39, -0.96, ?1.02]]),
?tensor([[-0.83, -0.09, ?0.05, ?0.17],
? ? ? ? ?[ 0.28, -0.74, -0.27, -0.85]]),
?tensor([[-0.55, -0.84, -1.60, -0.83, -0.09, ?0.05, ?0.17],
? ? ? ? ?[ 0.39, -0.96, ?1.02, ?0.28, -0.74, -0.27, -0.85]]))

2.3 輸入兩個三維張量：dim=0 對通道進(jìn)行拼接

a = torch.randn(2,3,4)
b =  torch.randn(1,3,4)
c = torch.cat((a,b),dim=0)
a,b,c

輸出結(jié)果如下：
(tensor([[[ 0.51, -0.72, -0.02, ?0.76],
? ? ? ? ? [ 0.72, ?1.01, ?0.39, -0.13],
? ? ? ? ? [ 0.37, -0.63, -2.69, ?0.74]],
?
? ? ? ? ?[[ 0.72, -0.31, -0.27, ?0.10],
? ? ? ? ? [ 1.66, -0.06, ?1.91, -0.66],
? ? ? ? ? [ 0.34, -0.23, -0.18, -1.22]]]),
?tensor([[[ 0.94, ?0.77, -0.41, -1.20],
? ? ? ? ? [-0.23, -1.03, -0.25, ?1.67],
? ? ? ? ? [-1.00, -0.68, -0.35, -0.50]]]),
?tensor([[[ 0.51, -0.72, -0.02, ?0.76],
? ? ? ? ? [ 0.72, ?1.01, ?0.39, -0.13],
? ? ? ? ? [ 0.37, -0.63, -2.69, ?0.74]],
?
? ? ? ? ?[[ 0.72, -0.31, -0.27, ?0.10],
? ? ? ? ? [ 1.66, -0.06, ?1.91, -0.66],
? ? ? ? ? [ 0.34, -0.23, -0.18, -1.22]],
?
? ? ? ? ?[[ 0.94, ?0.77, -0.41, -1.20],
? ? ? ? ? [-0.23, -1.03, -0.25, ?1.67],
? ? ? ? ? [-1.00, -0.68, -0.35, -0.50]]]))

2.4 輸入兩個三維張量：dim=1對行進(jìn)行拼接

a = torch.randn(2,3,4)
b =  torch.randn(2,4,4)
c = torch.cat((a,b),dim=1)
a,b,c

輸出結(jié)果如下：
(tensor([[[-0.86, ?0.00, -1.26, ?1.20],
? ? ? ? ? [-0.46, -1.08, -0.82, ?2.03],
? ? ? ? ? [-0.89, ?0.43, ?1.92, ?0.49]],
?
? ? ? ? ?[[ 0.24, -0.02, ?0.32, ?0.97],
? ? ? ? ? [ 0.33, -1.34, ?0.76, -1.55],
? ? ? ? ? [ 0.38, ?1.45, ?0.27, -0.64]]]),
?tensor([[[ 0.82, ?0.85, -0.30, -0.58],
? ? ? ? ? [-0.09, ?0.40, ?0.02, ?0.75],
? ? ? ? ? [-0.70, ?0.67, -0.88, -0.50],
? ? ? ? ? [-0.62, -1.65, -1.10, -1.39]],
?
? ? ? ? ?[[-0.85, -1.61, -0.35, -0.56],
? ? ? ? ? [ 0.00, ?1.40, ?0.41, ?0.39],
? ? ? ? ? [-0.01, ?0.04, ?0.80, ?0.41],
? ? ? ? ? [-1.21, -0.64, ?1.14, ?1.64]]]),
?tensor([[[-0.86, ?0.00, -1.26, ?1.20],
? ? ? ? ? [-0.46, -1.08, -0.82, ?2.03],
? ? ? ? ? [-0.89, ?0.43, ?1.92, ?0.49],
? ? ? ? ? [ 0.82, ?0.85, -0.30, -0.58],
? ? ? ? ? [-0.09, ?0.40, ?0.02, ?0.75],
? ? ? ? ? [-0.70, ?0.67, -0.88, -0.50],
? ? ? ? ? [-0.62, -1.65, -1.10, -1.39]],
?
? ? ? ? ?[[ 0.24, -0.02, ?0.32, ?0.97],
? ? ? ? ? [ 0.33, -1.34, ?0.76, -1.55],
? ? ? ? ? [ 0.38, ?1.45, ?0.27, -0.64],
? ? ? ? ? [-0.85, -1.61, -0.35, -0.56],
? ? ? ? ? [ 0.00, ?1.40, ?0.41, ?0.39],
? ? ? ? ? [-0.01, ?0.04, ?0.80, ?0.41],
? ? ? ? ? [-1.21, -0.64, ?1.14, ?1.64]]]))

2.5 輸入兩個三維張量：dim=2對列進(jìn)行拼接

a = torch.randn(2,3,4)
b =  torch.randn(2,3,5)
c = torch.cat((a,b),dim=2)
a,b,c

輸出結(jié)果如下：
(tensor([[[ 0.13, -0.02, ?0.13, -0.25],
? ? ? ? ? [ 1.42, -0.22, -0.87, ?0.27],
? ? ? ? ? [-0.07, ?1.04, -0.06, ?0.91]],
?
? ? ? ? ?[[ 0.88, -1.46, ?0.04, ?0.35],
? ? ? ? ? [ 1.36, ?0.64, ?0.75, ?0.39],
? ? ? ? ? [ 0.36, ?1.13, ?0.83, ?0.56]]]),
?tensor([[[-0.47, -2.30, -0.49, -1.02, ?1.74],
? ? ? ? ? [ 0.71, ?0.89, ?0.80, -0.05, -1.35],
? ? ? ? ? [-0.40, ?0.26, -0.78, -1.50, -0.92]],
?
? ? ? ? ?[[-0.77, -0.01, ?1.23, ?0.70, -0.66],
? ? ? ? ? [ 0.28, -0.18, -0.91, ?2.23, ?1.14],
? ? ? ? ? [-1.93, -0.17, ?0.15, ?0.40, ?0.32]]]),
?tensor([[[ 0.13, -0.02, ?0.13, -0.25, -0.47, -2.30, -0.49, -1.02, ?1.74],
? ? ? ? ? [ 1.42, -0.22, -0.87, ?0.27, ?0.71, ?0.89, ?0.80, -0.05, -1.35],
? ? ? ? ? [-0.07, ?1.04, -0.06, ?0.91, -0.40, ?0.26, -0.78, -1.50, -0.92]],
?
? ? ? ? ?[[ 0.88, -1.46, ?0.04, ?0.35, -0.77, -0.01, ?1.23, ?0.70, -0.66],
? ? ? ? ? [ 1.36, ?0.64, ?0.75, ?0.39, ?0.28, -0.18, -0.91, ?2.23, ?1.14],
? ? ? ? ? [ 0.36, ?1.13, ?0.83, ?0.56, -1.93, -0.17, ?0.15, ?0.40, ?0.32]]]))

總結(jié)