Pytorch(2)：关于torch.cat()与torch.stack()
用法：
torch.cat(): 用于连接两个相同大小的张量
torch.stack(): 用于连接两个相同大小的张量，并扩展维度
实例：
import torch
a = torch.tensor(torch.arange(10)).reshape(3, 3)
b = torch.tensor(torch.arange(10, 100, 10)).reshape(3, 3)
print(a)
Out[7]:
tensor([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
print(b)
Out[10]:
tensor([[10, 20, 30],
[40, 50, 60],
[70, 80, 90]])
torch.cat()
使用不同的参数，输出的结果不同，首先填入一个会返回错误的参数：从返回报错原因可以看到，参数的返回必须是在[-2, 1]之间。
d3 = torch.cat((a, b), dim=2)
# 返回输出如下
Traceback (most recent call last):
File "/home/franklinpan/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3251, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
d3 = torch.cat((a, b), dim=2)
IndexError: Dimension out of range (expected to be in range of [-2, 1], but got 2) 设置dim=-1，得到如下结果，当参数为-1时，与dim=1的返回结果相同
d_1= torch.cat((a, b), dim=-1)
print(d_1)
Out[25]:
tensor([[ 1, 2, 3, 10, 20, 30],
[ 4, 5, 6, 40, 50, 60],
[ 7, 8, 9, 70, 80, 90]])
d1 = torch.cat((a, b), dim=1)
print(d1)
Out[22]:
tensor([[ 1, 2, 3, 10, 20, 30],
[ 4, 5, 6, 40, 50, 60],
[ 7, 8, 9, 70, 80, 90]])设置dim=-2，得到如下结果，与dim=0结果相同
d_2= torch.cat((a, b), dim=-2)
print(d_2)
Out[27]:
tensor([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 20, 30],
[40, 50, 60],
[70, 80, 90]])
d1 = torch.cat((a, b), dim=0)
print(d1)
Out[20]:
tensor([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 20, 30],
[40, 50, 60],
[70, 80, 90]])可以看到，采用不同的参数，输出的张量维度仍然与原来张量的维度保持一致。
若输入参数的维度不一样，会产生什么结果呢？
当输出张量保持一个维度一致时，若在相同维度的方向进行连接torch.cat操作，则仍然可以张量的合并操作，若在维度不同的方向进行连接操作，会报错。（torch.cat操作没有广播机制）
b2 = torch.tensor(torch.arange(10, 70, 10)).reshape(2, 3)
d2 = torch.cat((a, b2))
Out[32]:
tensor([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 20, 30],
[40, 50, 60]])
d3 = torch.cat((a, b2), dim=1)
Traceback (most recent call last):
File "/home/franklinpan/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3251, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
d3 = torch.cat((a, b2), dim=1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 3 but got size 2 for tensor number 1 in the list. torch.stack()
先使用超出范围的参数，得到反馈结果如下：参数范围应该在[-3, 2]之间（此处的参数范围跟输入张量的维度有关）
c4 = torch.stack((a, b), dim=3)
Traceback (most recent call last):
File "/home/franklinpan/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3251, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
c4 = torch.stack((a, b), dim=3)
IndexError: Dimension out of range (expected to be in range of [-3, 2], but got 3) 此处不再重复dim=-3 or -2等操作，当dim=0时
c1 = torch.stack((a, b), dim=0)
Out[12]:
tensor([[[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9]],
[[10, 20, 30],
[40, 50, 60],
[70, 80, 90]]])当dim=1时
c2 = torch.stack((a, b), dim=1)
Out[15]:
tensor([[[ 1, 2, 3],
[10, 20, 30]],
[[ 4, 5, 6],
[40, 50, 60]],
[[ 7, 8, 9],
[70, 80, 90]]])当 dim=2时
c3 = torch.stack((a, b), dim=2)
Out[17]:
tensor([[[ 1, 10],
[ 2, 20],
[ 3, 30]],
[[ 4, 40],
[ 5, 50],
[ 6, 60]],
[[ 7, 70],
[ 8, 80],
[ 9, 90]]])若在torch.stack中使用不同维度的输入，得到反馈如下：
c5 = torch.stack((a, b2))
Traceback (most recent call last):
File "/home/franklinpan/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3251, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "", line 1, in
c5 = torch.stack((a, b2))
RuntimeError: stack expects each tensor to be equal size, but got [3, 3] at entry 0 and [2, 3] at entry 1
从实例可见，torch.stack操作将会增加合并后张量的维度。
各张量维度如下所示：
总结：
torch.cat()与torch.stack()操作都是对张量进行拼接操作，不同点如下：
torch.stack()将对张量维度进行扩张
torch.cat()可以对只有一个方向维度相同的张量进行合并，而torch.stack()要求输入张量的维度必须一样。