torch版本：

import torchx1 = torch.tensor([[11, 21, 31], [21, 31, 41]], dtype=torch.int)
x1.shape  # torch.Size([2, 3])
# x2
x2 = torch.tensor([[12, 22, 32], [22, 32, 42]], dtype=torch.int)
x2.shape  # torch.Size([2, 3])
inputs = [x1, x2]
#print(inputs)
output = torch.cat(inputs, dim=0)
print(output)

对应numpy版本：

import numpy as np
x1 = np.array([[11, 21, 31], [21, 31, 41]], dtype=np.int32)
x1.shape  # torch.Size([2, 3])
# x2
x2 = np.array([[12, 22, 32], [22, 32, 42]], dtype=np.int32)
x2.shape  # torch.Size([2, 3])
inputs = [x1, x2]
# print(inputs)
output = np.concatenate(inputs, axis=0)
print(output)

因此torch.cat函数和Numpy中concatenate对应,numpy里面是灭有没有cat函数的