torch.mul torch.bmm

torch.bmm：https://blog.csdn.net/guotong1988/article/details/78707619 

参考 https://blog.csdn.net/Real_Brilliant/article/details/85756477

batch matrix multiply  相当于矩阵的乘法。

>>> batch1 = torch.randn(10, 3, 4)
>>> batch2 = torch.randn(10, 4, 5)
>>> res = torch.bmm(batch1, batch2)
>>> res.size()
torch.Size([10, 3, 5])

 

• torch.mul(a, b)是矩阵a和b对应位相乘，a和b的维度必须相等，比如a的维度是(1, 2)，b的维度是(1, 2)，返回的仍是(1, 2)的矩阵
• torch.mm(a, b)是矩阵a和b矩阵相乘，比如a的维度是(1, 2)，b的维度是(2, 3)，返回的就是(1, 3)的矩阵

• import torch
   
  a = torch.rand(1, 2)
  b = torch.rand(1, 2)
  c = torch.rand(2, 3)
   
  print(torch.mul(a, b))  # 返回 1*2 的tensor
  print(torch.mm(a, c))   # 返回 1*3 的tensor
  print(torch.mul(a, c))  # 由于a、b维度不同，报错

  >>> import torch
  >>> a =[ [[1,2,3],[2,3,4]]]
  >>> a = torch.Tensor(a)
  >>> b =[ [[1,2,3],[2,3,4]]]
  >>> b = torch.Tensor(b)
  >>> c = torch.mul(a,b)
  >>> c
  tensor([[[ 1.,  4.,  9.],
           [ 4.,  9., 16.]]])
  >>> c.requires_grad
  False
  >>> d = a*b
  >>> d
  tensor([[[ 1.,  4.,  9.],
           [ 4.,  9., 16.]]])
  >>> d.requires_grad
  False
  >>>