*Memos:
- My post explains add().
- My post explains sub().
- My post explains div().
- My post explains remainder().
- My post explains fmod().
mul() can do multiplication with two of the 0D or more D tensors of zero or more elements or scalars or the 0D or more D tensor of zero or more elements and a scalar. getting the 0D or more D tensor of zero or more elements as shown below:
*Memos:
-
mul()can be used with torch or a tensor. - The 1st argument(
input) withtorch(Type:tensororscalarofint,float,complexorbool) or using a tensor(Type:tensorofint,float,complexorbool)(Required). - The 2nd argument with
torchor the 1st argument with a tensor isother(Required-Type:tensororscalarofint,float,complexorbool). - There is
outargument withtorch(Optional-Default:None-Type:tensor): *Memos:-
out=must be used. - My post explains
outargument.
-
- multiply() is the alias of
mul().
import torch tensor1 = torch.tensor([9, 7, 6]) tensor2 = torch.tensor([[4, -4, 3], [-2, 5, -5]]) torch.mul(input=tensor1, other=tensor2) tensor1.mul(other=tensor2) # tensor([[36, -28, 18], [-18, 35, -30]]) torch.mul(input=9, other=tensor2) # tensor([[36, -36, 27], [-18, 45, -45]]) torch.mul(input=tensor1, other=4) # tensor([36, 28, 24]) torch.mul(input=9, other=4) # tensor(36) tensor1 = torch.tensor([9., 7., 6.]) tensor2 = torch.tensor([[4., -4., 3.], [-2., 5., -5.]]) torch.mul(input=tensor1, other=tensor2) # tensor([[36., -28., 18.], [-18., 35., -30.]]) torch.mul(input=9., other=tensor2) # tensor([[36., -36., 27.], [-18., 45., -45.]]) torch.mul(input=tensor1, other=4.) # tensor([36., 28., 24.]) torch.mul(input=9., other=4.) # tensor(36.) tensor1 = torch.tensor([9.+0.j, 7.+0.j, 6.+0.j]) tensor2 = torch.tensor([[4.+0.j, -4.+0.j, 3.+0.j], [-2.+0.j, 5.+0.j, -5.+0.j]]) torch.mul(input=tensor1, other=tensor2) # tensor([[36.+0.j, -28.+0.j, 18.+0.j], # [-18.+0.j, 35.+0.j, -30.+0.j]]) torch.mul(input=9.+0.j, other=tensor2) # tensor([[36.+0.j, -36.+0.j, 27.+0.j], # [-18.+0.j, 45.+0.j, -45.+0.j]]) torch.mul(input=tensor1, other=4.+0.j) # tensor([36.+0.j, 28.+0.j, 24.+0.j]) torch.mul(input=9.+0.j, other=4.+0.j) # tensor(36.+0.j) tensor1 = torch.tensor([True, False, True]) tensor2 = torch.tensor([[False, True, False], [True, False, True]]) torch.mul(input=tensor1, other=tensor2) # tensor([[False, False, False], # [True, False, True]]) torch.mul(input=True, other=tensor2) # tensor([[False, True, False], [True, False, True]]) torch.mul(input=tensor1, other=False) # tensor([False, False, False]) torch.mul(input=True, other=False) # tensor(False) 
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