sub in PyTorch

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*Memos:

• My post explains add().
• My post explains mul().
• My post explains div().
• My post explains remainder().
• My post explains fmod().

sub() can do subtraction 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:

• sub() can be used with torch or a tensor.
• The 1st argument(input) with torch(Type:tensor or scalar of int, float or complex) or using a tensor(Type:tensor of int, float or complex)(Required).
• The 2nd argument with torch or the 1st argument with a tensor is other(Required-Type:tensor or scalar of int, float or complex).
• The 3rd argument with torch or the 2nd argument with a tensor is alpha(Optional-Default:1-Type:tensor or scalar of int, float or complex). *otheris multiplied by alpha(input or a tensor-(otherxalpha)).
• There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
  • out= must be used.
  • My post explains out argument.
• subtract() is the alias of sub().

import torch

tensor1 = torch.tensor([9, 7, 6])
tensor2 = torch.tensor([[4, -4, 3], [-2, 5, -5]])

torch.sub(input=tensor1, other=tensor2)
tensor1.sub(other=tensor2)
torch.sub(input=tensor1, other=tensor2, alpha=1)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(1))
# tensor([[5, 11, 3], [11, 2, 11]])

torch.sub(input=tensor1, other=tensor2, alpha=0)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(0))
# tensor([[9, 7, 6], [9, 7, 6]])

torch.sub(input=tensor1, other=tensor2, alpha=2)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(2))
# tensor([[1, 15, 0], [13, -3, 16]])

torch.sub(input=tensor1, other=tensor2, alpha=-1)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(-1))
# tensor([[13, 3, 9], [7, 12, 1]])

torch.sub(input=tensor1, other=tensor2, alpha=-2)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(-2))
# tensor([[17, -1, 12], [5, 17, -4]])

torch.sub(input=9, other=tensor2)
torch.sub(input=9, other=tensor2, alpha=1)
torch.sub(input=9, other=tensor2, alpha=torch.tensor(1))
# tensor([[5, 13, 6], [11, 4, 14]])

torch.sub(input=tensor1, other=4)
torch.sub(input=tensor1, other=4, alpha=1)
torch.sub(input=tensor1, other=4, alpha=torch.tensor(1))
# tensor([5, 3, 2])

torch.sub(input=9, other=4)
torch.sub(input=9, other=4, alpha=1)
torch.sub(input=9, other=4, alpha=torch.tensor(1))
# tensor(5)

tensor1 = torch.tensor([9., 7., 6.])
tensor2 = torch.tensor([[4., -4., 3.], [-2., 5., -5.]])

torch.sub(input=tensor1, other=tensor2)
torch.sub(input=tensor1, other=tensor2, alpha=1.)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(1.))
# tensor([[5., 11., 3.], [11., 2., 11.]])

torch.sub(input=9., other=tensor2)
torch.sub(input=9., other=tensor2, alpha=1.)
torch.sub(input=9., other=tensor2, alpha=torch.tensor(1.))
# tensor([[5., 13., 6.], [11., 4., 14.]])

torch.sub(input=tensor1, other=4)
torch.sub(input=tensor1, other=4, alpha=1.)
torch.sub(input=tensor1, other=4, alpha=torch.tensor(1.))
# tensor([5., 3., 2.])

torch.sub(input=9., other=4)
torch.sub(input=9., other=4, alpha=1.)
torch.sub(input=9., other=4, alpha=torch.tensor(1.))
# tensor(5.)

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.sub(input=tensor1, other=tensor2)
torch.sub(input=tensor1, other=tensor2, alpha=1.+0.j)
torch.sub(input=tensor1, other=tensor2, alpha=torch.tensor(1.+0.j))
# tensor([[5.+0.j, 11.+0.j, 3.+0.j],
#         [11.+0.j, 2.+0.j, 11.+0.j]])

torch.sub(input=9.+0.j, other=tensor2)
torch.sub(input=9.+0.j, other=tensor2, alpha=1.+0.j)
torch.sub(input=9.+0.j, other=tensor2, alpha=torch.tensor(1.+0.j))
# tensor([[5.+0.j, 13.+0.j, 6.+0.j],
#         [11.+0.j, 4.+0.j, 14.+0.j]])

torch.sub(input=tensor1, other=4.+0.j)
torch.sub(input=tensor1, other=4.+0.j, alpha=1.+0.j)
torch.sub(input=tensor1, other=4.+0.j, alpha=torch.tensor(1.+0.j))
# tensor([5.+0.j, 3.+0.j, 2.+0.j])

torch.sub(input=9.+0.j, other=4.+0.j)
torch.sub(input=9.+0.j, other=4.+0.j, alpha=1.+0.j)
torch.sub(input=9.+0.j, other=4.+0.j, alpha=torch.tensor(1.+0.j))
# tensor(5.+0.j)

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