fmod in PyTorch

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*Memos:

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

fmod() can do the modulo(mod) calculation of C++’s std::fmod with two of the 0D or more D tensors of zero or more elements 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:

• fmod() can be used with torch or a tensor.
• The 1st argument(input) with torch or using a tensor(Required-Type:tensor of int or float).
• The 2nd argument with torch or the 1st argument with a tensor is other(Required-Type:tensor or scalar of int or float).
• There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
  • out= must be used.
  • My post explains out argument.
• Setting 0(int) to other gets ZeroDivisionError.
• The result has the same sign as the original tensor.

import torch tensor1 = torch.tensor([9, 7, 6]) tensor2 = torch.tensor([[4, -4, 3], [-2, 5, -5]]) torch.fmod(input=tensor1, other=tensor2) tensor1.fmod(other=tensor2) # tensor([[1, 3, 0], [1, 2, 1]])  torch.fmod(input=tensor1, other=4) # tensor([1, 3, 2])  tensor1 = torch.tensor([-9, -7, -6]) tensor2 = torch.tensor([[4, -4, 3], [-2, 5, -5]]) torch.fmod(input=tensor1, other=tensor2) # tensor([[-1, -3, 0], [-1, -2, -1]])  torch.fmod(input=tensor1, other=4) # tensor([-1, -3, -2])  tensor1 = torch.tensor([9.75, 7.08, 6.26]) tensor2 = torch.tensor([[4.26, -4.54, 3.37], [-2.16, 5.43, -5.98]]) torch.fmod(input=tensor1, other=tensor2) # tensor([[1.2300, 2.5400, 2.8900], [1.1100, 1.6500, 0.2800]])  torch.fmod(input=tensor1, other=4.26) # tensor([1.2300, 2.8200, 2.0000])