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Super Kai (Kazuya Ito)
Super Kai (Kazuya Ito)

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any in PyTorch

#python #pytorch #any #function

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*My post explains all().

any() can check if any elements of a 0D or more D tensor are True, getting the 0D or more D tensor of zero or more elements as shown below:

*Memos:

  • any() can be used with torch or a tensor.
  • The 1st argument(input) with torch or using a tensor(Required-Type:tensor of int, float, complex or bool).
  • The 2nd argument with torch or the 1st argument with a tensor is dim(Optional-Type:int, tuple of int or list of int).
  • The 3rd argument with torch or the 2nd argument with a tensor is keepdim(Optional-Default:False-Type:bool). *My post explains keepdim argument.
  • There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
    • out= must be used.
    • My post explains out argument.
  • An empty tensor returns a False of a 1D or more D tensor or an empty 1D or more D tensor. 
import torch my_tensor = torch.tensor(True) torch.any(input=my_tensor) my_tensor.any() torch.any(input=my_tensor, dim=0) torch.any(input=my_tensor, dim=-1) torch.any(input=my_tensor, dim=(0,)) torch.any(input=my_tensor, dim=(-1,)) # tensor(True)  torch.any(input=my_tensor, dim=0, keepdim=True) # tensor(True)  my_tensor = torch.tensor([True, False, True, False]) torch.any(input=my_tensor) torch.any(input=my_tensor, dim=0) torch.any(input=my_tensor, dim=-1) torch.any(input=my_tensor, dim=(0,)) torch.any(input=my_tensor, dim=(-1,)) # tensor(True)  torch.any(input=my_tensor, dim=0, keepdim=True) # tensor([True])  my_tensor = torch.tensor([[True, False, True, False], [True, False, True, False]]) torch.any(input=my_tensor) torch.any(input=my_tensor, dim=(0, 1)) torch.any(input=my_tensor, dim=(0, -1)) torch.any(input=my_tensor, dim=(1, 0)) torch.any(input=my_tensor, dim=(1, -2)) torch.any(input=my_tensor, dim=(-1, 0)) torch.any(input=my_tensor, dim=(-1, -2)) torch.any(input=my_tensor, dim=(-2, 1)) torch.any(input=my_tensor, dim=(-2, -1)) # tensor(True)  torch.any(input=my_tensor, dim=0) torch.any(input=my_tensor, dim=(0,)) torch.any(input=my_tensor, dim=-2) # tensor([True, False, True, False])  torch.any(input=my_tensor, dim=1) torch.any(input=my_tensor, dim=-1) torch.any(input=my_tensor, dim=(-1,)) # tensor([True, True])  torch.any(input=my_tensor, dim=0, keepdim=True) # tensor([[True, False, True, False]])  my_tensor = torch.tensor([[0, 1, 2, 3], [4, 5, 6, 7]]) torch.any(input=my_tensor) # tensor(True)  my_tensor = torch.tensor([[0., 1., 2., 3.], [4., 5., 6., 7.]]) torch.any(input=my_tensor) # tensor(True)  my_tensor = torch.tensor([[0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j], [4.+0.j, 5.+0.j, 6.+0.j, 7.+0.j]]) torch.any(input=my_tensor) # tensor(True)  my_tensor = torch.tensor([[]]) torch.any(input=my_tensor) # tensor(False)  torch.any(input=my_tensor, dim=0) torch.any(input=my_tensor, dim=-2) # tensor([], dtype=torch.bool)  torch.any(input=my_tensor, dim=1) torch.any(input=my_tensor, dim=-1) # tensor([False])
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