all() and any() in PyTorch

#pytorch #all #any #function

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

*Memos:

all() can be used with torch or a tensor.
The 1st argument(tensor of int, float, complex or bool) with torch or using a tensor(tensor of int, float, complex or bool) is input(Required).
The 2nd argument(int, tuple of int or list of int) with torch or the 1st argument(int, tuple of int or list of int) with a tensor is dim(Optional).
The 3rd argument(bool) with torch or the 2nd argument(bool) with a tensor is keepdim(Optional-Default:False) which keeps the dimension of the input tensor.
An empty tensor returns True of a 1D or more D tensor or an empty 1D or more D tensor.

import torch

my_tensor = torch.tensor(True)

torch.all(input=my_tensor)
my_tensor.all()
torch.all(input=my_tensor, dim=0)
torch.all(input=my_tensor, dim=-1)
torch.all(input=my_tensor, dim=(0,))
torch.all(input=my_tensor, dim=(-1,))
# tensor(True)

torch.all(input=my_tensor, dim=0, keepdim=True)
# tensor(True)

my_tensor = torch.tensor([True, False, True, False])

torch.all(input=my_tensor)
torch.all(input=my_tensor, dim=0)
torch.all(input=my_tensor, dim=-1)
torch.all(input=my_tensor, dim=(0,))
torch.all(input=my_tensor, dim=(-1,))
# tensor(False)

torch.all(input=my_tensor, dim=0, keepdim=True)
# tensor([False])

my_tensor = torch.tensor([[True, False, True, False],
                          [True, False, True, False]])
torch.all(input=my_tensor)
torch.all(input=my_tensor, dim=(0, 1))
torch.all(input=my_tensor, dim=(0, -1))
torch.all(input=my_tensor, dim=(1, 0))
torch.all(input=my_tensor, dim=(1, -2))
torch.all(input=my_tensor, dim=(-1, 0))
torch.all(input=my_tensor, dim=(-1, -2))
torch.all(input=my_tensor, dim=(-2, 1))
torch.all(input=my_tensor, dim=(-2, -1))
# tensor(False)

torch.all(input=my_tensor, dim=0)
torch.all(input=my_tensor, dim=(0,))
torch.all(input=my_tensor, dim=-2)
# tensor([True, False, True, False])

torch.all(input=my_tensor, dim=1)
torch.all(input=my_tensor, dim=-1)
torch.all(input=my_tensor, dim=(-1,))
# tensor([False, False])

torch.all(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.all(input=my_tensor)
# tensor(False)

my_tensor = torch.tensor([[0., 1., 2., 3.],
                          [4., 5., 6., 7.]])
torch.all(input=my_tensor)
# tensor(False)

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.all(input=my_tensor)
# tensor(False)

any() can check if any element of a 0D or more D tensor is True as shown below:

*Memos:

any() can be used with torch or a tensor.
The 1st argument(tensor of int, float, complex or bool) with torch or using a tensor(tensor of int, float, complex or bool) is input(Required).
The 2nd argument(int, tuple of int or list of int) with torch or the 1st argument(int, tuple of int or list of int) with a tensor is dim(Optional).
The 3rd argument(bool) with torch or the 2nd argument(bool) with a tensor is keepdim(Optional-Default:False) which keeps the dimension of the input tensor.
An empty tensor returns 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)

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all() and any() in PyTorch

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