abs and sqrt in PyTorch

hyperkai

Super Kai (Kazuya Ito)

Posted on May 17, 2024

abs and sqrt in PyTorch

Buy Me a Coffee

*My post explains gcd() and lcm().

abs() can get the 0D or more D tensor of zero or more absolute values from the 0D or more D tensor of zero or more elements as shown below:

*Memos:

  • abs() can be used with torch or a tensor.
  • The 1st argument(input) with torch or using a tensor(Required-Type:tensor of int, float or complex). *If the type is complex, float is returned.
  • There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
    • out= must be used.
    • My post explains out argument.
  • absolute() is the alias of abs().
import torch

my_tensor = torch.tensor(7)

torch.abs(input=my_tensor)
my_tensor.abs()
# tensor(7)

my_tensor = torch.tensor([7, -1, 5, -7, -9, -3, 0, 6])

torch.abs(input=my_tensor)
# tensor([7, 1, 5, 7, 9, 3, 0, 6])

my_tensor = torch.tensor([[-7, 1, -5, 7],
                          [9, -3, 0, -6]])
torch.abs(input=my_tensor)
# tensor([[7, 1, 5, 7],
#         [9, 3, 0, 6]])

my_tensor = torch.tensor([[7, -1, 5, -7],
                          [-9, -3, 0, 6]])
torch.abs(input=my_tensor)
# tensor([[[7, 1], [5, 7]],
#         [[9, 3], [0, 6]]])

my_tensor = torch.tensor([[[7., -1.], [5., -7.]],
                          [[-9., -3.], [0., 6.]]])
torch.abs(input=my_tensor)
# tensor([[[7., 1.], [5., 7.]],
#         [[9., 3.], [0., 6.]]])

my_tensor = torch.tensor([[[7.+0.j, -1.+0.j], [5.+0.j, -7.+0.j]],
                          [[-9.+0.j, -3.+0.j], [0.+0.j, 6.+0.j]]])
torch.abs(input=my_tensor)
# tensor([[[7., 1.], [5., 7.]],
#         [[9., 3.], [0., 6.]]])
Enter fullscreen mode Exit fullscreen mode

sqrt() can get the 0D or more D tensor of zero or more square roots from the 0D or more D tensor of zero or more elements as shown below:

*Memos:

  • sqrt() 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).
  • There is out argument with torch(Optional-Default:None-Type:tensor): *Memos:
    • out= must be used.
    • My post explains out argument.
import torch

my_tensor = torch.tensor(7)

torch.sqrt(input=my_tensor)
my_tensor.sqrt()
# tensor(2.6458)

my_tensor = torch.tensor([7, -1, 5, -7, -9, -3, 0, 6])

torch.sqrt(input=my_tensor)
# tensor([2.6458, nan, 2.2361, nan, nan, nan, 0.0000, 2.4495])

my_tensor = torch.tensor([[7, -1, 5, -7],
                          [-9, -3, 0, 6]])
torch.sqrt(input=my_tensor)
# tensor([[2.6458, nan, 2.2361, nan],
#         [nan, nan, 0.0000, 2.4495]])

my_tensor = torch.tensor([[[7, -1],
                           [5, -7]],
                          [[-9, -3],
                           [0, 6]]])
torch.sqrt(input=my_tensor)
# tensor([[[2.6458, nan],
#          [2.2361, nan]],
#         [[nan, nan],
#          [0.0000, 2.4495]]])

my_tensor = torch.tensor([[[7., -1.],
                           [5., -7.]],
                          [[-9., -3.],
                           [0., 6.]]])
torch.sqrt(input=my_tensor)
# tensor([[[2.6458, nan],
#          [2.2361, nan]],
#         [[nan, nan],
#          [0.0000, 2.4495]]])

my_tensor = torch.tensor([[[7.+0.j, -1.+0.j],
                           [5.+0.j, -7.+0.j]],
                          [[-9.+0.j, -3.+0.j],
                           [0.+0.j, 6.+0.j]]])
torch.sqrt(input=my_tensor)
# tensor([[[2.6458+0.0000j, 0.0000+1.0000j],
#          [2.2361+0.0000j, 0.0000+2.6458j]],
#         [[0.0000+3.0000j, 0.0000+1.7321j],
#          [0.0000+0.0000j, 2.4495+0.0000j]]])

my_tensor = torch.tensor([[[True, False],
                           [True, False]],
                          [[False, True],
                           [False, True]]])
torch.sqrt(input=my_tensor)
# tensor([[[1., 0.],
#          [1., 0.]],
#         [[0., 1.],
#          [0., 1.]]])
Enter fullscreen mode Exit fullscreen mode
💖 💪 🙅 🚩
hyperkai
Super Kai (Kazuya Ito)

Posted on May 17, 2024

Join Our Newsletter. No Spam, Only the good stuff.

Sign up to receive the latest update from our blog.

Related

abs and sqrt in PyTorch
python abs and sqrt in PyTorch

May 17, 2024