*Memos:
- My post explains square().
- My post explains float_power().
- My post explains abs() and sqrt().
- My post explains gcd() and lcm().
- My post explains trace(), reciprocal() and rsqrt().
pow() can get the 0D or more D tensor of zero or more powers from 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 as shown below:
*Memos:
-
pow()can be used with torch or a tensor. - The 1st argument(
input) withtorch(Required-Type:tensororscalarofint,floatorcomplex) or using a tensor(Required-Type:tensorofint,floatorcomplex). *torchmust use a scalar withoutinput=. - The 2nd argument with
torchor the 1st argument with a tensor isexponent(Required-Type:tensororscalarofint,floatorcomplex). *A negative scalar cannot be used. - There is
outargument withtorch(Optional-Default:None-Type:tensor): *Memos:-
out=must be used. - My post explains
outargument.
-
- The combination of a scalar(
inputor a tensor) and a scalar(exponent) cannot be used. - The combination of a tensor(
input(bool) or a tensor(bool)) and a scalar(exponent(bool)) works.
import torch tensor1 = torch.tensor(-3) tensor2 = torch.tensor([-4, -3, -2, -1, 0, 1, 2, 3]) torch.pow(input=tensor1, exponent=tensor2) tensor1.pow(exponent=tensor2) # tensor([0, 0, 0, 0, 1, -3, 9, -27]) torch.pow(-3, exponent=tensor2) # tensor([0, 0, 0, 0, 1, -3, 9, -27]) torch.pow(input=tensor1, exponent=3) # tensor(-27) tensor1 = torch.tensor([-3, 1, -2, 3, 5, -5, 0, -4]) tensor2 = torch.tensor([-4, -3, -2, -1, 0, 1, 2, 3]) torch.pow(input=tensor1, exponent=tensor2) # tensor([0, 1, 0, 0, 1, -5, 0, -64]) torch.pow(-3, exponent=tensor2) # tensor([0, 0, 0, 0, 1, -3, 9, -27]) torch.pow(input=tensor1, exponent=3) # tensor([-27, 1, -8, 27, 125, -125, 0, -64]) tensor1 = torch.tensor([[-3, 1, -2, 3], [5, -5, 0, -4]]) tensor2 = torch.tensor([0, 1, 2, 3]) torch.pow(input=tensor1, exponent=tensor2) # tensor([[1, 1, 4, 27], [1, -5, 0, -64]]) torch.pow(-3, exponent=tensor2) # tensor([1, -3, 9, -27]) torch.pow(input=tensor1, exponent=3) # tensor([[-27, 1, -8, 27], [125, -125, 0, -64]]) tensor1 = torch.tensor([[[-3, 1], [-2, 3]], [[5, -5], [0, -4]]]) tensor2 = torch.tensor([2, 3]) torch.pow(input=tensor1, exponent=tensor2) # tensor([[[9, 1], [4, 27]], # [[25, -125], [0, -64]]]) torch.pow(-3, exponent=tensor2) # tensor([9, -27]) torch.pow(input=tensor1, exponent=3) # tensor([[[-27, 1], [-8, 27]], # [[125, -125], [0, -64]]]) tensor1 = torch.tensor([[[-3., 1.], [-2., 3.]], [[5., -5.], [0., -4.]]]) tensor2 = torch.tensor([2., 3.]) torch.pow(input=tensor1, exponent=tensor2) # tensor([[[9., 1.], [4., 27.]], # [[25., -125.], [0., -64.]]]) torch.pow(-3., exponent=tensor2) # tensor([9., -27.]) torch.pow(input=tensor1, exponent=3.) # tensor([[[-27., 1.], [-8., 27.]], # [[125., -125.], [0., -64.]]]) tensor1 = torch.tensor([[[-3.+0.j, 1.+0.j], [-2.+0.j, 3.+0.j]], [[5.+0.j, -5.+0.j], [0.+0.j, -4.+0.j]]]) tensor2 = torch.tensor([2.+0.j, 3.+0.j]) torch.pow(input=tensor1, exponent=tensor2) # tensor([[[9.0000+1.5736e-06j, 1.0000+0.0000e+00j], # [4.0000+6.9938e-07j, 27.0000+0.0000e+00j]], # [[25.0000+0.0000e+00j, -125.0000-2.9812e-06j], # [0.0000-0.0000e+00j, -64.0000-1.5264e-06j]]]) torch.pow(-3.+0.j, exponent=tensor2) # tensor([9.0000+1.5736e-06j, -27.0000-6.4394e-07j]) torch.pow(input=tensor1, exponent=3.+0.j) # tensor([[[-27.+0.j, 1.+0.j], # [-8.+0.j, 27.+0.j]], # [[125.+0.j, -125.+0.j], # [0.+0.j, -64.+0.j]]]) my_tensor = torch.tensor([[[True, False], [True, False]], [[False, True], [False, True]]]) torch.pow(input=my_tensor, exponent=True) # tensor([[[True, False], [True, False]], # [[False, True], [False, True]]]) 
Top comments (0)