*My post explains abs() and sqrt().
gcd() can get the 0D or more D tensor of zero or more greatest common divisors from two of the 0D or more D tensors of zero or more elements as shown below:
*Memos:
-
gcd()can be used with torch or a tensor. - The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofint). - The 2nd argument with
torchor the 1st argument isother(Required-Type:tensorofint). - There is
outargument withtorch(Optional-Default:None-Type:tensor): *Memos:-
out=must be used. -
My post explains
outargument.
-
import torch
tensor1 = torch.tensor(16)
tensor2 = torch.tensor([-40, -30, -20, -10, 0, 10, 20, 30])
torch.gcd(input=tensor1, other=tensor2)
tensor1.gcd(other=tensor2)
torch.gcd(input=tensor2, other=tensor1)
# tensor([8, 2, 4, 2, 16, 2, 4, 2])
tensor1 = torch.tensor([16, -12, -15, 1, 9, -25, 0, -18])
tensor2 = torch.tensor([-40, -30, -20, -10, 0, 10, 20, 30])
torch.gcd(input=tensor1, other=tensor2)
torch.gcd(input=tensor2, other=tensor1)
# tensor([8, 6, 5, 1, 9, 5, 20, 6])
tensor1 = torch.tensor([[16, -12, -15, 1], [9, -25, 0, -18]])
tensor2 = torch.tensor([0, 10, 20, 30])
torch.gcd(input=tensor1, other=tensor2)
torch.gcd(input=tensor2, other=tensor1)
# tensor([[16, 2, 5, 1], [9, 5, 20, 6]])
tensor1 = torch.tensor([[[16, -12], [-15, 1]],
[[9, -25], [0, -18]]])
tensor2 = torch.tensor([0, 10])
torch.gcd(input=tensor1, other=tensor2)
torch.gcd(input=tensor2, other=tensor1)
# tensor([[[16, 2], [15, 1]],
# [[9, 5], [0, 2]]])
lcm() can get the 0D or more D tensor of zero or more least common multiples from two of the 0D or more D tensors of zero or more elements as shown below:
*Memos:
-
lcm()can be used withtorchor a tensor. - The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofint). - The 2nd argument with
torchor the 1st argument isother(Required-Type:tensorofint). - There is
outargument withtorch(Optional-Default:None-Type:tensor): *Memos:-
out=must be used. -
My post explains
outargument.
-
import torch
tensor1 = torch.tensor(10)
tensor2 = torch.tensor([-4, -3, -2, -1, 0, 1, 2, 3])
torch.lcm(input=tensor1, other=tensor2)
tensor1.lcm(other=tensor2)
torch.lcm(input=tensor2, other=tensor1)
# tensor([20, 30, 10, 10, 0, 10, 10, 30])
tensor1 = torch.tensor([10, 1, -15, 4, 9, -6, 0, -5])
tensor2 = torch.tensor([-4, -3, -2, -1, 0, 1, 2, 3])
torch.lcm(input=tensor1, other=tensor2)
torch.lcm(input=tensor2, other=tensor1)
# tensor([20, 3, 30, 4, 0, 6, 0, 15])
tensor1 = torch.tensor([[10, 1, -15, 4], [9, -6, 0, -5]])
tensor2 = torch.tensor([0, 1, 2, 3])
torch.lcm(input=tensor1, other=tensor2)
torch.lcm(input=tensor2, other=tensor1)
# tensor([[0, 1, 30, 12], [0, 6, 0, 15]])
tensor1 = torch.tensor([[[10, 1], [-15, 4]], [[9, -6], [0, -5]]])
tensor2 = torch.tensor([0, 1])
torch.lcm(input=tensor1, other=tensor2)
torch.lcm(input=tensor2, other=tensor1)
# tensor([[[0, 1], [0, 4]],
# [[0, 6], [0, 5]]])
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