*Memos:
- My post explains min(), max(), argmin() and argmax()
- My post explains minimum(), maximum(), kthvalue() and topk().
aminmax() can get the one or more minimum and maximum values of a 0D or more D tensor as shown below:
*Memos:
-
aminmax()can be called both from torch and a tensor. - Setting a dimension(
dim) to the 2nd argument withtorchor the 1st argument with a tensor gets zero or more 1st minimum and maximum values. *You must usedim=. - Only zero or more integers, floating-point numbers or boolean values can be used so zero or more complex numbers cannot be used except the 0D tensor of a complex number with
dim=0ordim=-1.
import torch
my_tensor = torch.tensor([[5, 4, 7, 7],
[6, 5, 3, 5],
[3, 8, 9, 3]])
torch.aminmax(my_tensor)
my_tensor.aminmax()
# torch.return_types.aminmax(
# min=tensor(3),
# max=tensor(9))
torch.aminmax(my_tensor, dim=0)
my_tensor.aminmax(dim=0)
torch.aminmax(my_tensor, dim=-2)
my_tensor.aminmax(dim=-2)
# torch.return_types.aminmax(
# min=tensor([3, 4, 3, 3]),
# max=tensor([6, 8, 9, 7]))
torch.aminmax(my_tensor, dim=1)
my_tensor.aminmax(dim=1)
torch.aminmax(my_tensor, dim=-1)
my_tensor.aminmax(dim=-1)
# torch.return_types.aminmax(
# min=tensor([4, 3, 3]),
# max=tensor([7, 6, 9]))
my_tensor = torch.tensor([[5., 4., 7., 7.],
[6., True, 3., 5.],
[3., 8., False, 3.]])
torch.aminmax(my_tensor, dim=0)
my_tensor.aminmax(dim=0)
torch.aminmax(my_tensor, dim=-2)
my_tensor.aminmax(dim=-2)
# torch.return_types.aminmax(
# min=tensor([3., 1., 0., 3.]),
# max=tensor([6., 8., 7., 7.]))
my_tensor = torch.tensor(5+7j)
torch.aminmax(my_tensor, dim=0)
my_tensor.aminmax(dim=0)
torch.aminmax(my_tensor, dim=-1)
my_tensor.aminmax(dim=-1)
# torch.return_types.aminmax(
# min=tensor(5.+7.j),
# max=tensor(5.+7.j))
amin() can get the one or more minimum values of a 0D or more D tensor as shown below:
*Memos:
-
amin()can be called both fromtorchand a tensor. - Setting a dimension(
dim) to the 2nd argument withtorchor the 1st argument with a tensor gets zero or more 1st minimum values. *You must usedim=. - Only zero or more integers, floating-point numbers or boolean values can be used so zero or more complex numbers cannot be used.
import torch
my_tensor = torch.tensor([[5, 4, 7, 7],
[6, 5, 3, 5],
[3, 8, 9, 3]])
torch.amin(my_tensor)
my_tensor.amin()
# tensor(3)
torch.amin(my_tensor, dim=0)
my_tensor.amin(dim=0)
torch.amin(my_tensor, dim=-2)
my_tensor.amin(dim=-2)
# tensor([3, 4, 3, 3])
torch.amin(my_tensor, dim=1)
my_tensor.amin(dim=1)
torch.amin(my_tensor, dim=-1)
my_tensor.amin(dim=-1)
# tensor([4, 3, 3])
my_tensor = torch.tensor([[5., 4., 7., 7.],
[6., True, 3., 5.],
[3., 8., False, 3.]])
torch.amin(my_tensor, dim=0)
my_tensor.amin(dim=0)
torch.amin(my_tensor, dim=-2)
my_tensor.amin(dim=-2)
# tensor([3., 1., 0., 3.])
amax() can get the one or more maximum values of a 0D or more D tensor as shown below:
*Memos:
-
amax()can be called both fromtorchand a tensor. - Setting a dimension(
dim) to the 2nd argument withtorchor the 1st argument with a tensor gets zero or more 1st maximum values. *You must usedim=. - Only zero or more integers, floating-point numbers or boolean values can be used so zero or more complex numbers cannot be used.
import torch
my_tensor = torch.tensor([[5, 4, 7, 7],
[6, 5, 3, 5],
[3, 8, 9, 3]])
torch.amax(my_tensor)
my_tensor.amax()
# tensor(9)
torch.amax(my_tensor, dim=0)
my_tensor.amax(dim=0)
torch.amax(my_tensor, dim=-2)
my_tensor.amax(dim=-2)
# tensor([6, 8, 9, 7])
torch.amax(my_tensor, dim=1)
my_tensor.amax(dim=1)
torch.amax(my_tensor, dim=-1)
my_tensor.amax(dim=-1)
# tensor([7, 6, 9])
my_tensor = torch.tensor([[5., 4., 7., 7.],
[6., True, 3., 5.],
[3., 8., False, 3.]])
torch.amax(my_tensor, dim=0)
my_tensor.amax(dim=0)
torch.amax(my_tensor, dim=-2)
my_tensor.amax(dim=-2)
# tensor([6., 8., 7., 7.])
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