*Memos:
- My post explains min() and max().
- My post explains minimum() and maximum().
- My post explains fmin() and fmax().
- My post explains aminmax(), amin() and amax().
- My post explains kthvalue() and topk().
- My post explains cummin() and cummax().
argmin() can get the 0D or more D tensor of the zero or more indices of the 1st minimum elements from the 0D or more D tensor of zero or more elements as shown below:
*Memos:
-
argmin()can be used with torch or a tensor. - The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofintorfloat). - The 2nd argument with
torchor the 1st argument isdim(Optional-Type:int). *Settingdimcan get the zero or more indices of the 1st minimum elements. - The 3rd argument with
torchor the 2nd argument iskeepdim(Optional-Default:False-Type:bool). *My post explainskeepdimargument. - The 1D or more D tensor of one complex number or boolean value with
dimworks. - An empty 2D or more D
inputtensor or tensor doesn't work if not settingdim. - An empty 1D
inputtesnor or tensor doesn't work even if settingdim.
import torch my_tensor = torch.tensor([[5, 4, 7, 7], [6, 5, 3, 5], [3, 8, 9, 3]]) torch.argmin(input=my_tensor) my_tensor.argmin() # tensor(6) torch.argmin(input=my_tensor, dim=0) torch.argmin(input=my_tensor, dim=-2) # tensor([2, 0, 1, 2]) torch.argmin(input=my_tensor, dim=1) torch.argmin(input=my_tensor, dim=-1) # tensor([1, 2, 0]) my_tensor = torch.tensor([[5., 4., 7., 7.], [6., 5., 3., 5.], [3., 8., 9., 3.]]) torch.argmin(input=my_tensor) # tensor(6) my_tensor = torch.tensor([5.+7.j]) torch.argmin(input=my_tensor, dim=0) # tensor(0) my_tensor = torch.tensor([[True]]) torch.argmin(input=my_tensor, dim=0) # tensor([0]) my_tensor = torch.tensor([]) my_tensor = torch.tensor([[]]) my_tensor = torch.tensor([[[]]]) torch.argmin(input=my_tensor) # Error my_tensor = torch.tensor([]) torch.argmin(input=my_tensor, dim=0) # Error my_tensor = torch.tensor([[]]) torch.argmin(input=my_tensor, dim=0) # tensor([], dtype=torch.int64) my_tensor = torch.tensor([[[]]]) torch.argmin(input=my_tensor, dim=0) # tensor([], size=(1, 0), dtype=torch.int64) argmax() can get the 0D or more D tensor of the zero or more indices of the 1st maximum elements from the 0D or more D tensor of zero or more elements as shown below:
*Memos:
-
argmax()can be used withtorchor a tensor. - The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofintorfloat). - The 2nd argument with
torchor the 1st argument isdim(Optional-Type:int). *Settingdimcan get the zero or more indices of the 1st maximum elements. - The 3rd argument with
torchor the 2nd argument iskeepdim(Optional-Default:False-Type:bool). *My post explainskeepdimargument. - The 1D or more D tensor of one complex number or boolean value with
dimworks. - An empty 2D or more D
inputtensor or tensor doesn't work if not settingdim. - An empty 1D
inputtesnor or tensor doesn't work even if settingdim.
import torch my_tensor = torch.tensor([[5, 4, 7, 7], [6, 5, 3, 5], [3, 8, 9, 3]]) torch.argmax(input=my_tensor) my_tensor.argmax() # tensor(10) torch.argmax(input=my_tensor, dim=0) torch.argmax(input=my_tensor, dim=-2) # tensor([1, 2, 2, 0]) torch.argmax(input=my_tensor, dim=1) torch.argmax(input=my_tensor, dim=-1) # tensor([2, 0, 2]) my_tensor = torch.tensor([[5., 4., 7., 7.], [6., 5., 3., 5.], [3., 8., 9., 3.]]) torch.argmax(input=my_tensor) # tensor(10) my_tensor = torch.tensor([5.+7.j]) torch.argmax(input=my_tensor, dim=0) # tensor(0) my_tensor = torch.tensor([[True]]) torch.argmax(input=my_tensor, dim=0) # tensor([0]) my_tensor = torch.tensor([]) my_tensor = torch.tensor([[]]) my_tensor = torch.tensor([[[]]]) torch.argmax(input=my_tensor) # Error my_tensor = torch.tensor([]) torch.argmax(input=my_tensor, dim=0) # Error my_tensor = torch.tensor([[]]) torch.argmax(input=my_tensor, dim=0) # tensor([], dtype=torch.int64) my_tensor = torch.tensor([[[]]]) torch.argmax(input=my_tensor, dim=0) # tensor([], size=(1, 0), dtype=torch.int64) 
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