*Memos:
- My post explainsmin() andmax().
- My post explainsfmin() andfmax().
- My post explainsargmin() andargmax().
- My post explainsaminmax(),amin() andamax().
- My post explainskthvalue() andtopk().
- My post explainscummin() andcummax().
minimum() can get the 0D or more D tensor of zero or more minimum elements prioritizingnan from two of the 0D or more D tensors of zero or more elements as shown below:
*Memos:
minimum()can be used withtorch or a tensor.- The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofint,floatorbool). - The 2nd argument with
torchor the 1st argument isother(Required-Type:tensorofint,floatorbool). - There is
outargument withtorch(Optional-Default:None-Type:tensor):*Memos:out=must be used.- My post explains
outargument.
nanis taken if there are a number andnan.
importtorchtensor1=torch.tensor([5.,float('nan'),4.,float('nan')])tensor2=torch.tensor([[7.,8.,float('nan'),float('nan')],[-9.,2.,0.,-6.]])torch.minimum(input=tensor1,other=tensor2)tensor1.minimum(other=tensor2)# tensor([[5., nan, nan, nan],# [-9., nan, 0., nan]])tensor1=torch.tensor(5.)tensor2=torch.tensor([[[7.,8.],[float('nan'),float('nan')]],[[-9.,2.],[0.,-6.]]])torch.minimum(input=tensor1,other=tensor2)# tensor([[[5., 5.], [nan, nan]],# [[-9., 2.], [0., -6.]]])tensor1=torch.tensor(5)tensor2=torch.tensor([[[7,8],[-5,-1]],[[-9,2],[0,-6]]])torch.minimum(input=tensor1,other=tensor2)# tensor([[[5, 5], [-5, -1]],# [[-9, 2], [0, -6]]])tensor1=torch.tensor(True)tensor2=torch.tensor([[[True,False],[True,False]],[[False,True],[False,True]]])torch.minimum(input=tensor1,other=tensor2)# tensor([[[True, False], [True, False]],# [[False, True], [False, True]]])maximum() can get the 0D or more D tensor of zero or more maximum elements prioritizingnan from two of the 0D or more D tensors of zero or more elements as shown below:
*Memos:
maximum()can be used withtorchor a tensor.- The 1st argument(
input) withtorchor using a tensor(Required-Type:tensorofint,floatorbool). - The 2nd argument with
torchor the 1st argument isother(Required-Type:tensorofint,floatorbool). - There is
outargument withtorch(Optional-Default:None-Type:tensor):*Memos:out=must be used.- My post explains
outargument.
nanis taken if there are a number andnan.
importtorchtensor1=torch.tensor([5.,float('nan'),4.,float('nan')])tensor2=torch.tensor([[7.,8.,float('nan'),float('nan')],[-9.,2.,0.,-6.]])torch.maximum(input=tensor1,other=tensor2)tensor1.maximum(other=tensor2)# tensor([[7., nan, nan, nan],# [5., nan, 4., nan]])tensor1=torch.tensor(5.)tensor2=torch.tensor([[[7.,8.],[float('nan'),float('nan')]],[[-9.,2.],[0.,-6.]]])torch.maximum(input=tensor1,other=tensor2)# tensor([[[7., 8.], [nan, nan]],# [[5., 5.], [5., 5.]]])tensor1=torch.tensor(5)tensor2=torch.tensor([[[7,8],[-5,-1]],[[-9,2],[0,-6]]])torch.maximum(input=tensor1,other=tensor2)# tensor([[[7, 8], [5, 5]],# [[5, 5], [5, 5]]])tensor1=torch.tensor(True)tensor2=torch.tensor([[[True,False],[True,False]],[[False,True],[False,True]]])torch.maximum(input=tensor1,other=tensor2)# tensor([[[True, True], [True, True]],# [[True, True], [True, True]]])Top comments(0)
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