how the code '-input[range(target.shape[0]),target]' works?
Question:
I’m learing pytorch.Reading the official tutorial,I met the preplexing code.
input is a tensor, so is target.
def nll(input,target):
return -input[range(target.shape[0]),target].mean()
And the pred is:
target is:
the ‘-input[range(target.shape[0]),target]’ is:
!['input[range(target.shape[0],target]'](https://i.stack.imgur.com/0gcq9.png)
Output shows this is not substracting target from input or merging two tensors
Answers:
The code input[range(target.shape[0]), target] simply picks, from each row i of input the element at column indicated by the corresponding element of target, that is target[i].
In other words, if out = input[range(target.shape[0]), target] then out[i] = input[i, target[i]].
This is very similar to torch.gather.
I’m learing pytorch.Reading the official tutorial,I met the preplexing code.
input is a tensor, so is target.
def nll(input,target):
return -input[range(target.shape[0]),target].mean()
And the pred is:
target is:
the ‘-input[range(target.shape[0]),target]’ is:
Output shows this is not substracting target from input or merging two tensors
The code input[range(target.shape[0]), target] simply picks, from each row i of input the element at column indicated by the corresponding element of target, that is target[i].
In other words, if out = input[range(target.shape[0]), target] then out[i] = input[i, target[i]].
This is very similar to torch.gather.