John1231983 opened a new issue #18333:
URL: https://github.com/apache/incubator-mxnet/issues/18333
Given a softmax classified feature ff (`Bx2xHxW`). And a target label size
of `Bx1xHxW` . I want to implement cross entropy loss using symbol only. This
is my implementation
```
# target size of Bx1xHxW
target_squeeze = mx.symbol.squeeze(target, axis=1) #size of BxHxW
target_squeeze = mx.sym.one_hot(target_squeeze, depth = 2, on_value = -1.0,
off_value = 0.0)
# Transpose from BxHxWx2 to Bx2xHxW
target_squeeze = mx.symbol.transpose(target_squeeze, axes=(0,3,1,2))
# Get log of feature f
f_log = mx.sym.log(f)
batch_size =32
f_sum = mx.symbol.sum(target_squeeze * f_log)/batch_size
f_sum = mx.symbol.MakeLoss(f_sum, name = 'loss_ce')
```
Is my implementation correct? If not, please correct it for me. Thanks in
advantage
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