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 ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org