[GitHub] CircleXing001 commented on issue #11006: bug about sum in loss

[GitBox <gi...@apache.org>]

CircleXing001 commented on issue #11006: bug about sum in loss
URL: https://github.com/apache/incubator-mxnet/issues/11006#issuecomment-390560631
 
 
   `data = mx.symbol.Variable('data')
   
   label = mx.symbol.Variable('softmax_label')
   
   conv1=mx.symbol.Convolution(data,kernel=(5,5),stride=(1,1),pad=(2,2),num_filter=32)
   
   fc1=mx.symbol.Activation(conv1,act_type='relu')
   
   pool1=mx.symbol.Pooling(fc1,kernel=(2,2),pool_type='max',stride=(2,2))
   
   conv2=mx.symbol.Convolution(pool1,kernel=(5,5),stride=(1,1),pad=(2,2),num_filter=64)
   
   fc2=mx.symbol.Activation(conv2,act_type='relu')
   
   pool2=mx.symbol.Pooling(fc2,kernel=(2,2),pool_type='max',stride=(2,2))
   
   fc3=mx.sym.Reshape(pool2,shape=(-1,7*7*64))
   
   fc4=mx.symbol.FullyConnected(fc3,num_hidden=1024)
   
   fc5=mx.symbol.Activation(fc4,act_type='relu')
   
   drop1=mx.symbol.Dropout(fc5,p=0.5)
   
   fc6=mx.symbol.FullyConnected(drop1,num_hidden=10)
   
   fc7=mx.symbol.softmax(fc6)
   
   out=mx.symbol.MakeLoss(-mx.symbol.sum(label*mx.symbol.log(fc7)))`
   i use the mnist dataset with data-shape (-1,1,28,28) and label-shape(-1,10).
   after i use the MakeLoss,when  i run it,the python doesnt work and kill the kernel.
   in ubantu and windows it did the same thing.and the version is mxnet 1.1.0.
   thanks for your   reply. @ankkhedia 

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