aravindhv10 opened a new issue #13087: softmax in symbol api URL: https://github.com/apache/incubator-mxnet/issues/13087 Hello, I want to have softmax activation with linear regression output, I was able to get this in gluon in the following way: class CenteredLayer(mx.gluon.nn.HybridSequential): def __init__(self, **kwargs): super(CenteredLayer, self).__init__(**kwargs) def forward(self, x): return x.softmax() net = gluon.nn.HybridSequential() with net.name_scope(): net.add ( gluon.nn.Dense ( sizes[1] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[2] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[3] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[4] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[5] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[4] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[3] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[2] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[1] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[0] , activation="relu" ) ) net.add ( gluon.nn.Dense ( sizes[0] ) ) net.add ( CenteredLayer() ) But now I want to get this in the symbol c++ api, I donot want the cross entropy softmax output but only softmax activation with
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