[GitHub] piiswrong closed pull request #8254: Fix softmax_cross_entropy

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

piiswrong closed pull request #8254: Fix softmax_cross_entropy
URL: https://github.com/apache/incubator-mxnet/pull/8254
 
 
   

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diff --git a/src/operator/loss_binary_op.cc b/src/operator/loss_binary_op.cc
index d0a77946ff..3e7d15c317 100644
--- a/src/operator/loss_binary_op.cc
+++ b/src/operator/loss_binary_op.cc
@@ -58,6 +58,10 @@ Example::
 )code" ADD_FILELINE)
 .set_num_inputs(2)
 .set_num_outputs(1)
+.set_attr<nnvm::FListInputNames>("FListInputNames",
+  [](const NodeAttrs& attrs) {
+    return std::vector<std::string>{"data", "label"};
+  })
 .set_attr<nnvm::FInferShape>("FInferShape", SoftmaxCrossEntropyShape)
 .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>)
 .set_attr<FResourceRequest>("FResourceRequest",
diff --git a/tests/python/unittest/test_operator.py b/tests/python/unittest/test_operator.py
index b4e49a98b4..59f2d1ea40 100644
--- a/tests/python/unittest/test_operator.py
+++ b/tests/python/unittest/test_operator.py
@@ -292,6 +292,29 @@ def test_softmax():
     check_softmax_with_shape((3, 4, 2), default_context(), preserve_shape=True)
 
 
+def test_softmax_cross_entropy():
+    batch_size = 32
+    num_class = 20
+
+    data = mx.sym.Variable("data")
+    label = mx.sym.Variable("softmax_label")
+    conv = mx.sym.Convolution(data=data, kernel=(2, 2), num_filter=5)
+    flatten = mx.sym.Flatten(data=conv)
+    fc = mx.sym.FullyConnected(data=flatten, num_hidden=num_class)
+    out = mx.sym.softmax_cross_entropy(data=fc, label=label)
+
+    data_shape = (batch_size , 3, 64, 64)
+    label_shape = (batch_size,)
+    mod = mx.mod.Module(symbol=out)
+    mod.bind(data_shapes=[('data', data_shape)],
+             label_shapes=[('softmax_label', label_shape)])
+    mod.init_params()
+    mod.init_optimizer(optimizer_params={'learning_rate': 0.01})
+    mod.forward(mx.io.DataBatch(data=[mx.ndarray.normal(0, 10, shape=data_shape)],
+                                label=[mx.ndarray.arange(0, batch_size)]))
+    assert mod.get_outputs()[0].shape == (1,)
+
+
 def test_python_op():
     X = mx.symbol.Variable('X')
     op = mx.operator.NumpyOp()


 

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