[GitHub] [incubator-mxnet] haojin2 commented on a change in pull request #15161: Numpy compatible max

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

haojin2 commented on a change in pull request #15161: Numpy compatible max
URL: https://github.com/apache/incubator-mxnet/pull/15161#discussion_r292573813
 
 

 ##########
 File path: src/operator/numpy/np_broadcast_reduce_op.h
 ##########
 @@ -152,6 +170,38 @@ inline bool NumpyReduceAxesShape(const nnvm::NodeAttrs& attrs,
   return shape_is_known(out_attrs->at(0));
 }
 
+inline bool NumpyMaxShape(const nnvm::NodeAttrs& attrs,
+                                 std::vector<TShape> *in_attrs,
+                                 std::vector<TShape> *out_attrs) {
+  CHECK_EQ(in_attrs->size(), 1U);
+  CHECK_EQ(out_attrs->size(), 1U);
+  if (!shape_is_known(in_attrs->at(0))) {
+    return false;
+  }
+  const NumpyMaxParam& param = nnvm::get<NumpyMaxParam>(attrs.parsed);
+  // check the case where the reduction axis should not be zero
+  bool is_all_reducded_axes_not_zero = true;
+  const TShape& ishape = (*in_attrs)[0];
+  if (param.axis.has_value()) {
+    const mxnet::Tuple<int>& axes = param.axis.value();
+    for (int i = 0; i < axes.ndim(); ++i) {
+      if (ishape[axes[i]] == 0) {
+        is_all_reducded_axes_not_zero = false;
 
 Review comment:
   you can just `break;` here so that you skip the extra loops afterwards.

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