From 6090a415850def1ea83a63dda91d9f66850968d8 Mon Sep 17 00:00:00 2001
From: Yiyan66 <yiyanwang66@gmail.com>
Date: Wed, 18 Dec 2019 08:43:09 +0000
Subject: [PATCH] ok

---
 src/operator/numpy/np_broadcast_reduce_op.h   | 22 ++++++++-----------
 .../numpy/np_broadcast_reduce_op_value.cc     |  1 -
 2 files changed, 9 insertions(+), 14 deletions(-)

diff --git a/src/operator/numpy/np_broadcast_reduce_op.h b/src/operator/numpy/np_broadcast_reduce_op.h
index 58af6f617186..2583adc69abb 100644
--- a/src/operator/numpy/np_broadcast_reduce_op.h
+++ b/src/operator/numpy/np_broadcast_reduce_op.h
@@ -25,7 +25,6 @@
 #ifndef MXNET_OPERATOR_NUMPY_NP_BROADCAST_REDUCE_OP_H_
 #define MXNET_OPERATOR_NUMPY_NP_BROADCAST_REDUCE_OP_H_
 
-#include <mshadow/tensor.h>
 #include <algorithm>
 #include <vector>
 #include <string>
@@ -902,12 +901,11 @@ struct median_forward {
 
 template<typename xpu>
 void NumpyMedianForward(const nnvm::NodeAttrs& attrs,
-                          const OpContext& ctx,
-                          const std::vector<TBlob>& inputs,
-                          const std::vector<OpReqType>& req,
-                          const std::vector<TBlob>& outputs) {
-  if (req[0] == kNullOp)
-    return;
+                        const OpContext& ctx,
+                        const std::vector<TBlob>& inputs,
+                        const std::vector<OpReqType>& req,
+                        const std::vector<TBlob>& outputs) {
+  if (req[0] == kNullOp) return;
 
   using namespace mxnet;
   using namespace mxnet_op;
@@ -1156,10 +1154,10 @@ void NumpyMedianForward(const nnvm::NodeAttrs& attrs,
                                       element_num)), 0, k), Shape3(0, 2, 1)));
         ASSIGN_DISPATCH(ret_indices, req_TopK[1], tcast<index_t>(F<mshadow_op::mod>(transpose(
                         slice<2>(inplace_reshape(indices,
-                                                Shape3(ret_indices.shape_[0],
-                                                        ret_indices.shape_[2],
-                                                        element_num)),
-                                0, k), Shape3(0, 2, 1)), element_num)));
+                                 Shape3(ret_indices.shape_[0],
+                                 ret_indices.shape_[2],
+                                 element_num)),
+                                 0, k), Shape3(0, 2, 1)), element_num)));
       } else {
         Tensor<xpu, 2, DType> ret_value =
           ret[0].get_with_shape<xpu, 2, DType>(Shape2(batch_size, k), s);
@@ -1172,8 +1170,6 @@ void NumpyMedianForward(const nnvm::NodeAttrs& attrs,
       }
     }
 
-
-
     MXNET_NDIM_SWITCH(small.ndim()+1, NDim, {
       Kernel<median_forward<NDim>, xpu>::Launch(
           s, r_shape.Size(), r.dptr<DType>(), a_sort.dptr<DType>(),
diff --git a/src/operator/numpy/np_broadcast_reduce_op_value.cc b/src/operator/numpy/np_broadcast_reduce_op_value.cc
index de17858f3d87..d1a4625e83ff 100644
--- a/src/operator/numpy/np_broadcast_reduce_op_value.cc
+++ b/src/operator/numpy/np_broadcast_reduce_op_value.cc
@@ -348,7 +348,6 @@ NNVM_REGISTER_OP(_npi_median)
   [](const NodeAttrs& attrs) {
     return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};
   })
-// .set_attr<THasDeterministicOutput>("THasDeterministicOutput", true)
 .set_attr<nnvm::FGradient>("FGradient", MakeZeroGradNodes);
 
 inline bool NumpyMeanType(const nnvm::NodeAttrs& attrs,