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Posted to commits@mxnet.apache.org by ta...@apache.org on 2019/09/29 02:31:08 UTC

[incubator-mxnet] branch mkldnn-v1.0 updated (ce5ec06 -> 4fba4c3)

This is an automated email from the ASF dual-hosted git repository.

taolv pushed a change to branch mkldnn-v1.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git.


    from ce5ec06  [mkldnn-v1.0] Add MKL-DNN Transpose (#16250)
     add f5d8fbf  New Website: Remove Old Content [2/3] (#15885)
     add 6af6570  fix flaky test (#16191)
     add 6247dc8  [Numpy] Differentiable svd (#15795)
     add a783d81  add epsilon to sum(pvalue) upperbound (#16211)
     add 7126438  New Website: New Pipeline [3/3] (#15883)
     add 986cecd  Update MKL-DNN dependency (#16073)
     add d61ed3f  Solve #14116, #15143 (#15144)
     add 618c481  [MXNET-1422] Fix wrong results of min([inf, inf]) and max([-inf,-inf]) (#16226)
     add be7296b  removing MXNDArrayLoadFromBuffer64 and MXNDArrayLoad64 (#16203)
     add 11f73ed  np compatible vstack (#15850)
     add 37c641f  Faster Scala NDArray to BufferedImage function (#16219)
     add 93b794e  Fix inconsistent interpolation method values (#16212)
     add 89cb4ad  Numpy add numpy op roll (#15902)
     add da6e744  add numpy compatible trace (#16008)
     add 53ebe12  add numpy op hanning, hamming, blackman (#15815)
     add 0994ea0  julia: implement `context.num_gpus` (#16236)
     add 8e48cec  julia: add `AbstractMXError` as parent type (#16235)
     add dccfc88  [Numpy]flip (#15819)
     add 7344c91  numpy operator around (#16126)
     add 8af1b57  numpy operator arctan2 (#15890)
     add ae2f1bb  numpy operator nonzero (#15838)
     add bea5653  numpy operator hypot (#15901)
     add 72b4d9b  tvm numpy operator deg2rad && rad2deg (#16015)
     add a77bd75  Integrate MKL-DNN leakyrelu (#16075)
     add cbbb96a  [CD] Add COMMIT_ID param to release job (#16202)
     add f635595  numpy op unique
     add 08f8372  try to fix bug
     add 3ca1920  fix memory bug and disable some test
     add 33bd02f  fix according to review
     add 1d4032d  set fixed seed for profiler (#16155)
     add a5e698a  FullyConnected Bias performance improvement on GPU (#16039)
     add 35ef45c  Fix lack of dylib support in Makefile when use lapack (#15813)
     add 985a4ca  Update KL Divergence formula (#16170)
     add ab2214b  fix broken links (#16255)
     add df34e76  Add list_ctx to ParameterDict (#16185)
     add 1a2da12  [MKLDNN] NDArray reorder in C API and deconv (#16265)
     add c5007ea  Numpy operators: `lcm`, `tril`, `identity` and `take` (#16264)
     add c69c8bf  redirect to the 404 page (#16287)
     add f52ddfd  Fix MXNDArrayGetData (#16289)
     add 7656a11  Removes git status update stop gap solution (#16285)
     add 33c7b5c  add google-analytics config (#16271)
     add 8004a02  Fixing links for website + Fixing search (#16284)
     add dc5470c  Factorize CUDA_KERNEL_LOOP used in CUDA kernels (#16197)
     add 01ca278  [Gluon] Support None argument in HybridBlock (#16280)
     add 943bed5  add mkl installation temp fix (#16304)
     add 3950a47  [MXNET-978] n-th order gradient test support. (#15611)
     add 512d25a  Minor fix in ToTensor documentation. (#16299)
     new 4fba4c3  Merge remote-tracking branch 'origin/master' into mkldnn-v1.0

The 1 revisions listed above as "new" are entirely new to this
repository and will be described in separate emails.  The revisions
listed as "add" were already present in the repository and have only
been added to this reference.


Summary of changes:
 .github/PULL_REQUEST_TEMPLATE.md                   |    2 +-
 3rdparty/mshadow/mshadow/base.h                    |   43 +-
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 benchmark/opperf/utils/benchmark_utils.py          |    1 +
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[incubator-mxnet] 01/01: Merge remote-tracking branch 'origin/master' into mkldnn-v1.0

Posted by ta...@apache.org.
This is an automated email from the ASF dual-hosted git repository.

taolv pushed a commit to branch mkldnn-v1.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git

commit 4fba4c3ce4333ce4e801a117d9eee615ca2dc412
Merge: ce5ec06 512d25a
Author: Tao Lv <ta...@intel.com>
AuthorDate: Sun Sep 29 19:17:31 2019 +0800

    Merge remote-tracking branch 'origin/master' into mkldnn-v1.0
    
    Conflicts:
    	3rdparty/mkldnn
    	ci/docker/install/ubuntu_mkl.sh
    	ci/docker/install/ubuntu_mklml.sh
    	cmake/DownloadMKLML.cmake
    	src/operator/nn/mkldnn/mkldnn_act-inl.h
    	src/operator/nn/mkldnn/mkldnn_act.cc

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 tests/python/unittest/test_numpy_ndarray.py        |   45 +
 tests/python/unittest/test_numpy_op.py             |  847 ++++++-
 tests/python/unittest/test_operator.py             |   17 +
 tests/python/unittest/test_profiler.py             |    1 -
 tests/tutorials/test_tutorials.py                  |    1 +
 tools/caffe_translator/README.md                   |    4 +-
 tools/caffe_translator/faq.md                      |    4 +-
 tools/coreml/pip_package/README.rst                |    2 +-
 tools/dependencies/README.md                       |    2 +-
 tools/pip/doc/CPU_ADDITIONAL.md                    |    2 +-
 tools/pip/doc/CU100MKL_ADDITIONAL.md               |    2 +-
 tools/pip/doc/CU100_ADDITIONAL.md                  |    2 +-
 tools/pip/doc/CU75MKL_ADDITIONAL.md                |    2 +-
 tools/pip/doc/CU75_ADDITIONAL.md                   |    2 +-
 tools/pip/doc/CU80MKL_ADDITIONAL.md                |    2 +-
 tools/pip/doc/CU80_ADDITIONAL.md                   |    2 +-
 tools/pip/doc/CU90MKL_ADDITIONAL.md                |    2 +-
 tools/pip/doc/CU90_ADDITIONAL.md                   |    2 +-
 tools/pip/doc/CU91MKL_ADDITIONAL.md                |    2 +-
 tools/pip/doc/CU91_ADDITIONAL.md                   |    2 +-
 tools/pip/doc/CU92MKL_ADDITIONAL.md                |    2 +-
 tools/pip/doc/CU92_ADDITIONAL.md                   |    2 +-
 tools/pip/doc/MKL_ADDITIONAL.md                    |    2 +-
 720 files changed, 15108 insertions(+), 53714 deletions(-)

diff --cc src/operator/nn/mkldnn/mkldnn_act-inl.h
index 57507a5,9c21b7f..524c74e
--- a/src/operator/nn/mkldnn/mkldnn_act-inl.h
+++ b/src/operator/nn/mkldnn/mkldnn_act-inl.h
@@@ -32,59 -32,70 +32,88 @@@
  #include <vector>
  #include <utility>
  #include "../activation-inl.h"
+ #include "../../leaky_relu-inl.h"
 -#include "./mkldnn_ops-inl.h"
 -#include "./mkldnn_base-inl.h"
  
  namespace mxnet {
  namespace op {
  
+ struct MKLDNNActParam {
+   mkldnn::algorithm alg;
+   float slope = 0.f;
+ 
+   bool operator==(const MKLDNNActParam& other) const {
+     return this->alg == other.alg &&
+            this->slope == other.slope;
+   }
+ };
+ 
  mkldnn::algorithm GetMKLDNNActAlgo(const ActivationParam& param);
+ mkldnn::algorithm GetMKLDNNActAlgo(const LeakyReLUParam& param);
++
  mkldnn::eltwise_forward::primitive_desc GetActFwdDescImpl(
-     const ActivationParam& param, bool is_train, const mkldnn::memory &input_mem);
+     const MKLDNNActParam& param, bool is_train,
 -    const mkldnn::memory &input_mem, int dtype);
++    const mkldnn::memory &input_mem);
  
  class MKLDNNActForward {
   public:
    const mkldnn::eltwise_forward::primitive_desc fwd_pd;
  
-   MKLDNNActForward(const ActivationParam& param, bool is_train,
+   MKLDNNActForward(const MKLDNNActParam& param, bool is_train,
                     const NDArray &data, const mkldnn::memory &mem): fwd_pd(
 -                       GetActFwdDescImpl(param, is_train, mem, data.dtype())) {}
 -  void SetNewMem(const mkldnn::memory &data, const mkldnn::memory &output);
 -  const mkldnn::eltwise_forward &GetFwd() const;
 +                       GetActFwdDescImpl(param, is_train, mem)) {
 +    fwd_ = std::make_shared<mkldnn::eltwise_forward>(fwd_pd);
 +  }
 +  const inline mkldnn::eltwise_forward &GetFwd() const;
  
   private:
    std::shared_ptr<mkldnn::eltwise_forward> fwd_;
 -  std::shared_ptr<mkldnn::memory> data_;
 -  std::shared_ptr<mkldnn::memory> out_;
  };
  
- typedef ParamOpSign<ActivationParam> MKLDNNActSignature;
- MKLDNNActForward &GetActForward(const ActivationParam& param,
+ typedef ParamOpSign<MKLDNNActParam> MKLDNNActSignature;
+ MKLDNNActForward &GetActForward(const MKLDNNActParam& param,
                                  const OpContext &ctx, const NDArray &in_data,
                                  const mkldnn::memory &in_mem);
  
  void MKLDNNActivationForward(const nnvm::NodeAttrs& attrs, const OpContext &ctx,
                               const NDArray &in_data, const OpReqType &req,
                               const NDArray &out_data);
+ void MKLDNNLeakyReluForward(const nnvm::NodeAttrs& attrs, const OpContext &ctx,
 -                             const NDArray &in_data, const OpReqType &req,
 -                             const NDArray &out_data);
++                            const NDArray &in_data, const OpReqType &req,
++                            const NDArray &out_data);
 +
 +mkldnn::eltwise_backward::primitive_desc GetActBwdDescImpl(
-     const ActivationParam &param, const mkldnn::memory &input_mem,
++    const MKLDNNActParam &param, const mkldnn::memory &input_mem,
 +    const mkldnn::memory &diff_dst_memory);
 +
 +class MKLDNNActBackward {
 + public:
 +  const mkldnn::eltwise_backward::primitive_desc pd;
 +
-   explicit MKLDNNActBackward(const ActivationParam &param, const NDArray &data,
++  explicit MKLDNNActBackward(const MKLDNNActParam &param, const NDArray &data,
 +                             const mkldnn::memory &mem,
 +                             const mkldnn::memory &diff_dst_memory): pd(
 +                                 GetActBwdDescImpl(param, mem, diff_dst_memory)) {
 +    bwd = std::make_shared<mkldnn::eltwise_backward>(pd);
 +  }
 +  const inline mkldnn::eltwise_backward &GetBwd() const;
 +
 + private:
 +  std::shared_ptr<mkldnn::eltwise_backward> bwd;
 +};
  }  // namespace op
  }  // namespace mxnet
  
+ namespace std {
+ template<>
+ struct hash<mxnet::op::MKLDNNActParam> {
+   size_t operator()(const mxnet::op::MKLDNNActParam& val) {
+     size_t ret = 0;
+     ret = dmlc::HashCombine(ret, static_cast<size_t>(val.alg));
+     ret = dmlc::HashCombine(ret, val.slope);
+     return ret;
+   }
+ };
+ }  // namespace std
+ 
 -#endif  // MXNET_USE_MKLDNN == 1
 +#endif  // MXNET_USE_MKLDNN == 100
  #endif  // MXNET_OPERATOR_NN_MKLDNN_MKLDNN_ACT_INL_H_
diff --cc src/operator/nn/mkldnn/mkldnn_act.cc
index e2ffd0b,f221ddf..86a7fdd
--- a/src/operator/nn/mkldnn/mkldnn_act.cc
+++ b/src/operator/nn/mkldnn/mkldnn_act.cc
@@@ -78,12 -93,26 +92,24 @@@ mkldnn::algorithm GetMKLDNNActAlgo(cons
    }
  }
  
+ mkldnn::algorithm GetMKLDNNActAlgo(const LeakyReLUParam& param) {
+   switch (param.act_type) {
+     case leakyrelu::kLeakyReLU:
+       return mkldnn::algorithm::eltwise_relu;
+     case leakyrelu::kELU:
+       return mkldnn::algorithm::eltwise_elu;
+     default:
+       LOG(FATAL) << "unknown activation type for LeakyReLU: " << param.act_type;
+       return mkldnn::algorithm::eltwise_relu;
+   }
+ }
+ 
  mkldnn::eltwise_forward::primitive_desc GetActFwdDescImpl(
-     const ActivationParam& param, bool is_train,
+     const MKLDNNActParam& param, bool is_train,
 -    const mkldnn::memory &input_mem, int dtype) {
 -  mkldnn::memory::primitive_desc data_mpd = input_mem.get_primitive_desc();
 -  mkldnn::memory::desc data_md = data_mpd.desc();
 -  auto cpu_engine = data_mpd.get_engine();
 -
 +    const mkldnn::memory &input_mem) {
 +  mkldnn::memory::desc data_md = input_mem.get_desc();
 +  auto cpu_engine = CpuEngine::Get()->get_engine();
-   auto alg = GetMKLDNNActAlgo(param);
+   auto alg = param.alg;
  
    auto prop = is_train ? mkldnn::prop_kind::forward_training :
                           mkldnn::prop_kind::forward_scoring;
@@@ -106,8 -155,10 +131,9 @@@ MKLDNNActForward &GetActForward(const M
  #endif
    MKLDNNActSignature key(param);
    key.AddSign(ctx.is_train);
-   key.AddSign(param.act_type);
 -  key.AddSign(param.alg);
++  key.AddSign(static_cast<int>(param.alg));
+   key.AddSign(param.slope);
    key.AddSign(in_data);
 -
    auto it = fwds.find(key);
    if (it == fwds.end()) {
      MKLDNNActForward fwd(param, ctx.is_train, in_data, in_mem);
@@@ -120,6 -171,31 +146,31 @@@ void MKLDNNActivationForward(const nnvm
                               const NDArray &in_data, const OpReqType &req,
                               const NDArray &out_data) {
    const ActivationParam& param = nnvm::get<ActivationParam>(attrs.parsed);
+   MKLDNNActParam param_;
+   param_.alg = GetMKLDNNActAlgo(param);
+ 
+   NDArray in_buffer = in_data;
+   MKLDNNStream *stream = MKLDNNStream::Get();
+ 
+   if (in_data.IsView() && in_data.IsMKLDNNData())
+     in_buffer = in_data.Reorder2Default();
+ 
+   auto input_mem = in_buffer.GetMKLDNNData();
+   MKLDNNActForward &fwd = GetActForward(param_, ctx, in_buffer, *input_mem);
 -  auto out_mem_t = CreateMKLDNNMem(out_data, fwd.fwd_pd.dst_primitive_desc(), req, &in_buffer);
 -  fwd.SetNewMem(*input_mem, *out_mem_t.second);
 -  stream->RegisterPrim(fwd.GetFwd());
++  auto out_mem_t = CreateMKLDNNMem(out_data, fwd.fwd_pd.dst_desc(), req, &in_buffer);
++  stream->RegisterPrimArgs(fwd.GetFwd(),
++                           {{ MKLDNN_ARG_SRC, *input_mem}, { MKLDNN_ARG_DST, *out_mem_t.second}});
+   CommitOutput(out_data, out_mem_t);
+   stream->Submit();
+ }
+ 
+ void MKLDNNLeakyReluForward(const nnvm::NodeAttrs& attrs, const OpContext &ctx,
+                              const NDArray &in_data, const OpReqType &req,
+                              const NDArray &out_data) {
+   const LeakyReLUParam& param = nnvm::get<LeakyReLUParam>(attrs.parsed);
+   MKLDNNActParam param_;
+   param_.alg = GetMKLDNNActAlgo(param);
+   param_.slope = param.slope;
  
    NDArray in_buffer = in_data;
    MKLDNNStream *stream = MKLDNNStream::Get();
@@@ -128,37 -204,83 +179,36 @@@
      in_buffer = in_data.Reorder2Default();
  
    auto input_mem = in_buffer.GetMKLDNNData();
-   MKLDNNActForward &fwd = GetActForward(param, ctx, in_buffer, *input_mem);
+   MKLDNNActForward &fwd = GetActForward(param_, ctx, in_buffer, *input_mem);
 -  auto out_mem_t = CreateMKLDNNMem(out_data, fwd.fwd_pd.dst_primitive_desc(), req, &in_buffer);
 -  fwd.SetNewMem(*input_mem, *out_mem_t.second);
 -  stream->RegisterPrim(fwd.GetFwd());
 +  auto out_mem_t = CreateMKLDNNMem(out_data, fwd.fwd_pd.dst_desc(), req, &in_buffer);
 +  stream->RegisterPrimArgs(fwd.GetFwd(),
 +                           {{ MKLDNN_ARG_SRC, *input_mem}, { MKLDNN_ARG_DST, *out_mem_t.second}});
    CommitOutput(out_data, out_mem_t);
    stream->Submit();
  }
  
 -static mkldnn::eltwise_backward::primitive_desc GetActBwdDescImpl(
 +mkldnn::eltwise_backward::primitive_desc GetActBwdDescImpl(
-     const ActivationParam &param, const mkldnn::memory &input_mem,
+     const MKLDNNActParam &param, const mkldnn::memory &input_mem,
 -    const mkldnn::memory &diff_dst_memory, int dtype) {
 -  mkldnn::memory::primitive_desc data_mpd = input_mem.get_primitive_desc();
 -  mkldnn::memory::desc data_md = data_mpd.desc();
 -  mkldnn::memory::desc diff_md = diff_dst_memory.get_primitive_desc().desc();
 -  auto cpu_engine = data_mpd.get_engine();
 +    const mkldnn::memory &diff_dst_memory) {
 +  mkldnn::memory::desc data_md = input_mem.get_desc();
 +  mkldnn::memory::desc diff_md = diff_dst_memory.get_desc();
 +  auto cpu_engine = CpuEngine::Get()->get_engine();
-   auto alg = GetMKLDNNActAlgo(param);
+   auto alg = param.alg;
  
-   float alpha = 0;
 -  MSHADOW_REAL_TYPE_SWITCH(dtype, DType, {
 -    mkldnn::eltwise_forward::desc fw_desc(mkldnn::prop_kind::forward_training,
 -                                          alg, data_md, param.slope);
 -    mkldnn::eltwise_forward::primitive_desc fw_pdesc(fw_desc, cpu_engine);
 -    mkldnn::eltwise_backward::desc bw_desc(alg, diff_md, data_md, param.slope);
 -    mkldnn::eltwise_backward::primitive_desc bw_pdesc(bw_desc, cpu_engine,
 -                                                      fw_pdesc);
 -    return bw_pdesc;
 -  });
 -  LOG(FATAL) << "Unsupported data type for MKLDNN activation";
    mkldnn::eltwise_forward::desc fw_desc(mkldnn::prop_kind::forward_training,
-                                         alg, data_md, alpha);
+                                         alg, data_md, param.slope);
    mkldnn::eltwise_forward::primitive_desc fw_pdesc(fw_desc, cpu_engine);
-   mkldnn::eltwise_backward::desc bw_desc(alg, diff_md, data_md, alpha);
+   mkldnn::eltwise_backward::desc bw_desc(alg, diff_md, data_md, param.slope);
    mkldnn::eltwise_backward::primitive_desc bw_pdesc(bw_desc, cpu_engine,
                                                      fw_pdesc);
    return bw_pdesc;
  }
  
 -class MKLDNNActBackward {
 -  std::shared_ptr<mkldnn::eltwise_backward> bwd;
 -  std::shared_ptr<mkldnn::memory> data;
 -  std::shared_ptr<mkldnn::memory> diff_dst_memory;
 -  std::shared_ptr<mkldnn::memory> diff_src_memory;
 -
 - public:
 -  const mkldnn::eltwise_backward::primitive_desc pd;
 -
 -  explicit MKLDNNActBackward(const MKLDNNActParam &param, const NDArray &data,
 -                             const mkldnn::memory &mem,
 -                             const mkldnn::memory &diff_dst_memory)
 -      : pd(GetActBwdDescImpl(param, mem, diff_dst_memory, data.dtype())) {}
 -
 -  void SetNewMem(const mkldnn::memory &data,
 -                 const mkldnn::memory &diff_dst_memory,
 -                 const mkldnn::memory &diff_src_memory) {
 -    if (this->bwd != nullptr) {
 -      this->data->set_data_handle(data.get_data_handle());
 -      this->diff_dst_memory->set_data_handle(diff_dst_memory.get_data_handle());
 -      this->diff_src_memory->set_data_handle(diff_src_memory.get_data_handle());
 -    } else {
 -      this->data = std::shared_ptr<mkldnn::memory>(new mkldnn::memory(
 -          data.get_primitive_desc(), data.get_data_handle()));
 -      this->diff_dst_memory = std::shared_ptr<mkldnn::memory>(
 -          new mkldnn::memory(diff_dst_memory.get_primitive_desc(),
 -                             diff_dst_memory.get_data_handle()));
 -      this->diff_src_memory = std::shared_ptr<mkldnn::memory>(
 -          new mkldnn::memory(diff_src_memory.get_primitive_desc(),
 -                             diff_src_memory.get_data_handle()));
 -      this->bwd = std::shared_ptr<mkldnn::eltwise_backward>(
 -          new mkldnn::eltwise_backward(
 -              this->pd, mkldnn::primitive::at(*this->data),
 -              *this->diff_dst_memory, *this->diff_src_memory));
 -    }
 -  }
 -
 -  const inline mkldnn::eltwise_backward &GetBwd() const { return *bwd; }
 -};
 +const inline mkldnn::eltwise_backward &MKLDNNActBackward::GetBwd() const {
 +  return *bwd;
 +}
  
- static inline MKLDNNActBackward &GetActBackward(const ActivationParam &param,
+ static inline MKLDNNActBackward &GetActBackward(const MKLDNNActParam &param,
                                                  const OpContext &ctx,
                                                  const NDArray &in_data,
                                                  const NDArray &out_grad,
@@@ -203,23 -327,60 +255,67 @@@ void MKLDNNActivationBackward(const nnv
    auto input_mem = in_buffer.GetMKLDNNData();
    // We need to make sure the two inputs to eltwise_backward has the same memory
    // descriptor. Otherwise, the perf will suffer.
 -  if (input_mem->get_primitive_desc() != diff_dst_memory->get_primitive_desc())
 -    input_mem = in_buffer.GetMKLDNNDataReorder(diff_dst_memory->get_primitive_desc());
 +  if (input_mem->get_desc() != diff_dst_memory->get_desc())
 +    input_mem = in_buffer.GetMKLDNNDataReorder(diff_dst_memory->get_desc());
    MKLDNNActBackward &bwd =
-       GetActBackward(param, ctx, in_buffer, out_buffer, *input_mem);
+       GetActBackward(param_, ctx, in_buffer, out_buffer, *input_mem);
    MKLDNNStream *stream = MKLDNNStream::Get();
    mkldnn_output_t diff_src_memory =
 -      CreateMKLDNNMem(in_grad, bwd.pd.diff_src_primitive_desc(), req);
 -  bwd.SetNewMem(*input_mem, *diff_dst_memory, *diff_src_memory.second);
 -  stream->RegisterPrim(bwd.GetBwd());
 +      CreateMKLDNNMem(in_grad, bwd.pd.diff_src_desc(), req);
 +  mkldnn_args_map_t args = {
 +    { MKLDNN_ARG_SRC, *input_mem },
 +    { MKLDNN_ARG_DIFF_DST, *diff_dst_memory },
 +    { MKLDNN_ARG_DIFF_SRC, *diff_src_memory.second },
 +  };
 +  stream->RegisterPrimArgs(bwd.GetBwd(), args);
    CommitOutput(in_grad, diff_src_memory);
    stream->Submit();
  }
  
+ void MKLDNNLeakyReluBackward(const nnvm::NodeAttrs& attrs,
+                              const OpContext &ctx,
+                              const std::vector<NDArray>& inputs,
+                              const OpReqType &req,
+                              const NDArray &output) {
+   if (req == kNullOp) {
+     return;
+   }
+   CHECK_GE(inputs.size(), 2U);
+   NDArray out_buffer = inputs[0];
+   if (inputs[0].IsView() && inputs[0].IsMKLDNNData())
+     out_buffer = inputs[0].Reorder2Default();
+ 
+   NDArray in_buffer = inputs[1];
+   if (inputs[1].IsView() && inputs[1].IsMKLDNNData())
+     in_buffer = inputs[1].Reorder2Default();
+ 
+   const LeakyReLUParam& param = nnvm::get<LeakyReLUParam>(attrs.parsed);
+   MKLDNNActParam param_;
+   param_.alg = GetMKLDNNActAlgo(param);
+   param_.slope = param.slope;
+ 
+   TmpMemMgr::Get()->Init(ctx.requested[leakyrelu::kRandom]);
+   auto diff_dst_memory = out_buffer.GetMKLDNNData();
+   auto input_mem = in_buffer.GetMKLDNNData();
+   // We need to make sure the two inputs to eltwise_backward has the same memory
+   // descriptor. Otherwise, the perf will suffer.
 -  if (input_mem->get_primitive_desc() != diff_dst_memory->get_primitive_desc())
 -    input_mem = in_buffer.GetMKLDNNDataReorder(diff_dst_memory->get_primitive_desc());
++  if (input_mem->get_desc() != diff_dst_memory->get_desc())
++    input_mem = in_buffer.GetMKLDNNDataReorder(diff_dst_memory->get_desc());
+   MKLDNNActBackward &bwd =
+       GetActBackward(param_, ctx, in_buffer, out_buffer, *input_mem);
+   MKLDNNStream *stream = MKLDNNStream::Get();
+   mkldnn_output_t diff_src_memory =
 -      CreateMKLDNNMem(output, bwd.pd.diff_src_primitive_desc(), req);
 -  bwd.SetNewMem(*input_mem, *diff_dst_memory, *diff_src_memory.second);
 -  stream->RegisterPrim(bwd.GetBwd());
++      CreateMKLDNNMem(output, bwd.pd.diff_src_desc(), req);
++  mkldnn_args_map_t args = {
++    { MKLDNN_ARG_SRC, *input_mem },
++    { MKLDNN_ARG_DIFF_DST, *diff_dst_memory },
++    { MKLDNN_ARG_DIFF_SRC, *diff_src_memory.second },
++  };
++  stream->RegisterPrimArgs(bwd.GetBwd(), args);
+   CommitOutput(output, diff_src_memory);
+   stream->Submit();
+ }
+ 
  }  // namespace op
  }  // namespace mxnet
 -
  #endif