Use MKLDNN sum in more cases.

apache · Dec 15, 2017 · 7a21ebc · 7a21ebc
1 parent d6d74f4
commit 7a21ebc
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Showing 3 changed files with 31 additions and 7 deletions.
diff --git a/src/operator/nn/mkldnn/mkldnn_base-inl.h b/src/operator/nn/mkldnn/mkldnn_base-inl.h
@@ -122,13 +122,18 @@ static inline bool SupportMKLDNNArray(int dtype, const TShape &shape) {
   return support;
 }
 
+static inline bool SupportStorageMKLDNN(int stype) {
+  return stype == kMKLDNNStorage || stype == kDefaultStorage;
+}
+
 static inline bool SupportMKLDNN(int dtype, const TShape &shape) {
   int ndim = shape.ndim();
   return dtype == mshadow::kFloat32 && (ndim == 1 || ndim == 2 || ndim == 4);
 }
 
 static inline bool SupportMKLDNN(const NDArray &input) {
-  return SupportMKLDNN(input.dtype(), input.shape());
+  return SupportMKLDNN(input.dtype(), input.shape())
+          && SupportStorageMKLDNN(input.storage_type());
 }
 
 static inline bool SupportMKLDNNConv(const NDArray &input) {

diff --git a/src/operator/tensor/elemwise_binary_op_basic.cc b/src/operator/tensor/elemwise_binary_op_basic.cc
@@ -25,6 +25,7 @@
 #include "./elemwise_unary_op.h"
 #include "./elemwise_binary_op-inl.h"
 #include "../nn/mkldnn/mkldnn_ops-inl.h"
+#include "../nn/mkldnn/mkldnn_base-inl.h"
 
 namespace mxnet {
 namespace op {
@@ -37,8 +38,7 @@ static void ElemwiseAddEx(const nnvm::NodeAttrs& attrs,
   CHECK_EQ(inputs.size(), 2U);
   CHECK_EQ(outputs.size(), 1U);
 #if MXNET_USE_MKLDNN == 1
-  if (inputs[0].storage_type() == kMKLDNNStorage
-      || inputs[1].storage_type() == kMKLDNNStorage) {
+  if (SupportMKLDNN(inputs[0]) && SupportMKLDNN(inputs[1])) {
     MKLDNNSum_Forward(attrs, ctx, inputs, req[0], outputs[0]);
     return;
   } else if (inputs[0].storage_type() == kDefaultStorage
@@ -68,7 +68,7 @@ static inline bool ElemwiseAddStorageType(const nnvm::NodeAttrs& attrs,
   CHECK_EQ(in_attrs->size(), 2);
   CHECK_EQ(out_attrs->size(), 1);
 #if MXNET_USE_MKLDNN == 1
-  if ((in_attrs->at(0) == kMKLDNNStorage || in_attrs->at(1) == kMKLDNNStorage)
+  if ((SupportStorageMKLDNN(in_attrs->at(0)) || SupportStorageMKLDNN(in_attrs->at(1)))
       && dev_mask == mshadow::cpu::kDevMask) {
     out_attrs->at(0) = kMKLDNNStorage;
     *dispatch_mode = DispatchMode::kFComputeEx;

diff --git a/src/operator/tensor/elemwise_sum.cc b/src/operator/tensor/elemwise_sum.cc
@@ -25,6 +25,7 @@
 #include "./elemwise_sum.h"
 #include "../../ndarray/ndarray_function.h"
 #include "../nn/mkldnn/mkldnn_ops-inl.h"
+#include "../nn/mkldnn/mkldnn_base-inl.h"
 #include "../../common/utils.h"
 
 namespace mxnet {
@@ -74,6 +75,25 @@ bool ElementWiseSumType(const nnvm::NodeAttrs& attrs,
     attrs, in_attrs, out_attrs, -1);
 }
 
+#if MXNET_USE_MKLDNN == 1
+static inline bool SupportMKLDNN(const std::vector<NDArray>& inputs) {
+  for (auto &i : inputs) {
+    if (!SupportMKLDNN(i))
+      return false;
+  }
+  return true;
+}
+
+static inline bool SupportStorageMKLDNN(const std::vector<int> &inputs) {
+  for (int i : inputs) {
+    if (!mxnet::SupportStorageMKLDNN(i))
+      return false;
+  }
+  return true;
+}
+
+#endif
+
 bool ElementWiseSumForwardInferStorageType(const nnvm::NodeAttrs& attrs,
                                            const int dev_mask,
                                            DispatchMode* dispatch_mode,
@@ -82,8 +102,7 @@ bool ElementWiseSumForwardInferStorageType(const nnvm::NodeAttrs& attrs,
   CHECK(!in_attrs->empty());
   CHECK_EQ(out_attrs->size(), 1U);
 #if MXNET_USE_MKLDNN == 1
-  if (dev_mask == mshadow::cpu::kDevMask
-      && common::ContainsStorage(*in_attrs, kMKLDNNStorage)) {
+  if (dev_mask == mshadow::cpu::kDevMask && SupportStorageMKLDNN(*in_attrs)) {
     *dispatch_mode = DispatchMode::kFComputeEx;
     (*out_attrs)[0] = kMKLDNNStorage;
     return true;
@@ -110,7 +129,7 @@ void ElementWiseSumComputeExCPU(const nnvm::NodeAttrs& attrs,
     NDArray out_nd = outputs[0];
     mxnet::ndarray::ElementwiseSum<cpu>(s, rsc, inputs, &out_nd);
 #if MXNET_USE_MKLDNN == 1
-  } else if (common::ContainsStorage(inputs, kMKLDNNStorage)) {
+  } else if (SupportMKLDNN(inputs)) {
     MKLDNNSum_Forward(attrs, op_ctx, inputs, req[0], outputs[0]);
 #endif
   } else if (common::ContainsOnlyStorage(inputs, kDefaultStorage)) {