TaoLv commented on a change in pull request #14893: Integrating the MKL VML
functions to MXNET to speed-up the (element-wised) mathematic computation
URL: https://github.com/apache/incubator-mxnet/pull/14893#discussion_r285129930
##########
File path: src/operator/tensor/elemwise_unary_op.h
##########
@@ -554,14 +560,48 @@ struct ReshapeLikeParam : public
dmlc::Parameter<ReshapeLikeParam> {
NNVM_REGISTER_OP(__name$) \
.set_num_inputs(1) \
.set_num_outputs(1) \
- .set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>) \
+ .set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<1, 1>) \
.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>) \
.set_attr<nnvm::FInplaceOption>("FInplaceOption", \
[](const NodeAttrs& attrs){ \
return std::vector<std::pair<int, int> >{{0, 0}}; \
}) \
.add_argument("data", "NDArray-or-Symbol", "The input array.")
+#if MSHADOW_USE_MKL == 1
+ /*! \bried MKL Unary compute.
+ * * With this macro means mxnet compile with MKL to accelerate math
function with mkl.
+ * * Will Register FCompute with UnaryOp::MKL_Compute() to compelet the
math function.
+ */
+ #define MXNET_MKL_OPERATOR_REGISTER_UNARY_WITH_RSP_CSR(__name$, __xpu$,
\
+ __kernel$,
__mkl_kernel$) \
+ MXNET_OPERATOR_REGISTER_UNARY(__name$)
\
+ MXNET_ADD_SPARSE_OP_ALIAS(__name$)
\
+ .set_attr<FInferStorageType>("FInferStorageType", ElemwiseStorageType<1,
1, \
+ false, true, true>)
\
+ .set_attr<FCompute>("FCompute<" #__xpu$ ">",
UnaryOp::MKL_Compute<__kernel$, __mkl_kernel$>) \
+ .set_attr<FComputeEx>("FComputeEx<" #__xpu$ ">",
UnaryOp::MKL_ComputeEx<__kernel$, \
Review comment:
I just reverted the change for FComputeEx as we don't have much data for
that yet. Will revisit this part once we meet any performance issue for sparse.
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