PawelGlomski-Intel commented on a change in pull request #20981:
URL: https://github.com/apache/incubator-mxnet/pull/20981#discussion_r837385725
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File path: src/operator/tensor/elemwise_unary_op.h
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@@ -457,30 +457,67 @@ class UnaryOp : public OpBase {
};
#if MXNET_USE_ONEDNN == 1
-inline bool TanhStorageType(const nnvm::NodeAttrs& attrs,
- const int dev_mask,
- DispatchMode* dispatch_mode,
- std::vector<int>* in_attrs,
- std::vector<int>* out_attrs) {
+inline bool EltwiseStorageType(const nnvm::NodeAttrs& attrs,
+ const int dev_mask,
+ DispatchMode* dispatch_mode,
+ std::vector<int>* in_attrs,
+ std::vector<int>* out_attrs) {
CHECK_EQ(in_attrs->size(), 1);
CHECK_EQ(out_attrs->size(), 1);
return DNNLStorageType(attrs, dev_mask, true, dispatch_mode, in_attrs,
out_attrs);
}
-inline void TanhComputeExCPU(const nnvm::NodeAttrs& attrs,
- const OpContext& ctx,
- const std::vector<mxnet::NDArray>& inputs,
- const std::vector<OpReqType>& req,
- const std::vector<mxnet::NDArray>& outputs) {
- if (SupportDNNLTanh(inputs[0], outputs[0])) {
+template <typename OP>
+struct DNNLAlgorithm {};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::plus> {
+ static const dnnl::algorithm value = dnnl::algorithm::binary_add;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::minus> {
+ static const dnnl::algorithm value = dnnl::algorithm::binary_sub;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::mul> {
+ static const dnnl::algorithm value = dnnl::algorithm::binary_mul;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::div> {
+ static const dnnl::algorithm value = dnnl::algorithm::binary_div;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::tanh> {
+ static const dnnl::algorithm value = dnnl::algorithm::eltwise_tanh;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::exp> {
+ static const dnnl::algorithm value = dnnl::algorithm::eltwise_exp;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::square> {
+ static const dnnl::algorithm value = dnnl::algorithm::eltwise_square;
+};
+template <>
+struct DNNLAlgorithm<op::mshadow_op::square_root> {
+ static const dnnl::algorithm value = dnnl::algorithm::eltwise_sqrt;
+};
Review comment:
Here is the function if you are intrerested:
```c++
template <class>
inline constexpr bool dependent_false_v = false;
template <typename MXNetOP>
constexpr dnnl::algorithm DNNLAlgorithm() {
if constexpr (std::is_same_v<MXNetOP, op::mshadow_op::plus>) {
return dnnl::algorithm::binary_add;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::minus>) {
return dnnl::algorithm::binary_sub;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::mul>) {
return dnnl::algorithm::binary_mul;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::div>) {
return dnnl::algorithm::binary_div;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::tanh>) {
return dnnl::algorithm::eltwise_tanh;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::exp>) {
return dnnl::algorithm::eltwise_exp;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::square>) {
return dnnl::algorithm::eltwise_square;
} else if (std::is_same_v<MXNetOP, op::mshadow_op::square_root>) {
return dnnl::algorithm::eltwise_sqrt;
} else {
static_assert(dependent_false_v<MXNetOP>, "Error");
return dnnl::algorithm();
}
}
```
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