Replace mkldnn_white_list to onednn_white_list [fluid_ops] (#67687)

co63oc · web-flow · commit 8c48de6200e9 · 2024-09-09T14:56:05.000+08:00
diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc
@@ -1579,7 +1579,7 @@ bool OperatorWithKernel::SupportsKernelType(
 // 2. Whether this op has specific implementation;
 // 3. Whether onednn kernel can be used.
 #ifdef PADDLE_WITH_DNNL
-  if (!this->DnnFallback() && !paddle::platform::in_mkldnn_white_list(type_) &&
+  if (!this->DnnFallback() && !paddle::platform::in_onednn_white_list(type_) &&
       this->CanMKLDNNBeUsed(exe_ctx, kernel_type.data_type_)) {
     auto tmp_kernel_type = kernel_type;
     tmp_kernel_type.library_type_ = framework::LibraryType::kMKLDNN;
@@ -1855,7 +1855,7 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
 // 3. Whether onednn kernel can be used.
 #ifdef PADDLE_WITH_DNNL
       if (!this->DnnFallback() &&
-          !paddle::platform::in_mkldnn_white_list(type_) &&
+          !paddle::platform::in_onednn_white_list(type_) &&
           this->CanMKLDNNBeUsed(exe_ctx, kernel_type_->data_type_)) {
         kernel_type_->library_type_ = framework::LibraryType::kMKLDNN;
         kernel_type_->data_layout_ = framework::DataLayout::ONEDNN;
@@ -2187,7 +2187,7 @@ OpKernelType OperatorWithKernel::InnerGetExpectedKernelType(
 // 2. Whether this op has specific implementation;
 // 3. Whether onednn kernel can be used.
 #ifdef PADDLE_WITH_DNNL
-  if (!this->DnnFallback() && !paddle::platform::in_mkldnn_white_list(type_) &&
+  if (!this->DnnFallback() && !paddle::platform::in_onednn_white_list(type_) &&
       this->CanMKLDNNBeUsed(ctx, expected_kernel_key.data_type_)) {
     expected_kernel_key.library_type_ = framework::LibraryType::kMKLDNN;
     expected_kernel_key.data_layout_ = framework::DataLayout::ONEDNN;
diff --git a/paddle/fluid/imperative/prepared_operator.cc b/paddle/fluid/imperative/prepared_operator.cc
@@ -197,7 +197,7 @@ PreparedOp PrepareImpl(
 // 2. Whether this op has specific implementation;
 // 3. Whether onednn kernel can be used.
 #ifdef PADDLE_WITH_DNNL
-  if (!op.DnnFallback() && !paddle::platform::in_mkldnn_white_list(op.Type()) &&
+  if (!op.DnnFallback() && !paddle::platform::in_onednn_white_list(op.Type()) &&
       op.CanMKLDNNBeUsed(dygraph_exe_ctx, expected_kernel_key.dtype())) {
     expected_kernel_key.set_backend(phi::Backend::ONEDNN);
     expected_kernel_key.set_layout(phi::DataLayout::ONEDNN);
diff --git a/paddle/fluid/platform/onednn_op_list.h b/paddle/fluid/platform/onednn_op_list.h
@@ -23,10 +23,10 @@ namespace platform {
 
 // NOTE(jiahongyu): Below ops have specific PADDLE_WITH_DNNL hard codes within
 // the function GetExpectedKernelType, so we need to handle them through
-// mkldnn_white_list and solve them one-by-one in the future.
-// TODO(jiahongyu): Delete mkldnn_white_list and fully support
+// onednn_white_list and solve them one-by-one in the future.
+// TODO(jiahongyu): Delete onednn_white_list and fully support
 // PADDLE_WITH_DNNL of GetExpectedKernelType.
-static const std::unordered_set<std::string> mkldnn_white_list = {
+static const std::unordered_set<std::string> onednn_white_list = {
     // NOTE(jiahongyu): Below ops use mem_desc function, which is encoded by
     // PADDLE_WITH_DNNL in DenseTensor. The hardcodes within
     // GetExpectedKernelType of these ops cannot be deleted now.
@@ -36,8 +36,8 @@ static const std::unordered_set<std::string> mkldnn_white_list = {
     "slice_grad",
     "split"};
 
-inline bool in_mkldnn_white_list(const std::string& op_name) {
-  return mkldnn_white_list.find(op_name) != mkldnn_white_list.end();
+inline bool in_onednn_white_list(const std::string& op_name) {
+  return onednn_white_list.find(op_name) != onednn_white_list.end();
 }
 
 }  // namespace platform
