Replace is_run_mkldnn_kernel is_run_onednn_kernel [fluid_ops] (#74314)

Author: co63oc

paddle/fluid/framework/new_executor/instruction/onednn/onednn_instruction.cc

@@ -375,9 +375,9 @@ OneDNNPhiKernelInstruction::OneDNNPhiKernelInstruction(
   }
   TensorNameMap(op, *value_exec_info_, yaml_info_parser, inputs_, outputs_);
 
-  // Step4: Mark is_run_mkldnn_kernel=true
+  // Step4: Mark is_run_onednn_kernel=true
   phi::MetaConfig new_config = infer_meta_context_.GetMetaConfig();
-  new_config.is_run_mkldnn_kernel = true;
+  new_config.is_run_onednn_kernel = true;
   infer_meta_context_.SetMetaConfig(new_config);
 
   // Step5: Handle skip_transform_inputs

paddle/fluid/framework/new_executor/instruction/onednn/onednn_legacy_instruction.cc

@@ -229,9 +229,9 @@ OneDNNLegacyKernelInstruction::OneDNNLegacyKernelInstruction(
     }
   }
 
-  // Step3: Mark is_run_mkldnn_kernel=true
+  // Step3: Mark is_run_onednn_kernel=true
   phi::MetaConfig new_config = infer_meta_context_.GetMetaConfig();
-  new_config.is_run_mkldnn_kernel = true;
+  new_config.is_run_onednn_kernel = true;
   infer_meta_context_.SetMetaConfig(new_config);
 
   // Step4: Handle skip_transform_inputs

paddle/phi/core/meta_tensor.h

@@ -25,13 +25,13 @@ namespace phi {
 
 struct TEST_API MetaConfig {
   bool is_runtime{true};
-  bool is_run_mkldnn_kernel{false};
+  bool is_run_onednn_kernel{false};
   MetaConfig() = default;
 
   // supporting implicit construction is easier to use
-  MetaConfig(bool is_runtime, bool is_run_mkldnn_kernel)
+  MetaConfig(bool is_runtime, bool is_run_onednn_kernel)
       : is_runtime(is_runtime),
-        is_run_mkldnn_kernel(is_run_mkldnn_kernel) {}  // NOLINT
+        is_run_onednn_kernel(is_run_onednn_kernel) {}  // NOLINT
 };
 
 class TEST_API MetaTensor {

paddle/phi/infermeta/binary.cc

@@ -587,7 +587,7 @@ void ConvInferMeta(const MetaTensor& input,
             "dilation is %d.",
             dilations[i]));
   }
-  const bool channel_last = (config.is_run_mkldnn_kernel == false) &&
+  const bool channel_last = (config.is_run_onednn_kernel == false) &&
                             (data_format == "NHWC" || data_format == "NDHWC");
 
   PADDLE_ENFORCE_EQ(
@@ -773,7 +773,7 @@ void ConvTransposeInferMeta(const MetaTensor& x,
   std::vector<int> paddings_ = paddings;
   std::vector<int> dilations_ = dilations;
 
-  const DataLayout data_layout = config.is_run_mkldnn_kernel
+  const DataLayout data_layout = config.is_run_onednn_kernel
                                      ? DataLayout::kNCHW
                                      : common::StringToDataLayout(data_format);
 
@@ -1700,7 +1700,7 @@ void ElementwiseRawInferMeta(const MetaTensor& x,
 
 #ifdef PADDLE_WITH_DNNL
     bool should_rotate =
-        config.is_run_mkldnn_kernel &&
+        config.is_run_onednn_kernel &&
         (phi::OneDNNContext::tls().get_cur_paddle_data_layout() ==
          phi::DataLayout::kNHWC) &&
         (x_dims.size() >= 3 || y_dims.size() >= 3);
@@ -3374,7 +3374,7 @@ void PReluInferMeta(const MetaTensor& x,
                           "For mode 'channel', data_format must be one of "
                           "NCHW and NHWC. But received data_format: %s",
                           data_format));
-    if (data_format == "NCHW" || config.is_run_mkldnn_kernel) {
+    if (data_format == "NCHW" || config.is_run_onednn_kernel) {
       PADDLE_ENFORCE_EQ(product(alpha.dims()) == x_dim[1],
                         true,
                         common::errors::InvalidArgument(

paddle/phi/infermeta/fusion.cc

@@ -2914,7 +2914,7 @@ void BNActXPUInferMeta(const MetaTensor& x,
           x_dims,
           x_dims.size()));
 
-  const int64_t C = ((config.is_run_mkldnn_kernel == true) ||
+  const int64_t C = ((config.is_run_onednn_kernel == true) ||
                              (data_layout_str == DataLayout::kNCHW)
                          ? x_dims[1]
                          : x_dims[x_dims.size() - 1]);

paddle/phi/infermeta/multiary.cc

@@ -965,7 +965,7 @@ void BatchNormInferMeta(const MetaTensor& x,
           x_dims,
           x_dims.size()));
 
-  const int64_t C = ((config.is_run_mkldnn_kernel == true) ||
+  const int64_t C = ((config.is_run_onednn_kernel == true) ||
                              (data_layout == DataLayout::kNCHW)
                          ? x_dims[1]
                          : x_dims[x_dims.size() - 1]);

paddle/phi/infermeta/unary.cc

@@ -3625,7 +3625,7 @@ void Pool2DInferMeta(const MetaTensor& x,
                      const std::string& padding_algorithm,
                      MetaTensor* out,
                      MetaConfig config) {
-  const bool channel_last = (config.is_run_mkldnn_kernel == false) &&
+  const bool channel_last = (config.is_run_onednn_kernel == false) &&
                             (data_format == "NHWC" || data_format == "NDHWC");
   if (!config.is_runtime && kernel_size.FromTensor()) {
     auto x_dims = x.dims();
@@ -3755,7 +3755,7 @@ void PoolInferMeta(const MetaTensor& x,
 
   // MKL-DNN Kernels are using NCHW order of dims description
   // so we ignore data_format consideration for MKL-DNN kernel
-  const bool channel_last = (config.is_run_mkldnn_kernel == false) &&
+  const bool channel_last = (config.is_run_onednn_kernel == false) &&
                             (data_format == "NHWC" || data_format == "NDHWC");
 
   // update paddings if "SAME" or global_pooling
@@ -4430,7 +4430,7 @@ void Shape64InferMeta(const MetaTensor& input,
                       MetaConfig config) {
   auto in_dim = input.dims();
   out->set_dims(common::make_ddim({in_dim.size()}));
-  if (config.is_run_mkldnn_kernel) {
+  if (config.is_run_onednn_kernel) {
     out->set_dtype(DataType::INT32);
   } else {
     out->set_dtype(DataType::INT64);