test/cpp rename use_mkldnn (#74501)

co63oc · web-flow · commit fe852a93f1ef · 2025-08-11T11:19:33.000+08:00
diff --git a/test/cpp/eager/performance_tests/benchmark_utils.cc b/test/cpp/eager/performance_tests/benchmark_utils.cc
@@ -228,7 +228,7 @@ void benchmark_fluid_scale(const std::shared_ptr<imperative::VarBase>& X,
   imperative::Tracer tracer;
   framework::AttributeMap attrs;
 
-  attrs["use_mkldnn"] = false;
+  attrs["use_onednn"] = false;
   attrs["scale"] = 2;
   attrs["bias"] = 3;
   attrs["bias_after_scale"] = true;
diff --git a/test/cpp/fluid/elementwise/test_elementwise_add_grad_grad.cc b/test/cpp/fluid/elementwise/test_elementwise_add_grad_grad.cc
@@ -59,7 +59,7 @@ class TestElementwiseAddGradGradWithoutDDX
         this->op_type_,
         {{"Y", {"Y"}}, {"DOut", {"DOut"}}, {"DDY", {"DDY"}}},
         {{"DDOut", {"DDOut"}}},
-        {{"use_mkldnn", false}, {"axis", 0}});
+        {{"use_onednn", false}, {"axis", 0}});
     return op;
   }
 };
diff --git a/test/cpp/fluid/elementwise/test_elementwise_div_grad_grad.cc b/test/cpp/fluid/elementwise/test_elementwise_div_grad_grad.cc
@@ -87,7 +87,7 @@ class TestElementwiseDivGradGradWithDout : public TestElementwiseOpGradGrad<T> {
          {"DDY", {"DDY"}},
          {"DX", {"DX"}}},
         {{"Y@GRAD", {"Y@GRAD"}}, {"DDOut", {"DDOut"}}, {"DOut", {"DOut"}}},
-        {{"use_mkldnn", false}, {"axis", 0}});
+        {{"use_onednn", false}, {"axis", 0}});
     return op;
   }
 };
diff --git a/test/cpp/fluid/mkldnn/test_conv_onednn_nhwc.cc b/test/cpp/fluid/mkldnn/test_conv_onednn_nhwc.cc
@@ -66,7 +66,7 @@ TEST(test_conv2d_output, fp32) {
   conv2d_op.SetAttr("paddings", paddings);
   conv2d_op.SetAttr("dilations", dilations);
   conv2d_op.SetAttr("groups", groups);
-  conv2d_op.SetAttr("use_mkldnn", true);
+  conv2d_op.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(conv2d_op);
 
@@ -95,7 +95,7 @@ TEST(test_conv2d_output, int8) {
   conv2d_op.SetAttr("paddings", paddings);
   conv2d_op.SetAttr("dilations", dilations);
   conv2d_op.SetAttr("groups", groups);
-  conv2d_op.SetAttr("use_mkldnn", true);
+  conv2d_op.SetAttr("use_onednn", true);
   conv2d_op.SetAttr("mkldnn_data_type", std::string("int8"));
   conv2d_op.SetAttr("force_fp32_output", false);
 
@@ -126,7 +126,7 @@ TEST(test_conv2d_output, ic1) {
   conv2d_op.SetAttr("paddings", paddings);
   conv2d_op.SetAttr("dilations", dilations);
   conv2d_op.SetAttr("groups", groups);
-  conv2d_op.SetAttr("use_mkldnn", true);
+  conv2d_op.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(conv2d_op);
 
@@ -156,7 +156,7 @@ TEST(test_conv2d_output, ic2) {
   conv2d_op.SetAttr("paddings", paddings);
   conv2d_op.SetAttr("dilations", dilations);
   conv2d_op.SetAttr("groups", groups);
-  conv2d_op.SetAttr("use_mkldnn", true);
+  conv2d_op.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(conv2d_op);
 
@@ -186,7 +186,7 @@ TEST(test_conv2d_output, ic4) {
   conv2d_op.SetAttr("paddings", paddings);
   conv2d_op.SetAttr("dilations", dilations);
   conv2d_op.SetAttr("groups", groups);
-  conv2d_op.SetAttr("use_mkldnn", true);
+  conv2d_op.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(conv2d_op);
 
diff --git a/test/cpp/fluid/mkldnn/test_onednn_caching.cc b/test/cpp/fluid/mkldnn/test_onednn_caching.cc
@@ -115,12 +115,12 @@ void RunOperator(const phi::Place &place,
                       {{first_input_var_name, {first_input}},
                        {second_input_var_name, {"x1"}}},
                       {{output_var_name, {output_name}}},
-                      {{"use_mkldnn", {true}}})
+                      {{"use_onednn", {true}}})
                 : framework::OpRegistry::CreateOp(
                       op_type,
                       {{first_input_var_name, {first_input}}},
                       {{output_var_name, {output_name}}},
-                      {{"use_mkldnn", {true}}});
+                      {{"use_onednn", {true}}});
 
   op->Run(scope, place);
   pool.Get(place)->Wait();
diff --git a/test/cpp/fluid/mkldnn/test_onednn_conv2d_transpose_bias.cc b/test/cpp/fluid/mkldnn/test_onednn_conv2d_transpose_bias.cc
@@ -61,7 +61,7 @@ void test_conv2d_transpose_bias() {
   AddVarToScope<float>("convtranspose-Bias", &scope, {256});
   AddVarToScope<float>("convtranspose-Out", &scope, {1, 256, 27, 23});
 
-  desc.SetAttr("use_mkldnn", true);
+  desc.SetAttr("use_onednn", true);
   desc.SetAttr("is_test", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(desc);
diff --git a/test/cpp/fluid/mkldnn/test_onednn_op_inplace.cc b/test/cpp/fluid/mkldnn/test_onednn_op_inplace.cc
@@ -87,11 +87,11 @@ bool TestMain(const phi::Place &place,
           ? framework::OpRegistry::CreateOp(op_type,
                                             {{"X", {"x"}}, {"Y", {"x1"}}},
                                             {{"Out", {"y"}}},
-                                            {{"use_mkldnn", {true}}})
+                                            {{"use_onednn", {true}}})
           : framework::OpRegistry::CreateOp(op_type,
                                             {{"X", {"x"}}},
                                             {{"Out", {"y"}}},
-                                            {{"use_mkldnn", {true}}});
+                                            {{"use_onednn", {true}}});
 
   op_ref->Run(scope, place);
   pool.Get(place)->Wait();
@@ -104,11 +104,11 @@ bool TestMain(const phi::Place &place,
                 ? framework::OpRegistry::CreateOp(op_type,
                                                   {{"X", {"x"}}, {"Y", {"x1"}}},
                                                   {{"Out", {"x"}}},
-                                                  {{"use_mkldnn", {true}}})
+                                                  {{"use_onednn", {true}}})
                 : framework::OpRegistry::CreateOp(op_type,
                                                   {{"X", {"x"}}},
                                                   {{"Out", {"x"}}},
-                                                  {{"use_mkldnn", {true}}});
+                                                  {{"use_onednn", {true}}});
 
   op->Run(scope, place);
   phi::DeviceContextPool::Instance().Get(place)->Wait();
diff --git a/test/cpp/fluid/mkldnn/test_onednn_op_nhwc.cc b/test/cpp/fluid/mkldnn/test_onednn_op_nhwc.cc
@@ -67,7 +67,7 @@ void Test_Pool2d_Transpose_NHWC(const std::string &transpose_type) {
                                       {{"pooling_type", {std::string("max")}},
                                        {"ksize", {ksize}},
                                        {"data_format", {std::string("NHWC")}},
-                                       {"use_mkldnn", {true}}});
+                                       {"use_onednn", {true}}});
 
   auto axis = std::vector<int>(4, 0);
   axis[1] = 2;
@@ -77,7 +77,7 @@ void Test_Pool2d_Transpose_NHWC(const std::string &transpose_type) {
       transpose_type,
       {{"X", {"y"}}},
       {{"Out", {"z"}}},
-      {{"axis", {axis}}, {"use_mkldnn", {true}}});
+      {{"axis", {axis}}, {"use_onednn", {true}}});
 
   op_pool->Run(scope, p);
   op_transpose->Run(scope, p);
@@ -130,7 +130,7 @@ TEST(test_pool2d_relu_relu_nhwc, cpu_place) {
                                       {{"pooling_type", {std::string("max")}},
                                        {"ksize", {ksize}},
                                        {"data_format", {std::string("NHWC")}},
-                                       {"use_mkldnn", {true}}});
+                                       {"use_onednn", {true}}});
 
   auto axis = std::vector<int>(4, 0);
   axis[1] = 2;
@@ -140,10 +140,10 @@ TEST(test_pool2d_relu_relu_nhwc, cpu_place) {
       "relu",
       {{"X", {"y"}}},
       {{"Out", {"u"}}},
-      {{"axis", {axis}}, {"use_mkldnn", {false}}});
+      {{"axis", {axis}}, {"use_onednn", {false}}});
 
   auto op_relu2 = framework::OpRegistry::CreateOp(
-      "relu", {{"X", {"u"}}}, {{"Out", {"z"}}}, {{"use_mkldnn", {true}}});
+      "relu", {{"X", {"u"}}}, {{"Out", {"z"}}}, {{"use_onednn", {true}}});
 
   op_pool->Run(scope, p);
   op_relu1->Run(scope, p);
@@ -192,10 +192,10 @@ TEST(test_pool2d_shape_nhwc, cpu_place) {
                                       {{"pooling_type", {std::string("max")}},
                                        {"ksize", {ksize}},
                                        {"data_format", {std::string("NHWC")}},
-                                       {"use_mkldnn", {true}}});
+                                       {"use_onednn", {true}}});
 
   auto op_shape = framework::OpRegistry::CreateOp(
-      "shape", {{"Input", {"y"}}}, {{"Out", {"z"}}}, {{"use_mkldnn", {true}}});
+      "shape", {{"Input", {"y"}}}, {{"Out", {"z"}}}, {{"use_onednn", {true}}});
 
   op_pool->Run(scope, p);
   op_shape->Run(scope, p);
diff --git a/test/cpp/fluid/mkldnn/test_onednn_pool_adaptive_op.cc b/test/cpp/fluid/mkldnn/test_onednn_pool_adaptive_op.cc
@@ -67,7 +67,7 @@ void test_pool2d(bool adaptive, bool ceil_mode, std::string pool_type = "max") {
   desc.SetAttr("paddings", paddings);
   desc.SetAttr("adaptive", adaptive);
   desc.SetAttr("ceil_mode", ceil_mode);
-  desc.SetAttr("use_mkldnn", true);
+  desc.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(desc);
 
diff --git a/test/cpp/fluid/mkldnn/test_onednn_squeeze.cc b/test/cpp/fluid/mkldnn/test_onednn_squeeze.cc
@@ -62,7 +62,7 @@ void test_squeeze() {
   std::vector<int> axes({-2});
 
   desc.SetAttr("axes", axes);
-  desc.SetAttr("use_mkldnn", true);
+  desc.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(desc);
 
@@ -86,7 +86,7 @@ void test_squeeze2() {
   std::vector<int> axes({-1});
 
   desc.SetAttr("axes", axes);
-  desc.SetAttr("use_mkldnn", true);
+  desc.SetAttr("use_onednn", true);
 
   auto op = paddle::framework::OpRegistry::CreateOp(desc);
 
diff --git a/test/cpp/fluid/op_debug_string_test.cc b/test/cpp/fluid/op_debug_string_test.cc
@@ -37,7 +37,7 @@ TEST(op_debug_str, test_unknown_dtype) {
   desc.SetOutput(framework::GradVarName("X"), {framework::GradVarName("X")});
   desc.SetOutput(framework::GradVarName("Y"), {framework::GradVarName("Y")});
   desc.SetAttr("axis", -1);
-  desc.SetAttr("use_mkldnn", false);
+  desc.SetAttr("use_onednn", false);
 
   auto x_tensor = scope.Var("X")->GetMutable<phi::DenseTensor>();
   x_tensor->Resize(dim);
diff --git a/test/cpp/imperative/test_hooks.cc b/test/cpp/imperative/test_hooks.cc
@@ -104,7 +104,7 @@ TEST(TestHooks, TestGradVarLeafBackwardHook) {
   NameVarBaseMap ins = {x_pair, y_pair};
   NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
 
   // add VariableWrapper hook
   x->GradVarBase()->AddVariableWrapperHook(
@@ -211,7 +211,7 @@ void GradVarLeafBackwardHookWithGradAccumulatedTest() {
   NameVarBaseMap ins = {x_pair, y_pair};
   NameVarBaseMap outs = {out_xy_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>("mul", ins, outs, mul_attr_map, place, true);
 
   var_pair z_pair = var_pair("Y", vb_vector(1, z));
diff --git a/test/cpp/imperative/test_prepare_op.cc b/test/cpp/imperative/test_prepare_op.cc
@@ -247,7 +247,7 @@ TEST(test_prepare_op, test_complex_eager) {
 
 #ifdef PADDLE_WITH_DNNL
 TEST(test_prepare_op, test_prepare_data_cpu_onednn) {
-  TestPrepareDataSamePlace({{"use_mkldnn", true}});
+  TestPrepareDataSamePlace({{"use_onednn", true}});
 }
 #endif
 }  // namespace imperative
diff --git a/test/cpp/imperative/test_tracer.cc b/test/cpp/imperative/test_tracer.cc
@@ -89,7 +89,7 @@ TEST(test_tracer, test_trace_op) {
   imperative::NameVarBaseMap ins = {x_pair, y_pair};
   imperative::NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>("mul", ins, outs, mul_attr_map, place, true);
 
 #ifndef PADDLE_WITH_XPU
@@ -141,7 +141,7 @@ TEST(test_tracer, test_trace_op_with_backward) {
   imperative::NameVarBaseMap ins = {x_pair, y_pair};
   imperative::NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>("mul", ins, outs, mul_attr_map, place, true);
   const auto& out_tensor = vout->Var().Get<phi::DenseTensor>();
   for (int i = 0; i < vout->Var().Get<phi::DenseTensor>().numel(); i++) {
@@ -187,7 +187,7 @@ TEST(test_tracer, test_track_backward_output) {
   imperative::NameVarBaseMap ins = {x_pair, y_pair};
   imperative::NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>("mul", ins, outs, mul_attr_map, place, true);
   ASSERT_EQ(x_in->GradVarBase()->GradOpNum(), 0UL);
   ASSERT_EQ(y_in->GradVarBase()->GradOpNum(), 0UL);
@@ -232,7 +232,7 @@ TEST(test_tracer, test_track_backward_input) {
   imperative::NameVarBaseMap ins = {x_pair, y_pair};
   imperative::NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>("mul", ins, outs, mul_attr_map, place, true);
 
   ASSERT_EQ(x_in->GradVarBase()->GradOpNum(), 0UL);
@@ -280,7 +280,7 @@ TEST(test_tracer, test_trace_op_with_multi_device_inputs) {
   imperative::NameVarBaseMap ins = {x_pair, y_pair};
   imperative::NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>(
       "elementwise_add", ins, outs, mul_attr_map, gpu_place, true);
 
@@ -417,7 +417,7 @@ TEST(test_tracer, test_var_without_grad_var) {
   imperative::NameVarBaseMap ins = {x_pair, y_pair};
   imperative::NameVarBaseMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<VarBase>("mul", ins, outs, mul_attr_map, place, true);
 
   const auto& out_tensor = vout->Var().Get<phi::DenseTensor>();
@@ -636,7 +636,7 @@ TEST(test_tracer, eager_tracer) {
   imperative::NameTensorMap ins = {x_pair, y_pair};
   imperative::NameTensorMap outs = {out_pair};
   framework::AttributeMap mul_attr_map;
-  mul_attr_map["use_mkldnn"] = false;
+  mul_attr_map["use_onednn"] = false;
   tracer.TraceOp<egr::EagerVariable>(
       "mul", ins, outs, mul_attr_map, place, true);
 

Original file line number	Diff line number	Diff line change
`@@ -59,7 +59,7 @@ class TestElementwiseAddGradGradWithoutDDX`
`59`	`59`	`this->op_type_,`
`60`	`60`	`{{"Y", {"Y"}}, {"DOut", {"DOut"}}, {"DDY", {"DDY"}}},`
`61`	`61`	`{{"DDOut", {"DDOut"}}},`
`62`		`- {{"use_mkldnn", false}, {"axis", 0}});`
	`62`	`+ {{"use_onednn", false}, {"axis", 0}});`
`63`	`63`	`return op;`
`64`	`64`	`}`
`65`	`65`	`};`
Original file line number	Diff line number	Diff line change
`@@ -87,7 +87,7 @@ class TestElementwiseDivGradGradWithDout : public TestElementwiseOpGradGrad<T> {`
`87`	`87`	`{"DDY", {"DDY"}},`
`88`	`88`	`{"DX", {"DX"}}},`
`89`	`89`	`{{"Y@GRAD", {"Y@GRAD"}}, {"DDOut", {"DDOut"}}, {"DOut", {"DOut"}}},`
`90`		`- {{"use_mkldnn", false}, {"axis", 0}});`
	`90`	`+ {{"use_onednn", false}, {"axis", 0}});`
`91`	`91`	`return op;`
`92`	`92`	`}`
`93`	`93`	`};`