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Merged
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Aug 11, 2025
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test/cpp modify use_mkldnn [fluid_ops] #74501

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2 changes: 1 addition & 1 deletion test/cpp/eager/performance_tests/benchmark_utils.cc
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Expand Up @@ -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;
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2 changes: 1 addition & 1 deletion test/cpp/fluid/elementwise/test_elementwise_add_grad_grad.cc
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Expand Up @@ -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;
}
};
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2 changes: 1 addition & 1 deletion test/cpp/fluid/elementwise/test_elementwise_div_grad_grad.cc
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Expand Up @@ -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;
}
};
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10 changes: 5 additions & 5 deletions test/cpp/fluid/mkldnn/test_conv_onednn_nhwc.cc
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Expand Up @@ -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);

Expand Down Expand Up @@ -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);

Expand Down Expand Up @@ -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);

Expand Down Expand Up @@ -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);

Expand Down Expand Up @@ -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);

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4 changes: 2 additions & 2 deletions test/cpp/fluid/mkldnn/test_onednn_caching.cc
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Expand Up @@ -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();
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2 changes: 1 addition & 1 deletion test/cpp/fluid/mkldnn/test_onednn_conv2d_transpose_bias.cc
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Expand Up @@ -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);
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8 changes: 4 additions & 4 deletions test/cpp/fluid/mkldnn/test_onednn_op_inplace.cc
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Expand Up @@ -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();
Expand All @@ -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();
Expand Down
14 changes: 7 additions & 7 deletions test/cpp/fluid/mkldnn/test_onednn_op_nhwc.cc
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Expand Up @@ -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;
Expand All @@ -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);
Expand Down Expand Up @@ -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;
Expand All @@ -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);
Expand Down Expand Up @@ -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);
Expand Down
2 changes: 1 addition & 1 deletion test/cpp/fluid/mkldnn/test_onednn_pool_adaptive_op.cc
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Expand Up @@ -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);

Expand Down
4 changes: 2 additions & 2 deletions test/cpp/fluid/mkldnn/test_onednn_squeeze.cc
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Expand Up @@ -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);

Expand All @@ -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);

Expand Down
2 changes: 1 addition & 1 deletion test/cpp/fluid/op_debug_string_test.cc
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Expand Up @@ -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);
Expand Down
4 changes: 2 additions & 2 deletions test/cpp/imperative/test_hooks.cc
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Expand Up @@ -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(
Expand Down Expand Up @@ -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));
Expand Down
2 changes: 1 addition & 1 deletion test/cpp/imperative/test_prepare_op.cc
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Expand Up @@ -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
Expand Down
14 changes: 7 additions & 7 deletions test/cpp/imperative/test_tracer.cc
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Expand Up @@ -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
Expand Down Expand Up @@ -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++) {
Expand Down Expand Up @@ -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);
Expand Down Expand Up @@ -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);
Expand Down Expand Up @@ -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);

Expand Down Expand Up @@ -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>();
Expand Down Expand Up @@ -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);

Expand Down
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