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Rename mkldnn onednn in paddle/cinn #63199

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Apr 3, 2024
Merged

Rename mkldnn onednn in paddle/cinn #63199

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22 changes: 11 additions & 11 deletions paddle/cinn/hlir/op/nn.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -167,7 +167,7 @@ std::shared_ptr<OpStrategy> StrategyForConv2d(
int groups = 1;
std::string key = "";
std::string conv_type = "";
bool use_mkldnn = false;
bool use_onednn = false;
if (attrs.attr_store.find("padding") != attrs.attr_store.end()) {
padding = absl::get<std::vector<int>>(attrs.attr_store.at("padding"));
}
Expand All @@ -183,8 +183,8 @@ std::shared_ptr<OpStrategy> StrategyForConv2d(
if (attrs.attr_store.find("groups") != attrs.attr_store.end()) {
groups = absl::get<int>(attrs.attr_store.at("groups"));
}
if (attrs.attr_store.find("use_mkldnn") != attrs.attr_store.end()) {
use_mkldnn = absl::get<bool>(attrs.attr_store.at("use_mkldnn"));
if (attrs.attr_store.find("use_onednn") != attrs.attr_store.end()) {
use_onednn = absl::get<bool>(attrs.attr_store.at("use_onednn"));
}
if (attrs.attr_store.find("key") != attrs.attr_store.end()) {
key = absl::get<std::string>(attrs.attr_store.at("key"));
Expand Down Expand Up @@ -231,7 +231,7 @@ std::shared_ptr<OpStrategy> StrategyForConv2d(
// A is input: [N, C, H, W], B is filter: [C_out, C_in/group,
// filter_h, filter_w]
if (target.arch == Target::Arch::X86) {
if (groups == 1 && !use_mkldnn) {
if (groups == 1 && !use_onednn) {
out = pe::Conv2d_NCHW_5D(A.as_tensor_ref(),
B.as_tensor_ref(),
padding[0],
Expand All @@ -245,7 +245,7 @@ std::shared_ptr<OpStrategy> StrategyForConv2d(
target);
} else {
#ifdef CINN_WITH_DNNL
out = pe::Conv2d_NCHW_MKLDNN(A.as_tensor_ref(),
out = pe::Conv2d_NCHW_ONEDNN(A.as_tensor_ref(),
B.as_tensor_ref(),
padding[0],
padding[1],
Expand Down Expand Up @@ -1912,12 +1912,12 @@ std::shared_ptr<OpStrategy> StrategyForSoftmax(
const std::vector<std::vector<int>> &output_shapes,
const Target &target) {
int axis = -1;
bool use_mkldnn = false;
bool use_onednn = false;
if (attrs.attr_store.count("axis")) {
axis = absl::get<int>(attrs.attr_store.at("axis"));
}
if (attrs.attr_store.count("use_mkldnn")) {
use_mkldnn = absl::get<bool>(attrs.attr_store.at("use_mkldnn"));
if (attrs.attr_store.count("use_onednn")) {
use_onednn = absl::get<bool>(attrs.attr_store.at("use_onednn"));
}
framework::CINNCompute softmax_compute(
[=](lang::Args args, lang::RetValue *ret) {
Expand All @@ -1942,8 +1942,8 @@ std::shared_ptr<OpStrategy> StrategyForSoftmax(
pack_args[pack_args.size() - 1].operator std::string();

#ifdef CINN_WITH_DNNL
if (use_mkldnn) {
out = pe::SoftmaxMKLDNN(A, new_axis, tensor_name);
if (use_onednn) {
out = pe::SoftmaxONEDNN(A, new_axis, tensor_name);
} else {
out = pe::Softmax(A, new_axis, tensor_name);
}
Expand Down Expand Up @@ -2043,7 +2043,7 @@ std::vector<std::vector<std::string>> InferLayoutForSoftmax(
CHECK_EQ(input_layouts.size(), 1U)
<< "The input's layout size is not 1! Please check again.";
if (input_shapes[0].size() > 4) {
// input tensor needs to be transformed back to NCHW for mkldnn
// input tensor needs to be transformed back to NCHW for onednn
return {{"NCHW", "NCHW"}, {"NCHW"}};
}
return {{input_layouts[0], input_layouts[0]}, input_layouts};
Expand Down
12 changes: 6 additions & 6 deletions paddle/cinn/hlir/pe/nn.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -652,7 +652,7 @@ std::vector<ir::Tensor> Conv2d_NCHWc(const ir::Tensor &input,
}

#ifdef CINN_WITH_DNNL
std::vector<ir::Tensor> Conv2d_NCHW_MKLDNN(const ir::Tensor &input,
std::vector<ir::Tensor> Conv2d_NCHW_ONEDNN(const ir::Tensor &input,
const ir::Tensor &weights,
int pad_h,
int pad_w,
Expand All @@ -674,7 +674,7 @@ std::vector<ir::Tensor> Conv2d_NCHW_MKLDNN(const ir::Tensor &input,
auto call = Compute(
{Expr(1)},
[=]() -> Expr {
return lang::CallExtern("cinn_cpu_mkldnn_conv2d_nchw_fp32",
return lang::CallExtern("cinn_cpu_onednn_conv2d_nchw_fp32",
{
Expr(input->shape[0]), // batch_size
Expr(input->shape[1]), // c_in
Expand All @@ -694,7 +694,7 @@ std::vector<ir::Tensor> Conv2d_NCHW_MKLDNN(const ir::Tensor &input,
weights // weights
});
},
UniqName("conv2d_nchw_mkldnn_out"));
UniqName("conv2d_nchw_onednn_out"));
auto out = call->TupleGet(0);
out->WithBuffer(input->type());
return {out, call};
Expand Down Expand Up @@ -1020,11 +1020,11 @@ std::vector<ir::Tensor> Softmax(const ir::Tensor &A,
}

#ifdef CINN_WITH_DNNL
std::vector<ir::Tensor> SoftmaxMKLDNN(const ir::Tensor &A,
std::vector<ir::Tensor> SoftmaxONEDNN(const ir::Tensor &A,
int axis,
const std::string &output_name) {
CHECK_LE(A->shape.size(), 4U)
<< "Input's dimension of mkldnn softmax op is less than 4! Please check.";
<< "Input's dimension of onednn softmax op is less than 4! Please check.";
if (axis == -1) {
axis = A->shape.size() - 1;
}
Expand All @@ -1036,7 +1036,7 @@ std::vector<ir::Tensor> SoftmaxMKLDNN(const ir::Tensor &A,
auto call = Compute(
{Expr(1)},
[=]() -> Expr {
return lang::CallExtern("cinn_cpu_mkldnn_softmax_fp32",
return lang::CallExtern("cinn_cpu_onednn_softmax_fp32",
{
shape[0], // batch_size
shape[1], // c_in
Expand Down
4 changes: 2 additions & 2 deletions paddle/cinn/hlir/pe/nn.h
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Original file line number Diff line number Diff line change
Expand Up @@ -179,7 +179,7 @@ std::vector<ir::Tensor> Conv2d_NCHWc(
const cinn::common::Target &target = cinn::common::DefaultHostTarget());

#ifdef CINN_WITH_DNNL
std::vector<ir::Tensor> Conv2d_NCHW_MKLDNN(
std::vector<ir::Tensor> Conv2d_NCHW_ONEDNN(
const ir::Tensor &input,
const ir::Tensor &weights,
int pad_h,
Expand Down Expand Up @@ -333,7 +333,7 @@ std::vector<ir::Tensor> Softmax(
const std::string &output_name = UniqName("T_softmax_out"));

#ifdef CINN_WITH_DNNL
std::vector<ir::Tensor> SoftmaxMKLDNN(
std::vector<ir::Tensor> SoftmaxONEDNN(
const ir::Tensor &A,
int axis = -1,
const std::string &output_name = UniqName("T_softmax_out"));
Expand Down
4 changes: 2 additions & 2 deletions paddle/cinn/runtime/cpu/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@ gather_srcs(cinnapi_src SRCS host_intrinsics.cc thread_backend.cc)
if(WITH_MKL_CBLAS)
gather_srcs(cinnapi_src SRCS mkl_math.cc cblas.cc)
if(WITH_MKLDNN)
gather_srcs(cinnapi_src SRCS mkldnn_math.cc)
gather_srcs(cinnapi_src SRCS onednn_math.cc)
endif()
endif()

Expand All @@ -16,7 +16,7 @@ if(WITH_MKL_CBLAS)
endif()

if(WITH_MKLDNN)
cinn_cc_test(test_mkldnn_math SRCS mkldnn_math_test.cc mkldnn_math.cc DEPS
cinn_cc_test(test_onednn_math SRCS onednn_math_test.cc onednn_math.cc DEPS
cinncore)
endif()
endif()
12 changes: 6 additions & 6 deletions paddle/cinn/runtime/cpu/mkldnn_math.cc → paddle/cinn/runtime/cpu/onednn_math.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.

#include "paddle/cinn/runtime/cpu/mkldnn_math.h"
#include "paddle/cinn/runtime/cpu/onednn_math.h"

#include <vector>

Expand All @@ -25,7 +25,7 @@ using dnnl::memory;
using tag = memory::format_tag;
using dt = memory::data_type;

void cinn_cpu_mkldnn_softmax_fp32(int batch,
void cinn_cpu_onednn_softmax_fp32(int batch,
int channel,
int h,
int w,
Expand Down Expand Up @@ -75,7 +75,7 @@ void cinn_cpu_mkldnn_softmax_fp32(int batch,
engine_stream.wait();
}

void cinn_cpu_mkldnn_conv2d_nchw_fp32(int batch_size,
void cinn_cpu_onednn_conv2d_nchw_fp32(int batch_size,
int c_in,
int input_h,
int input_w,
Expand Down Expand Up @@ -157,7 +157,7 @@ void cinn_cpu_mkldnn_conv2d_nchw_fp32(int batch_size,
cpu_stream.wait();
}

CINN_REGISTER_HELPER(cinn_cpu_mkldnn) {
CINN_REGISTER_HELPER(cinn_cpu_onednn) {
using namespace cinn; // NOLINT
using backends::FunctionProto;
auto host_target = cinn::common::DefaultHostTarget();
Expand Down Expand Up @@ -195,7 +195,7 @@ CINN_REGISTER_HELPER(cinn_cpu_mkldnn) {
return shape;
};

REGISTER_EXTERN_FUNC_HELPER(cinn_cpu_mkldnn_conv2d_nchw_fp32, host_target)
REGISTER_EXTERN_FUNC_HELPER(cinn_cpu_onednn_conv2d_nchw_fp32, host_target)
.SetRetType<void>()
.AddInputType<int>() // batch_size
.AddInputType<int>() // c_in
Expand All @@ -217,7 +217,7 @@ CINN_REGISTER_HELPER(cinn_cpu_mkldnn) {
.SetShapeInference(inference_shape_conv2d_nchw)
.End();

REGISTER_EXTERN_FUNC_HELPER(cinn_cpu_mkldnn_softmax_fp32, host_target)
REGISTER_EXTERN_FUNC_HELPER(cinn_cpu_onednn_softmax_fp32, host_target)
.SetRetType<void>()
.AddInputType<int>() // batch_size
.AddInputType<int>() // c_in
Expand Down
4 changes: 2 additions & 2 deletions paddle/cinn/runtime/cpu/mkldnn_math.h → paddle/cinn/runtime/cpu/onednn_math.h
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Original file line number Diff line number Diff line change
Expand Up @@ -21,15 +21,15 @@

// define some C APIs
extern "C" {
void cinn_cpu_mkldnn_softmax_fp32(int batch,
void cinn_cpu_onednn_softmax_fp32(int batch,
int channel,
int h,
int w,
int axis,
cinn_buffer_t* inputs,
cinn_buffer_t* out);

void cinn_cpu_mkldnn_conv2d_nchw_fp32(int batch_size,
void cinn_cpu_onednn_conv2d_nchw_fp32(int batch_size,
int c_in,
int input_h,
int input_w,
Expand Down
6 changes: 3 additions & 3 deletions paddle/cinn/runtime/cpu/mkldnn_math_test.cc → paddle/cinn/runtime/cpu/onednn_math_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@ cinn_buffer_t *CreateBuffer(const std::vector<int> shape,
return cinn::common::BufferBuilder(Float(32), shape).set_zero().Build();
}

TEST(cinn_cpu_mkldnn_conv2d_nchw_fp32, test) {
TEST(cinn_cpu_onednn_conv2d_nchw_fp32, test) {
int n(1);
int c_in(3);
int i_h(224);
Expand All @@ -65,7 +65,7 @@ TEST(cinn_cpu_mkldnn_conv2d_nchw_fp32, test) {
auto call = Compute(
{Expr(1)},
[=]() -> Expr {
return lang::CallExtern("cinn_cpu_mkldnn_conv2d_nchw_fp32",
return lang::CallExtern("cinn_cpu_onednn_conv2d_nchw_fp32",
{
Expr(n), // batch_size
Expr(c_in), // c_in
Expand All @@ -85,7 +85,7 @@ TEST(cinn_cpu_mkldnn_conv2d_nchw_fp32, test) {
weights.tensor() // weights
});
},
"cinn_cpu_mkldnn_conv2d_nchw_fp32");
"cinn_cpu_onednn_conv2d_nchw_fp32");

auto out = call->TupleGet(0);
out->WithBuffer(Float(32));
Expand Down
2 changes: 1 addition & 1 deletion paddle/cinn/runtime/cpu/use_extern_funcs.h
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Expand Up @@ -21,7 +21,7 @@ CINN_USE_REGISTER(host_intrinsics)
CINN_USE_REGISTER(mkl_math)
CINN_USE_REGISTER(cinn_cpu_mkl)
#ifdef CINN_WITH_DNNL
CINN_USE_REGISTER(cinn_cpu_mkldnn)
CINN_USE_REGISTER(cinn_cpu_onednn)
#endif
#endif
CINN_USE_REGISTER(cinn_backend_parallel)