refactor matmul directory in pten (#38227)

* refactor matmul directory in pten

* fix merge conflict

paddle/fluid/operators/matmul_v2_op.h

@@ -28,7 +28,7 @@ limitations under the License. */
 // only can include the headers in paddle/pten/api dirs
 #include "paddle/pten/api/lib/utils/tensor_utils.h"
 #include "paddle/pten/include/core.h"
-#include "paddle/pten/include/linalg.h"
+#include "paddle/pten/kernels/matmul_kernel.h"
 
 #if defined(__NVCC__) || defined(__HIPCC__)
 #include "paddle/fluid/operators/reduce_ops/reduce_op.cu.h"
@@ -384,8 +384,8 @@ class MatMulV2Kernel : public framework::OpKernel<T> {
     auto pt_out = paddle::experimental::MakePtenDenseTensor(*Out);
 
     // call new kernel
-    pten::Matmul<T>(dev_ctx, *pt_x.get(), *pt_y.get(), trans_x, trans_y,
-                    pt_out.get());
+    pten::MatmulKernel<T>(dev_ctx, *pt_x, *pt_y, trans_x, trans_y,
+                          pt_out.get());
   }
 };
 

paddle/pten/CMakeLists.txt

@@ -28,10 +28,10 @@ get_property(pten_kernels GLOBAL PROPERTY PTEN_KERNELS)
 # keep this message for debug, remove it later if needless
 message(STATUS "All standard pten kernels: ${pten_kernels}")
 set(PTEN_DEPS ${PTEN_DEPS} ${pten_kernels})
-set(PTEN_DEPS ${PTEN_DEPS} math_cpu linalg_cpu)
+set(PTEN_DEPS ${PTEN_DEPS} math_cpu)
 set(PTEN_DEPS ${PTEN_DEPS} nary unary binary)
 if(WITH_GPU OR WITH_ROCM)
-  set(PTEN_DEPS ${PTEN_DEPS} math_gpu linalg_gpu)
+  set(PTEN_DEPS ${PTEN_DEPS} math_gpu)
 endif()
 
 cc_library(pten SRCS all.cc DEPS ${PTEN_DEPS})

paddle/pten/api/lib/kernel_declare.h

@@ -20,10 +20,8 @@ limitations under the License. */
 // the kernel declare statement is automatically generated according to the
 // file name of the kernel, and this header file will be removed
 
-PT_DECLARE_KERNEL(matmul, CPU, ALL_LAYOUT);
 PT_DECLARE_KERNEL(mean, CPU, ALL_LAYOUT);
 
 #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
-PT_DECLARE_KERNEL(matmul, GPU, ALL_LAYOUT);
 PT_DECLARE_KERNEL(mean, GPU, ALL_LAYOUT);
 #endif

paddle/pten/include/linalg.h

@@ -17,9 +17,7 @@
 // See Note: [ How do we organize the kernel directory ]
 #include "paddle/pten/api/lib/utils/storage.h"
 #include "paddle/pten/include/infermeta.h"
-#include "paddle/pten/kernels/cpu/linalg.h"
 #include "paddle/pten/kernels/dot_kernel.h"
-#include "paddle/pten/kernels/gpu/linalg.h"
 
 namespace pten {
 

paddle/pten/kernels/cpu/CMakeLists.txt

 cc_library(math_cpu SRCS math.cc DEPS dense_tensor kernel_context kernel_factory eigen_function blas pten_transpose_cpu cast_kernel)
-cc_library(linalg_cpu SRCS linalg.cc DEPS dense_tensor kernel_context kernel_factory)

paddle/pten/kernels/cpu/linalg.cc

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#include "paddle/pten/kernels/cpu/linalg.h"
-
-#include "paddle/pten/core/kernel_registry.h"
-
-// See Note [ Why still include the fluid headers? ]
-#include "paddle/fluid/framework/eigen.h"
-#include "paddle/fluid/operators/math/blas.h"
-#include "paddle/fluid/platform/complex.h"
-
-#include "paddle/pten/kernels/hybird/math/matmul_func.h"
-
-namespace pten {
-
-template <typename T>
-void Matmul(const CPUContext& dev_ctx,
-            const DenseTensor& x,
-            const DenseTensor& y,
-            bool transpose_x,
-            bool transpose_y,
-            DenseTensor* out) {
-  PADDLE_ENFORCE_NE(paddle::framework::product(x.dims()),
-                    0,
-                    paddle::platform::errors::InvalidArgument(
-                        "The Input(X) dims size must not be equal 0,"
-                        " but reviced dims size is 0. "));
-  PADDLE_ENFORCE_NE(paddle::framework::product(y.dims()),
-                    0,
-                    paddle::platform::errors::InvalidArgument(
-                        "The Input(Y) dims size must not be equal 0,"
-                        " but reviced dims size is 0. "));
-  math::MatMulFunction<CPUContext, T>(
-      dev_ctx, x, y, out, transpose_x, transpose_y);
-}
-
-}  // namespace pten
-
-using complex64 = ::paddle::platform::complex<float>;
-using complex128 = ::paddle::platform::complex<double>;
-
-PT_REGISTER_KERNEL(matmul,
-                   CPU,
-                   ALL_LAYOUT,
-                   pten::Matmul,
-                   float,
-                   double,
-                   complex64,
-                   complex128) {}

paddle/pten/kernels/cpu/linalg.h

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#pragma once
-
-#include "paddle/pten/backends/cpu/cpu_context.h"
-#include "paddle/pten/core/dense_tensor.h"
-
-// See Note [ Why still include the fluid headers? ]
-#include "paddle/fluid/platform/device_context.h"
-
-namespace pten {
-
-template <typename T>
-void Matmul(const CPUContext& dev_ctx,
-            const DenseTensor& x,
-            const DenseTensor& y,
-            bool transpose_x,
-            bool transpose_y,
-            DenseTensor* out);
-
-}  // namespace pten

paddle/pten/kernels/cpu/matmul_kernel.cc

+/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/pten/kernels/matmul_kernel.h"
+
+#include "paddle/pten/backends/cpu/cpu_context.h"
+#include "paddle/pten/core/kernel_registry.h"
+
+#include "paddle/fluid/platform/complex.h"
+#include "paddle/pten/kernels/impl/matmul_kernel_impl.h"
+
+PT_REGISTER_CTX_KERNEL(matmul,
+                       CPU,
+                       ALL_LAYOUT,
+                       pten::MatmulKernel,
+                       float,
+                       double,
+                       paddle::platform::complex<float>,
+                       paddle::platform::complex<double>) {}

paddle/pten/kernels/gpu/CMakeLists.txt

 if(WITH_GPU)
   nv_library(math_gpu SRCS math.cu DEPS eigen_function dense_tensor convert_utils kernel_context kernel_factory pten_transpose_gpu cast_kernel copy_kernel)
-  nv_library(linalg_gpu SRCS linalg.cu DEPS eigen_function dense_tensor kernel_context kernel_factory)
 elseif(WITH_ROCM)
   hip_library(math_gpu SRCS math.cu DEPS eigen_function dense_tensor convert_utils kernel_context kernel_factory pten_transpose_gpu cast_kernel copy_kernel)
-  hip_library(linalg_gpu SRCS linalg.cu DEPS eigen_function dense_tensor kernel_context kernel_factory)
 endif()

paddle/pten/kernels/gpu/linalg.cu

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#include "paddle/pten/kernels/gpu/linalg.h"
-
-#include "paddle/pten/core/kernel_registry.h"
-#include "paddle/pten/kernels/hybird/math/matmul_func.h"
-
-// See Note [ Why still include the fluid headers? ]
-#include "paddle/fluid/platform/complex.h"
-
-namespace pten {
-
-template <typename T>
-void Matmul(const GPUContext& dev_ctx,
-            const DenseTensor& x,
-            const DenseTensor& y,
-            bool transpose_x,
-            bool transpose_y,
-            DenseTensor* out) {
-  PADDLE_ENFORCE_NE(paddle::framework::product(x.dims()),
-                    0,
-                    paddle::platform::errors::InvalidArgument(
-                        "The Input(X) dims size must not be equal 0,"
-                        " but reviced dims size is 0. "));
-  PADDLE_ENFORCE_NE(paddle::framework::product(y.dims()),
-                    0,
-                    paddle::platform::errors::InvalidArgument(
-                        "The Input(Y) dims size must not be equal 0,"
-                        " but reviced dims size is 0. "));
-  math::MatMulFunction<GPUContext, T>(
-      dev_ctx, x, y, out, transpose_x, transpose_y);
-}
-
-}  // namespace pten
-
-using float16 = paddle::platform::float16;
-using complex64 = ::paddle::platform::complex<float>;
-using complex128 = ::paddle::platform::complex<double>;
-
-PT_REGISTER_KERNEL(matmul,
-                   GPU,
-                   ALL_LAYOUT,
-                   pten::Matmul,
-                   float,
-                   double,
-                   float16,
-                   complex64,
-                   complex128) {}

paddle/pten/kernels/gpu/matmul_kernel.cu

+/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/pten/kernels/matmul_kernel.h"
+
+#include "paddle/pten/backends/gpu/gpu_context.h"
+#include "paddle/pten/core/kernel_registry.h"
+
+#include "paddle/fluid/platform/complex.h"
+#include "paddle/pten/kernels/impl/matmul_kernel_impl.h"
+
+PT_REGISTER_CTX_KERNEL(matmul,
+                       GPU,
+                       ALL_LAYOUT,
+                       pten::MatmulKernel,
+                       float,
+                       double,
+                       paddle::platform::float16,
+                       paddle::platform::complex<float>,
+                       paddle::platform::complex<double>) {}

paddle/pten/kernels/hybird/math/matmul_func.h → paddle/pten/kernels/impl/matmul_kernel_impl.h

@@ -20,7 +20,6 @@ limitations under the License. */
 #include "paddle/pten/core/dense_tensor.h"
 
 namespace pten {
-namespace math {
 
 static void GetBroadcastFromDims(const int x_ndim,
                                  const std::int64_t* x_dims,
@@ -86,8 +85,8 @@ static void IndexIncreaseFromDims(const int ndim,
   }
 }
 
-template <typename DeviceContext, typename T>
-void MatMulFunction(const DeviceContext& dev_ctx,
+template <typename Context, typename T>
+void MatMulFunction(const Context& context,
                     const DenseTensor& X,
                     const DenseTensor& Y,
                     const std::vector<std::int64_t>& x_dims,
@@ -103,7 +102,7 @@ void MatMulFunction(const DeviceContext& dev_ctx,
   const T* x_data = X.data<T>();
   const T* y_data = Y.data<T>();
 
-  auto blas = paddle::operators::math::GetBlas<DeviceContext, T>(dev_ctx);
+  auto blas = paddle::operators::math::GetBlas<Context, T>(context);
 
   if (x_ndim == 1 && y_ndim == 1) {
     const int M = X.numel();
@@ -471,8 +470,8 @@ void MatMulFunction(const DeviceContext& dev_ctx,
   }
 }
 
-template <typename DeviceContext, typename T>
-void MatMulFunction(const DeviceContext& dev_ctx,
+template <typename Context, typename T>
+void MatMulFunction(const Context& context,
                     const DenseTensor& X,
                     const DenseTensor& Y,
                     DenseTensor* Out,
@@ -481,9 +480,28 @@ void MatMulFunction(const DeviceContext& dev_ctx,
                     bool flag = false) {
   const std::vector<std::int64_t> x_dims = vectorize(X.dims());
   const std::vector<std::int64_t> y_dims = vectorize(Y.dims());
-  MatMulFunction<DeviceContext, T>(
-      dev_ctx, X, Y, x_dims, y_dims, Out, trans_x, trans_y, flag);
+  MatMulFunction<Context, T>(
+      context, X, Y, x_dims, y_dims, Out, trans_x, trans_y, flag);
+}
+
+template <typename T, typename Context>
+void MatmulKernel(const Context& context,
+                  const DenseTensor& x,
+                  const DenseTensor& y,
+                  bool transpose_x,
+                  bool transpose_y,
+                  DenseTensor* out) {
+  PADDLE_ENFORCE_NE(paddle::framework::product(x.dims()),
+                    0,
+                    paddle::platform::errors::InvalidArgument(
+                        "The Input(X) dims size must not be equal 0,"
+                        " but reviced dims size is 0. "));
+  PADDLE_ENFORCE_NE(paddle::framework::product(y.dims()),
+                    0,
+                    paddle::platform::errors::InvalidArgument(
+                        "The Input(Y) dims size must not be equal 0,"
+                        " but reviced dims size is 0. "));
+  MatMulFunction<Context, T>(context, x, y, out, transpose_x, transpose_y);
 }
 
-}  // namespace math
 }  // namespace pten

paddle/pten/kernels/gpu/linalg.h → paddle/pten/kernels/matmul_kernel.h

@@ -14,22 +14,33 @@
 
 #pragma once
 
-// CUDA and HIP use same api
-#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
-
-#include "paddle/pten/backends/gpu/gpu_context.h"
+#include "paddle/pten/api/lib/utils/storage.h"
 #include "paddle/pten/core/dense_tensor.h"
+#include "paddle/pten/include/infermeta.h"
 
 namespace pten {
 
-template <typename T>
-void Matmul(const GPUContext& dev_ctx,
-            const DenseTensor& x,
-            const DenseTensor& y,
-            bool transpose_x,
-            bool transpose_y,
-            DenseTensor* out);
+template <typename T, typename Context>
+void MatmulKernel(const Context& context,
+                  const DenseTensor& x,
+                  const DenseTensor& y,
+                  bool transpose_x,
+                  bool transpose_y,
+                  DenseTensor* out);
 
-}  // namespace pten
+template <typename T, typename Context>
+DenseTensor Matmul(const Context& context,
+                   const DenseTensor& x,
+                   const DenseTensor& y,
+                   bool transpose_x,
+                   bool transpose_y) {
+  auto out_meta = MatmulInferMeta(x.meta(), y.meta(), transpose_x, transpose_y);
+  DenseTensor dense_out(
+      pten::make_intrusive<paddle::experimental::SharedStorage>(
+          context.GetPlace()),
+      std::move(out_meta));
+  MatmulKernel<T, Context>(context, x, y, transpose_x, transpose_y, &dense_out);
+  return dense_out;
+}
 
-#endif
+}  // namespace pten

paddle/pten/tests/kernels/CMakeLists.txt

@@ -2,6 +2,7 @@ cc_test(test_copy_dev_api SRCS test_copy_dev_api.cc DEPS pten pten_api_utils)
 cc_test(test_dot_dev_api SRCS test_dot_dev_api.cc DEPS pten pten_api_utils)
 cc_test(test_creation_dev_api SRCS test_creation_dev_api.cc DEPS pten pten_api_utils)
 cc_test(test_flatten_dev_api SRCS test_flatten_dev_api.cc DEPS pten pten_api_utils)
+cc_test(test_matmul_dev_api SRCS test_matmul_dev_api.cc DEPS pten pten_api_utils)
 cc_test(test_mean_dev_api SRCS test_mean_dev_api.cc DEPS pten pten_api_utils)
 cc_test(test_scale_dev_api SRCS test_scale_dev_api.cc DEPS pten pten_api_utils)
 cc_test(test_cast_dev_api SRCS test_cast_dev_api.cc DEPS pten pten_api_utils)

paddle/pten/tests/kernels/test_matmul_dev_api.cc

+/* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <gtest/gtest.h>
+#include <memory>
+
+#include "paddle/pten/kernels/matmul_kernel.h"
+
+#include "paddle/pten/api/lib/utils/allocator.h"
+#include "paddle/pten/core/dense_tensor.h"
+#include "paddle/pten/core/kernel_registry.h"
+
+namespace pten {
+namespace tests {
+
+namespace framework = paddle::framework;
+using DDim = paddle::framework::DDim;
+
+TEST(DEV_API, dot) {
+  // 1. create tensor
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  DenseTensor dense_x(alloc,
+                      pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                            framework::make_ddim({3, 3}),
+                                            pten::DataLayout::NCHW));
+
+  auto* dense_x_data = dense_x.mutable_data<float>();
+
+  DenseTensor dense_y(alloc,
+                      pten::DenseTensorMeta(pten::DataType::FLOAT32,
+                                            framework::make_ddim({3, 3}),
+                                            pten::DataLayout::NCHW));
+  auto* dense_y_data = dense_y.mutable_data<float>();
+
+  for (size_t i = 0; i < 9; ++i) {
+    dense_x_data[i] = 1.0;
+    dense_y_data[i] = 2.0;
+  }
+  std::vector<float> sum(9, 6.0);
+
+  paddle::platform::DeviceContextPool& pool =
+      paddle::platform::DeviceContextPool::Instance();
+  auto* ctx = pool.Get(paddle::platform::CPUPlace());
+
+  // 2. test API
+  auto out = Matmul<float, CPUContext>(
+      *(static_cast<CPUContext*>(ctx)), dense_x, dense_y, false, false);
+
+  // 3. check result
+  ASSERT_EQ(out.dims().size(), 2);
+  ASSERT_EQ(out.dims()[0], 3);
+  ASSERT_EQ(out.dims()[1], 3);
+  ASSERT_EQ(out.numel(), 9);
+  ASSERT_EQ(out.dtype(), DataType::FLOAT32);
+  ASSERT_EQ(out.layout(), DataLayout::NCHW);
+  ASSERT_EQ(out.initialized(), true);
+
+  for (size_t i = 0; i < 9; i++) {
+    ASSERT_NEAR(sum[i], out.data<float>()[i], 1e-6f);
+  }
+}
+
+}  // namespace tests
+}  // namespace pten