complete data layout transform (#7440)

* add data layout transform and optimize the implementation of data_transform

paddle/framework/CMakeLists.txt

@@ -33,8 +33,13 @@ cc_library(scope SRCS scope.cc DEPS glog threadpool)
 cc_test(scope_test SRCS scope_test.cc DEPS scope)
 
 cc_library(data_device_transform SRCS data_device_transform.cc DEPS tensor)
+nv_test(data_device_transform_test SRCS data_device_transform_test.cu
+        DEPS operator op_registry init math_function)
+
 cc_library(data_type_transform SRCS data_type_transform.cc DEPS tensor)
+
 cc_library(data_layout_transform SRCS data_layout_transform.cc DEPS tensor math_function)
+cc_test(data_layout_transform_test SRCS data_layout_transform_test.cc DEPS data_layout_transform)
 
 cc_library(data_transform SRCS data_transform.cc DEPS math_function tensor
         framework_proto selected_rows data_device_transform data_type_transform data_layout_transform)
@@ -82,5 +87,3 @@ cc_test(init_test SRCS init_test.cc DEPS init)
 
 cc_test(op_kernel_type_test SRCS op_kernel_type_test.cc DEPS place device_context framework_proto)
 cc_test(cow_ptr_tests SRCS details/cow_ptr_test.cc)
-nv_test(data_device_transform_test SRCS data_device_transform_test.cu
-        DEPS operator op_registry init math_function)

paddle/framework/data_device_transform_test.cu

@@ -150,6 +150,7 @@ TEST(Operator, CPUtoGPU) {
   // get output
   auto* output2 = scope.Var("OUT2");
   gpu_op->Run(scope, cuda_place);
+  VLOG(3) << "after gpu_op run";
 
   // auto* output2_ptr = output2->Get<LoDTensor>().data<float>();
   DeviceContextPool& pool = DeviceContextPool::Instance();

paddle/framework/data_layout_transform.cc

@@ -1,4 +1,4 @@
-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -14,12 +14,23 @@ limitations under the License. */
 
 #include "paddle/framework/data_layout_transform.h"
 
-#include "paddle/framework/tensor.h"
 #include "paddle/operators/math/math_function.h"
 
 namespace paddle {
 namespace framework {
 
+std::vector<int> GetAxis(const DataLayout& from, const DataLayout& to) {
+  PADDLE_ENFORCE_NE(from, to,
+                    "layout transform should transform different layout");
+  if (from == DataLayout::kNCHW && to == DataLayout::kNHWC) {
+    return {0, 2, 3, 1};
+  } else if (from == DataLayout::kNHWC && to == DataLayout::kNCHW) {
+    return {0, 3, 1, 2};
+  } else {
+    PADDLE_THROW("unsupported transform");
+  }
+}
+
 struct CastDataLayout {
   CastDataLayout(const platform::DeviceContext* ctx,
                  const std::vector<int>& axis, const framework::Tensor& in,
@@ -44,38 +55,36 @@ struct CastDataLayout {
   }
 };
 
-void TransDataLayout(const std::vector<int>& axis,
-                     const platform::DeviceContext* ctx,
-                     const KernelTypePair& kernel_pair, const Variable& in,
-                     Variable* out) {
-  PADDLE_ENFORCE(in.IsType<Tensor>(), "Only support Tensor transform!.");
+void TransDataLayout(const OpKernelType& kernel_type_for_var,
+                     const OpKernelType& expected_kernel_type, const Tensor& in,
+                     Tensor* out) {
   PADDLE_ENFORCE(
-      platform::places_are_same_class(kernel_pair.first.place_,
-                                      kernel_pair.second.place_),
+      platform::places_are_same_class(kernel_type_for_var.place_,
+                                      expected_kernel_type.place_),
       "TransDataLayout only support DataLayout transform on same place!");
-  PADDLE_ENFORCE(kernel_pair.first.data_type_ == kernel_pair.second.data_type_,
-                 "TransDataLayout only support Datatype are same!");
 
-  auto src = in.Get<Tensor>();
-  auto* dst = out->GetMutable<Tensor>();
-  PADDLE_ENFORCE(arity(src.dims()) == 4, "Input Arity Only Suppport 4!");
+  PADDLE_ENFORCE(arity(in.dims()) == 4, "Input Arity only support 4!");
+
+  auto& pool = platform::DeviceContextPool::Instance();
 
-  auto src_dim = src.dims();
+  auto src_dim = in.dims();
   std::vector<int64_t> dst_dim;
 
+  auto axis = GetAxis(kernel_type_for_var.data_layout_,
+                      expected_kernel_type.data_layout_);
   dst_dim.resize(axis.size());
   for (size_t i = 0; i < axis.size(); i++) {
     dst_dim[i] = src_dim[axis[i]];
   }
 
-  dst->Resize(make_ddim(dst_dim));
-  auto place = kernel_pair.second.place_;
-  dst->mutable_data(place, src.type());
+  out->Resize(make_ddim(dst_dim));
+  out->mutable_data(expected_kernel_type.place_, in.type());
 
-  auto src_type = kernel_pair.first.data_type_;
-  framework::VisitDataType(src_type, CastDataLayout(ctx, axis, src, dst));
+  framework::VisitDataType(
+      framework::ToDataType(in.type()),
+      CastDataLayout(pool.Get(expected_kernel_type.place_), axis, in, out));
 
-  dst->set_layout(kernel_pair.second.data_layout_);
+  out->set_layout(expected_kernel_type.data_layout_);
 }
 
 }  // namespace framework

paddle/framework/data_layout_transform.h

@@ -1,4 +1,4 @@
-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -15,17 +15,17 @@ limitations under the License. */
 #pragma once
 
 #include "paddle/framework/op_kernel_type.h"
+#include "paddle/framework/tensor.h"
 #include "paddle/framework/variable.h"
 
 namespace paddle {
 namespace framework {
 
-using KernelTypePair = std::pair<OpKernelType, OpKernelType>;
+std::vector<int> GetAxis(const DataLayout& from, const DataLayout& to);
 
-void TransDataLayout(const std::vector<int>& axis,
-                     const platform::DeviceContext* ctx,
-                     const KernelTypePair& kernel_pair, const Variable& in,
-                     Variable* out);
+void TransDataLayout(const OpKernelType& kernel_type_for_var,
+                     const OpKernelType& expected_kernel_type, const Tensor& in,
+                     Tensor* out);
 
 }  // namespace framework
 }  // namespace paddle

paddle/framework/data_layout_transform_test.cc

@@ -0,0 +1,44 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
+
+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/framework/data_layout_transform.h"
+
+#include "gtest/gtest.h"
+#include "paddle/platform/device_context.h"
+
+TEST(DataTransform, DataLayoutFunction) {
+  using namespace paddle::framework;
+  using namespace paddle::platform;
+
+  auto place = CPUPlace();
+  Tensor in = Tensor();
+  Tensor out = Tensor();
+  in.mutable_data<double>(make_ddim({2, 3, 1, 2}), place);
+  in.set_layout(DataLayout::kNHWC);
+
+  auto kernel_nhwc = OpKernelType(proto::DataType::FP32, place,
+                                  DataLayout::kNHWC, LibraryType::kPlain);
+  auto kernel_ncwh = OpKernelType(proto::DataType::FP32, place,
+                                  DataLayout::kNCHW, LibraryType::kPlain);
+
+  TransDataLayout(kernel_nhwc, kernel_ncwh, in, &out);
+
+  EXPECT_TRUE(out.layout() == DataLayout::kNCHW);
+  EXPECT_TRUE(out.dims() == make_ddim({2, 2, 3, 1}));
+
+  TransDataLayout(kernel_ncwh, kernel_nhwc, in, &out);
+
+  EXPECT_TRUE(in.layout() == DataLayout::kNHWC);
+  EXPECT_TRUE(in.dims() == make_ddim({2, 3, 1, 2}));
+}

paddle/framework/data_transform.cc

@@ -15,18 +15,43 @@ limitations under the License. */
 #include "paddle/framework/data_transform.h"
 
 #include "paddle/framework/data_device_transform.h"
+#include "paddle/framework/data_layout_transform.h"
 
 namespace paddle {
 namespace framework {
 
+static void PassTensorData(Tensor* from, Tensor* to) {
+  to->ShareDataWith(*from);
+  *from = Tensor();
+}
+
 void DataTransform(const OpKernelType& expected_kernel_type,
                    const OpKernelType& kernel_type_for_var,
-                   const Tensor& input_tensor, Tensor* out) {
+                   const Tensor& input_tensor, Tensor* output_tensor) {
+  bool transformed = false;
+  Tensor in;
+  in.ShareDataWith(input_tensor);
+  Tensor out;
+
+  // do layout transform
+  if (NeedTransformLayout(expected_kernel_type.data_layout_,
+                          kernel_type_for_var.data_layout_)) {
+    TransDataLayout(kernel_type_for_var, expected_kernel_type, in, &out);
+    transformed = true;
+    PassTensorData(&out, &in);
+  }
+
+  // do device transform
   if (!platform::is_same_place(kernel_type_for_var.place_,
                                expected_kernel_type.place_)) {
-    DeviceTransform(input_tensor, expected_kernel_type.place_, out);
+    DeviceTransform(in, expected_kernel_type.place_, &out);
+    transformed = true;
+    PassTensorData(&out, &in);
   }
-  PADDLE_ENFORCE_NOT_NULL(out, "out should not be null");
+
+  PADDLE_ENFORCE(transformed, "no transform is done, please check!");
+  // get output data
+  output_tensor->ShareDataWith(in);
 }
 
 void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,

paddle/framework/op_kernel_type.h

@@ -85,9 +85,14 @@ inline std::string KernelTypeToString(const OpKernelType& kernel_key) {
   return stream.str();
 }
 
+inline bool NeedTransformLayout(const DataLayout& l, const DataLayout& r) {
+  return l != DataLayout::kAnyLayout && r != DataLayout::kAnyLayout && l != r;
+}
+
 inline bool TransFromNeeded(const OpKernelType& l, const OpKernelType& r) {
   return (!platform::places_are_same_class(l.place_, r.place_)) ||
-         (l.data_type_ != r.data_type_) || (l.data_layout_ != r.data_layout_);
+         (l.data_type_ != r.data_type_) ||
+         NeedTransformLayout(l.data_layout_, r.data_layout_);
 }
 
 }  // namespace framework