Add a unittest to inplace elementwise_add (#18385)

* add_elementwise_add_inplace_test,test=develop

* rename file, test=develop

paddle/fluid/operators/elementwise/CMakeLists.txt

 include(operators)
 register_operators()
+
+cc_test(test_elementwise_add_op_inplace SRCS test_elementwise_add_op_inplace.cc DEPS op_registry elementwise_add_op scope device_context enforce executor)

paddle/fluid/operators/elementwise/test_elementwise_add_op_inplace.cc

+// Copyright (c) 2019 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 <algorithm>
+#include <cstdlib>
+#include <memory>
+#include <random>
+#include "gtest/gtest.h"
+#include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/operator.h"
+#include "paddle/fluid/framework/scope.h"
+#include "paddle/fluid/platform/device_context.h"
+#include "paddle/fluid/platform/enforce.h"
+#include "paddle/fluid/platform/place.h"
+
+USE_OP(elementwise_add);
+
+namespace paddle {
+namespace operators {
+
+static void Memcpy(void *dst, const void *src, size_t n, bool copy_to_gpu) {
+  if (copy_to_gpu) {
+#ifdef PADDLE_WITH_CUDA
+    PADDLE_ENFORCE(cudaMemcpy(dst, src, n, cudaMemcpyHostToDevice));
+#else
+    PADDLE_THROW("Not compiled with cuda");
+#endif
+  } else {
+    std::memcpy(dst, src, n);
+  }
+}
+
+template <typename T>
+bool TestMain(const platform::Place &place, const framework::DDim &dims,
+              bool inplace) {
+  framework::Scope scope;
+  auto *x = scope.Var("x")->GetMutable<framework::LoDTensor>();
+  auto *y = scope.Var("y")->GetMutable<framework::LoDTensor>();
+  auto *z = scope.Var("z")->GetMutable<framework::LoDTensor>();
+
+  x->Resize(dims);
+  y->Resize(dims);
+  z->Resize(dims);
+
+  size_t numel = static_cast<size_t>(framework::product(dims));
+
+  auto x_ptr = x->mutable_data<T>(place);
+  auto y_ptr = y->mutable_data<T>(place);
+  auto z_ptr = z->mutable_data<T>(place);
+
+  std::uniform_real_distribution<T> dist(static_cast<T>(10.0),
+                                         static_cast<T>(20.0));
+  std::mt19937 engine;
+  std::vector<T> x_data(numel), y_data(numel), z_data(numel);
+  std::vector<T> sum_result(numel);
+
+  for (size_t i = 0; i < numel; ++i) {
+    x_data[i] = dist(engine);
+    y_data[i] = dist(engine);
+    sum_result[i] = x_data[i] + y_data[i];
+    z_data[i] = -1.0;  // set some data that is not existed
+  }
+
+  auto bytes = sizeof(T) * numel;
+  bool is_gpu_place = platform::is_gpu_place(place);
+  Memcpy(x_ptr, x_data.data(), bytes, is_gpu_place);
+  Memcpy(y_ptr, y_data.data(), bytes, is_gpu_place);
+  Memcpy(z_ptr, z_data.data(), bytes, is_gpu_place);
+
+  const char *out_name = inplace ? "x" : "z";
+  auto op = framework::OpRegistry::CreateOp("elementwise_add",
+                                            {{"X", {"x"}}, {"Y", {"y"}}},
+                                            {{"Out", {out_name}}}, {});
+  op->Run(scope, place);
+  platform::DeviceContextPool::Instance().Get(place)->Wait();
+
+  framework::LoDTensor cpu_out;
+  auto &out_tensor = scope.FindVar(out_name)->Get<framework::LoDTensor>();
+  PADDLE_ENFORCE(scope.kids().empty());
+  if (inplace) {
+    PADDLE_ENFORCE_EQ(&out_tensor, x);
+  } else {
+    PADDLE_ENFORCE_EQ(&out_tensor, z);
+  }
+
+  if (is_gpu_place) {
+    framework::TensorCopySync(out_tensor, platform::CPUPlace(), &cpu_out);
+  } else {
+    cpu_out = out_tensor;
+  }
+
+  auto *out_ptr = cpu_out.data<T>();
+  bool is_equal = std::equal(out_ptr, out_ptr + numel, sum_result.data());
+  return is_equal;
+}
+
+TEST(test_elementwise_add_inplace, cpu_place) {
+  framework::DDim dims({32, 64});
+  platform::CPUPlace p;
+  ASSERT_TRUE(TestMain<float>(p, dims, true));
+}
+
+TEST(test_elementwise_add_not_inplace, cpu_place) {
+  framework::DDim dims({32, 64});
+  platform::CPUPlace p;
+  ASSERT_TRUE(TestMain<float>(p, dims, false));
+}
+
+#ifdef PADDLE_WITH_CUDA
+TEST(test_elementwise_add_inplace, gpu_place) {
+  framework::DDim dims({32, 64});
+  platform::CUDAPlace p(0);
+  ASSERT_TRUE(TestMain<float>(p, dims, true));
+}
+
+TEST(test_elementwise_add_not_inplace, gpu_place) {
+  framework::DDim dims({32, 64});
+  platform::CUDAPlace p(0);
+  ASSERT_TRUE(TestMain<float>(p, dims, false));
+}
+#endif
+
+}  // namespace operators
+}  // namespace paddle

paddle/fluid/operators/math/blas_impl.h

@@ -422,8 +422,12 @@ void Blas<platform::CPUDeviceContext>::VADD(int n, const T *x, const T *y,
 #ifdef PADDLE_WITH_MKLML
   CBlas<T>::VADD(n, x, y, z);
 #else
-  this->template VCOPY<T>(n, y, z);
-  this->template AXPY<T>(n, 1., x, z);
+  if (x == z) {
+    this->template AXPY<T>(n, 1., y, z);
+  } else {
+    this->template VCOPY<T>(n, y, z);
+    this->template AXPY<T>(n, 1., x, z);
+  }
 #endif
 }