Merge pull request #13685 from luotao1/naive_cmake

update libpaddle_fluid.a/so

paddle/fluid/framework/ir/CMakeLists.txt

@@ -1,5 +1,6 @@
 set(pass_file ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/paddle_inference_pass.h)
 file(WRITE ${pass_file} "// Generated by the paddle/fluid/framework/ir/CMakeLists.txt.  DO NOT EDIT!\n\n")
+file(APPEND ${pass_file} "\#pragma once\n")
 file(APPEND ${pass_file} "\#include \"paddle/fluid/framework/ir/pass.h\"\n")
 
 

paddle/fluid/inference/CMakeLists.txt

@@ -20,7 +20,8 @@ cc_library(paddle_fluid_origin DEPS ${fluid_modules} paddle_fluid_api)
 add_subdirectory(api)
 
 # Create static library
-cc_library(paddle_fluid DEPS ${fluid_modules} paddle_fluid_api paddle_inference_api analysis_predictor)
+cc_library(paddle_fluid DEPS ${fluid_modules} paddle_fluid_api paddle_inference_api 
+           analysis_predictor zero_copy_tensor)
 if(NOT APPLE)
   # TODO(liuyiqu: Temporarily disable the link flag because it is not support on Mac.
   set(LINK_FLAGS "-Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/paddle_fluid.sym")
@@ -31,6 +32,7 @@ endif()
 cc_library(paddle_fluid_shared SHARED
     SRCS io.cc ${CMAKE_CURRENT_SOURCE_DIR}/api/api.cc ${CMAKE_CURRENT_SOURCE_DIR}/api/api_impl.cc
     ${CMAKE_CURRENT_SOURCE_DIR}/api/analysis_predictor.cc
+    ${CMAKE_CURRENT_SOURCE_DIR}/api/details/zero_copy_tensor.cc
     DEPS ${fluid_modules} paddle_fluid_api)
 
 set_target_properties(paddle_fluid_shared PROPERTIES OUTPUT_NAME paddle_fluid)

paddle/fluid/inference/api/analysis_predictor.cc

@@ -24,7 +24,6 @@
 #include "paddle/fluid/inference/api/helper.h"
 #include "paddle/fluid/inference/api/paddle_inference_api.h"
 #include "paddle/fluid/inference/api/paddle_inference_pass.h"
-#include "paddle/fluid/inference/api/timer.h"
 #include "paddle/fluid/inference/utils/singleton.h"
 #include "paddle/fluid/platform/profiler.h"
 

paddle/fluid/inference/api/api_impl.cc

@@ -23,7 +23,6 @@ limitations under the License. */
 #include "paddle/fluid/framework/feed_fetch_method.h"
 #include "paddle/fluid/inference/api/api_impl.h"
 #include "paddle/fluid/inference/api/helper.h"
-#include "paddle/fluid/inference/api/timer.h"
 #include "paddle/fluid/platform/profiler.h"
 
 DEFINE_bool(profile, false, "Turn on profiler for fluid");

paddle/fluid/inference/api/helper.h

@@ -16,19 +16,34 @@
 
 #include <glog/logging.h>
 #include <sys/time.h>
-#include <algorithm>
+#include <chrono>  // NOLINT
 #include <numeric>
 #include <sstream>
 #include <string>
 #include <vector>
-#include "paddle/fluid/framework/lod_tensor.h"
-#include "paddle/fluid/inference/api/paddle_inference_api.h"
-#include "paddle/fluid/inference/api/timer.h"
 #include "paddle/fluid/string/printf.h"
+#include "paddle_inference_api.h"
 
 namespace paddle {
 namespace inference {
 
+// Timer for timer
+class Timer {
+ public:
+  std::chrono::high_resolution_clock::time_point start;
+  std::chrono::high_resolution_clock::time_point startu;
+
+  void tic() { start = std::chrono::high_resolution_clock::now(); }
+  double toc() {
+    startu = std::chrono::high_resolution_clock::now();
+    std::chrono::duration<double> time_span =
+        std::chrono::duration_cast<std::chrono::duration<double>>(startu -
+                                                                  start);
+    double used_time_ms = static_cast<double>(time_span.count()) * 1000.0;
+    return used_time_ms;
+  }
+};
+
 static void split(const std::string &str, char sep,
                   std::vector<std::string> *pieces) {
   pieces->clear();
@@ -154,127 +169,5 @@ static void PrintTime(int batch_size, int repeat, int num_threads, int tid,
   }
 }
 
-template <typename T>
-std::string LoDTensorSummary(const framework::LoDTensor &tensor) {
-  std::stringstream ss;
-  ss << "\n---- tensor ---" << '\n';
-  ss << "lod: [";
-  for (const auto &level : tensor.lod()) {
-    ss << "[ ";
-    for (auto i : level) {
-      ss << i << ", ";
-    }
-    ss << "]";
-  }
-  ss << "]\n";
-
-  ss << "shape: [";
-  int size = 1;
-  for (int i = 0; i < tensor.dims().size(); i++) {
-    int dim = tensor.dims()[i];
-    ss << dim << ", ";
-    size *= dim;
-  }
-  ss << "]\n";
-
-  ss << "data: ";
-  for (int i = 0; i < std::min(20, size); i++) {
-    ss << tensor.data<T>()[i] << " ";
-  }
-  ss << "\n";
-
-  return ss.str();
-}
-
-static bool CompareLoD(const framework::LoD &a, const framework::LoD &b) {
-  if (a.size() != b.size()) {
-    LOG(ERROR) << string::Sprintf("lod size not match %d != %d", a.size(),
-                                  b.size());
-    return false;
-  }
-  for (size_t i = 0; i < a.size(); i++) {
-    auto &al = a[i];
-    auto &bl = b[i];
-    if (al.size() != bl.size()) {
-      LOG(ERROR) << string::Sprintf("level size %d != %d", al.size(),
-                                    bl.size());
-      return false;
-    }
-  }
-  return true;
-}
-
-static bool CompareShape(const std::vector<int64_t> &a,
-                         const std::vector<int64_t> &b) {
-  if (a.size() != b.size()) {
-    LOG(ERROR) << string::Sprintf("shape size not match %d != %d", a.size(),
-                                  b.size());
-    return false;
-  }
-  for (size_t i = 0; i < a.size(); i++) {
-    if (a[i] != b[i]) {
-      LOG(ERROR) << string::Sprintf("shape %d-th element not match %d != %d", i,
-                                    a[i], b[i]);
-      return false;
-    }
-  }
-  return true;
-}
-
-static bool CompareTensorData(const framework::LoDTensor &a,
-                              const framework::LoDTensor &b) {
-  auto a_shape = framework::vectorize(a.dims());
-  auto b_shape = framework::vectorize(b.dims());
-  size_t a_size = std::accumulate(a_shape.begin(), a_shape.end(), 1,
-                                  [](int a, int b) { return a * b; });
-  size_t b_size = std::accumulate(b_shape.begin(), b_shape.end(), 1,
-                                  [](int a, int b) { return a * b; });
-  if (a_size != b_size) {
-    LOG(ERROR) << string::Sprintf("tensor data size not match, %d != %d",
-                                  a_size, b_size);
-  }
-
-  for (size_t i = 0; i < a_size; i++) {
-    if (a.type() == typeid(float)) {
-      const auto *a_data = a.data<float>();
-      const auto *b_data = b.data<float>();
-      if (std::abs(a_data[i] - b_data[i]) > 1e-3) {
-        LOG(ERROR) << string::Sprintf(
-            "tensor data %d-th element not match, %f != %f", i, a_data[i],
-            b_data[i]);
-        return false;
-      }
-    } else if (a.type() == typeid(int64_t)) {
-      const auto *a_data = a.data<int64_t>();
-      const auto *b_data = b.data<int64_t>();
-      if (std::abs(a_data[i] - b_data[i]) > 1e-3) {
-        LOG(ERROR) << string::Sprintf(
-            "tensor data %d-th element not match, %f != %f", i, a_data[i],
-            b_data[i]);
-        return false;
-      }
-    }
-  }
-
-  return true;
-}
-
-static bool CompareTensor(const framework::LoDTensor &a,
-                          const framework::LoDTensor &b) {
-  if (!CompareLoD(a.lod(), b.lod())) {
-    return false;
-  }
-  if (!CompareShape(framework::vectorize(a.dims()),
-                    framework::vectorize(b.dims()))) {
-    return false;
-  }
-
-  if (!CompareTensorData(a, b)) {
-    return false;
-  }
-
-  return true;
-}
-
 }  // namespace inference
 }  // namespace paddle

paddle/fluid/inference/api/paddle_inference_api.h

@@ -268,9 +268,8 @@ struct AnalysisConfig : public NativeConfig {
   // NOT stable yet.
   bool use_feed_fetch_ops{true};
 
-  // NOTE this is just for internal development, please not use it.	NOT
+  // NOTE this is just for internal development, please not use it.
-  // stable
+  // NOT stable yet.
-  // yet.
   bool _use_mkldnn{false};
 };
 

paddle/fluid/inference/api/timer.h

@@ -1,39 +0,0 @@
-// Copyright (c) 2018 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 <chrono>  // NOLINT
-
-namespace paddle {
-namespace inference {
-
-// Timer for timer
-class Timer {
- public:
-  std::chrono::high_resolution_clock::time_point start;
-  std::chrono::high_resolution_clock::time_point startu;
-
-  void tic() { start = std::chrono::high_resolution_clock::now(); }
-  double toc() {
-    startu = std::chrono::high_resolution_clock::now();
-    std::chrono::duration<double> time_span =
-        std::chrono::duration_cast<std::chrono::duration<double>>(startu -
-                                                                  start);
-    double used_time_ms = static_cast<double>(time_span.count()) * 1000.0;
-    return used_time_ms;
-  }
-};
-
-}  // namespace inference
-}  // namespace paddle

paddle/fluid/inference/tests/api/anakin_rnn1_tester.cc

@@ -22,7 +22,6 @@ limitations under the License. */
 #include <vector>
 #include "paddle/fluid/inference/api/helper.h"
 #include "paddle/fluid/inference/api/paddle_inference_api.h"
-#include "paddle/fluid/inference/api/timer.h"
 #include "utils/logger/logger.h"
 
 DEFINE_string(model, "", "Directory of the inference model.");

paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc

@@ -12,7 +12,6 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/fluid/inference/api/analysis_predictor.h"
 #include "paddle/fluid/inference/tests/api/tester_helper.h"
 
 DEFINE_bool(with_precision_check, true, "turn on test");

paddle/fluid/inference/tests/api/tester_helper.h

@@ -15,6 +15,7 @@
 #pragma once
 
 #include <gtest/gtest.h>
+#include <algorithm>
 #include <string>
 #include <thread>  // NOLINT
 #include <vector>
@@ -182,5 +183,127 @@ void CompareNativeAndAnalysis(
   CompareResult(analysis_outputs, native_outputs);
 }
 
+template <typename T>
+std::string LoDTensorSummary(const framework::LoDTensor &tensor) {
+  std::stringstream ss;
+  ss << "\n---- tensor ---" << '\n';
+  ss << "lod: [";
+  for (const auto &level : tensor.lod()) {
+    ss << "[ ";
+    for (auto i : level) {
+      ss << i << ", ";
+    }
+    ss << "]";
+  }
+  ss << "]\n";
+
+  ss << "shape: [";
+  int size = 1;
+  for (int i = 0; i < tensor.dims().size(); i++) {
+    int dim = tensor.dims()[i];
+    ss << dim << ", ";
+    size *= dim;
+  }
+  ss << "]\n";
+
+  ss << "data: ";
+  for (int i = 0; i < std::min(20, size); i++) {
+    ss << tensor.data<T>()[i] << " ";
+  }
+  ss << "\n";
+
+  return ss.str();
+}
+
+static bool CompareLoD(const framework::LoD &a, const framework::LoD &b) {
+  if (a.size() != b.size()) {
+    LOG(ERROR) << string::Sprintf("lod size not match %d != %d", a.size(),
+                                  b.size());
+    return false;
+  }
+  for (size_t i = 0; i < a.size(); i++) {
+    auto &al = a[i];
+    auto &bl = b[i];
+    if (al.size() != bl.size()) {
+      LOG(ERROR) << string::Sprintf("level size %d != %d", al.size(),
+                                    bl.size());
+      return false;
+    }
+  }
+  return true;
+}
+
+static bool CompareShape(const std::vector<int64_t> &a,
+                         const std::vector<int64_t> &b) {
+  if (a.size() != b.size()) {
+    LOG(ERROR) << string::Sprintf("shape size not match %d != %d", a.size(),
+                                  b.size());
+    return false;
+  }
+  for (size_t i = 0; i < a.size(); i++) {
+    if (a[i] != b[i]) {
+      LOG(ERROR) << string::Sprintf("shape %d-th element not match %d != %d", i,
+                                    a[i], b[i]);
+      return false;
+    }
+  }
+  return true;
+}
+
+static bool CompareTensorData(const framework::LoDTensor &a,
+                              const framework::LoDTensor &b) {
+  auto a_shape = framework::vectorize(a.dims());
+  auto b_shape = framework::vectorize(b.dims());
+  size_t a_size = std::accumulate(a_shape.begin(), a_shape.end(), 1,
+                                  [](int a, int b) { return a * b; });
+  size_t b_size = std::accumulate(b_shape.begin(), b_shape.end(), 1,
+                                  [](int a, int b) { return a * b; });
+  if (a_size != b_size) {
+    LOG(ERROR) << string::Sprintf("tensor data size not match, %d != %d",
+                                  a_size, b_size);
+  }
+
+  for (size_t i = 0; i < a_size; i++) {
+    if (a.type() == typeid(float)) {
+      const auto *a_data = a.data<float>();
+      const auto *b_data = b.data<float>();
+      if (std::abs(a_data[i] - b_data[i]) > 1e-3) {
+        LOG(ERROR) << string::Sprintf(
+            "tensor data %d-th element not match, %f != %f", i, a_data[i],
+            b_data[i]);
+        return false;
+      }
+    } else if (a.type() == typeid(int64_t)) {
+      const auto *a_data = a.data<int64_t>();
+      const auto *b_data = b.data<int64_t>();
+      if (std::abs(a_data[i] - b_data[i]) > 1e-3) {
+        LOG(ERROR) << string::Sprintf(
+            "tensor data %d-th element not match, %f != %f", i, a_data[i],
+            b_data[i]);
+        return false;
+      }
+    }
+  }
+
+  return true;
+}
+
+static bool CompareTensor(const framework::LoDTensor &a,
+                          const framework::LoDTensor &b) {
+  if (!CompareLoD(a.lod(), b.lod())) {
+    return false;
+  }
+  if (!CompareShape(framework::vectorize(a.dims()),
+                    framework::vectorize(b.dims()))) {
+    return false;
+  }
+
+  if (!CompareTensorData(a, b)) {
+    return false;
+  }
+
+  return true;
+}
+
 }  // namespace inference
 }  // namespace paddle