add feature/infer demo/se resnext50

paddle/contrib/inference/demo/CMakeLists.txt

@@ -14,3 +14,42 @@
 #
 
 inference_api_test(simple_on_word2vec ARGS test_word2vec)
+
+set(DEMO_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo")
+set(URL_ROOT http://paddlemodels.bj.bcebos.com/inference-vis-demos%2F)
+
+function(inference_download_test_demo TARGET)
+    if (NOT WITH_TESTING)
+        return()
+    endif()
+    set(options "")
+    set(oneValueArgs URL)
+    set(multiValueArgs SRCS)
+    cmake_parse_arguments(tests "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
+
+    set(test_dir "${DEMO_INSTALL_DIR}/${TARGET}")
+    message(STATUS "inference demo ${test_dir}")
+
+    if(NOT EXISTS "${test_dir}")
+        message(STATUS "Download ${TARGET} model from ${tests_URL}")
+        execute_process(COMMAND bash -c "mkdir -p ${test_dir}")
+        execute_process(COMMAND bash -c "cd ${test_dir}; wget -q ${tests_URL}")
+        execute_process(COMMAND bash -c "cd ${test_dir}; tar xzf *.tar.gz")
+    endif()
+
+    cc_test(${TARGET} SRCS "${tests_SRCS}"
+        DEPS paddle_inference_api paddle_fluid
+        ARGS --data=${test_dir}/data.txt
+             --modeldir=${test_dir}/model
+             --refer=${test_dir}/result.txt)
+endfunction()
+
+inference_download_test_demo(mobilenet_inference_demo
+    SRCS vis_demo.cc
+    URL ${URL_ROOT}mobilenet.tar.gz)
+inference_download_test_demo(se_resnext50_inference_demo
+    SRCS vis_demo.cc
+    URL ${URL_ROOT}se_resnext50.tar.gz)
+inference_download_test_demo(ocr_inference_demo
+    SRCS vis_demo.cc
+    URL ${URL_ROOT}ocr.tar.gz)

paddle/contrib/inference/demo/README.md

@@ -0,0 +1,36 @@
+# Infernce Demos
+
+Input data format:
+
+- Each line contains a single record
+- Each record's format is
+
+```
+<space splitted floats as data>\t<space splitted ints as shape>
+```
+
+Follow the C++ codes in `vis_demo.cc`.
+
+## MobileNet
+
+To execute the demo, simply run
+
+```sh
+./mobilenet_inference_demo --modeldir <model> --data <datafile>
+```
+
+## SE-ResNeXt-50
+
+To execute the demo, simply run
+
+```sh
+./se_resnext50_inference_demo --modeldir <model> --data <datafile>
+```
+
+## OCR
+
+To execute the demo, simply run
+
+```sh
+./ocr_inference_demo --modeldir <model> --data <datafile>
+```

paddle/contrib/inference/demo/simple_on_word2vec.cc

@@ -21,6 +21,7 @@ limitations under the License. */
 #include <memory>
 #include <thread>
 #include "paddle/contrib/inference/paddle_inference_api.h"
+
 namespace paddle {
 namespace demo {
 

paddle/contrib/inference/demo/utils.h

@@ -0,0 +1,68 @@
+// 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 <string>
+#include <vector>
+
+#include "paddle/contrib/inference/paddle_inference_api.h"
+
+namespace paddle {
+namespace demo {
+
+static void split(const std::string& str,
+                  char sep,
+                  std::vector<std::string>* pieces) {
+  pieces->clear();
+  if (str.empty()) {
+    return;
+  }
+  size_t pos = 0;
+  size_t next = str.find(sep, pos);
+  while (next != std::string::npos) {
+    pieces->push_back(str.substr(pos, next - pos));
+    pos = next + 1;
+    next = str.find(sep, pos);
+  }
+  if (!str.substr(pos).empty()) {
+    pieces->push_back(str.substr(pos));
+  }
+}
+
+/*
+ * Get a summary of a PaddleTensor content.
+ */
+static std::string SummaryTensor(const PaddleTensor& tensor) {
+  std::stringstream ss;
+  int num_elems = tensor.data.length() / PaddleDtypeSize(tensor.dtype);
+
+  ss << "data[:10]\t";
+  switch (tensor.dtype) {
+    case PaddleDType::INT64: {
+      for (int i = 0; i < std::min(num_elems, 10); i++) {
+        ss << static_cast<int64_t*>(tensor.data.data())[i] << " ";
+      }
+      break;
+    }
+    case PaddleDType::FLOAT32:
+      for (int i = 0; i < std::min(num_elems, 10); i++) {
+        ss << static_cast<float*>(tensor.data.data())[i] << " ";
+      }
+      break;
+  }
+  return ss.str();
+}
+
+}  // namespace demo
+}  // namespace paddle

paddle/contrib/inference/demo/vis_demo.cc

@@ -0,0 +1,149 @@
+/* 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. */
+
+/*
+ * This file contains demo for mobilenet, se-resnext50 and ocr.
+ */
+
+#include <gflags/gflags.h>
+#include <glog/logging.h>  // use glog instead of PADDLE_ENFORCE to avoid importing other paddle header files.
+#include <gtest/gtest.h>
+#include <fstream>
+#include <iostream>
+#include "paddle/contrib/inference/demo/utils.h"
+#include "paddle/contrib/inference/paddle_inference_api.h"
+
+namespace paddle {
+namespace demo {
+
+DEFINE_string(modeldir, "", "Directory of the inference model.");
+DEFINE_string(refer, "", "path to reference result for comparison.");
+DEFINE_string(
+    data,
+    "",
+    "path of data; each line is a record, format is "
+    "'<space splitted floats as data>\t<space splitted ints as shape'");
+
+#ifdef PADDLE_WITH_CUDA
+DECLARE_double(fraction_of_gpu_memory_to_use);
+#endif
+
+struct Record {
+  std::vector<float> data;
+  std::vector<int32_t> shape;
+};
+
+void split(const std::string& str, char sep, std::vector<std::string>* pieces);
+
+Record ProcessALine(const std::string& line) {
+  LOG(INFO) << "process a line";
+  std::vector<std::string> columns;
+  split(line, '\t', &columns);
+  CHECK_EQ(columns.size(), 2UL)
+      << "data format error, should be <data>\t<shape>";
+
+  Record record;
+  std::vector<std::string> data_strs;
+  split(columns[0], ' ', &data_strs);
+  for (auto& d : data_strs) {
+    record.data.push_back(std::stof(d));
+  }
+
+  std::vector<std::string> shape_strs;
+  split(columns[1], ' ', &shape_strs);
+  for (auto& s : shape_strs) {
+    record.shape.push_back(std::stoi(s));
+  }
+  LOG(INFO) << "data size " << record.data.size();
+  LOG(INFO) << "data shape size " << record.shape.size();
+  return record;
+}
+
+void CheckOutput(const std::string& referfile, const PaddleTensor& output) {
+  std::string line;
+  std::ifstream file(referfile);
+  std::getline(file, line);
+  auto refer = ProcessALine(line);
+  file.close();
+
+  size_t numel = output.data.length() / PaddleDtypeSize(output.dtype);
+  LOG(INFO) << "predictor output numel " << numel;
+  LOG(INFO) << "reference output numel " << refer.data.size();
+  EXPECT_EQ(numel, refer.data.size());
+  switch (output.dtype) {
+    case PaddleDType::INT64: {
+      for (size_t i = 0; i < numel; ++i) {
+        EXPECT_EQ(static_cast<int64_t*>(output.data.data())[i], refer.data[i]);
+      }
+      break;
+    }
+    case PaddleDType::FLOAT32:
+      for (size_t i = 0; i < numel; ++i) {
+        EXPECT_NEAR(
+            static_cast<float*>(output.data.data())[i], refer.data[i], 1e-3);
+      }
+      break;
+  }
+}
+
+/*
+ * Use the native fluid engine to inference the demo.
+ */
+void Main(bool use_gpu) {
+  NativeConfig config;
+  // config.model_dir = FLAGS_modeldir;
+  config.param_file = FLAGS_modeldir + "/__params__";
+  config.prog_file = FLAGS_modeldir + "/__model__";
+  config.use_gpu = use_gpu;
+  config.fraction_of_gpu_memory = 0.1;
+#ifdef PADDLE_WITH_CUDA
+  config.fraction_of_gpu_memory = FLAGS_fraction_of_gpu_memory_to_use;
+#endif
+  config.device = 0;
+
+  LOG(INFO) << "init predictor";
+  auto predictor =
+      CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config);
+
+  LOG(INFO) << "begin to process data";
+  // Just a single batch of data.
+  std::string line;
+  std::ifstream file(FLAGS_data);
+  std::getline(file, line);
+  auto record = ProcessALine(line);
+  file.close();
+
+  // Inference.
+  PaddleTensor input{
+      .name = "xx",
+      .shape = record.shape,
+      .data = PaddleBuf(record.data.data(), record.data.size() * sizeof(float)),
+      .dtype = PaddleDType::FLOAT32};
+
+  LOG(INFO) << "run executor";
+  std::vector<PaddleTensor> output;
+  predictor->Run({input}, &output);
+
+  LOG(INFO) << "output.size " << output.size();
+  auto& tensor = output.front();
+  LOG(INFO) << "output: " << SummaryTensor(tensor);
+
+  // compare with reference result
+  CheckOutput(FLAGS_refer, tensor);
+}
+
+TEST(demo, vis_demo) { Main(false /*use_gpu*/); }
+
+}  // namespace demo
+}  // namespace paddle

paddle/contrib/inference/paddle_inference_api.cc

@@ -16,6 +16,19 @@ limitations under the License. */
 
 namespace paddle {
 
+int PaddleDtypeSize(PaddleDType dtype) {
+  switch (dtype) {
+    case PaddleDType::FLOAT32:
+      return sizeof(float);
+    case PaddleDType::INT64:
+      return sizeof(int64_t);
+    default:
+      //
+      assert(false);
+      return -1;
+  }
+}
+
 PaddleBuf::PaddleBuf(PaddleBuf&& other)
     : data_(other.data_),
       length_(other.length_),
@@ -62,4 +75,4 @@ void PaddleBuf::Free() {
   }
 }
 
-}  // namespace paddle
+}  // namespace paddle

paddle/contrib/inference/paddle_inference_api.h

@@ -15,7 +15,7 @@ limitations under the License. */
 /*
  * This file contains the definition of a simple Inference API for Paddle.
  *
- * ATTENTION: It requires some C++ features, for lower version C++ or C, we
+ * ATTENTION: It requires some C++11 features, for lower version C++ or C, we
  * might release another API.
  */
 
@@ -140,4 +140,7 @@ struct AnakinConfig : public PaddlePredictor::Config {
 // Similarly, each engine kind should map to a unique predictor implementation.
 template <typename ConfigT, PaddleEngineKind engine = PaddleEngineKind::kNative>
 std::unique_ptr<PaddlePredictor> CreatePaddlePredictor(const ConfigT& config);
+
+int PaddleDtypeSize(PaddleDType dtype);
+
 }  // namespace paddle