addd test_analyzer_mobilenet

paddle/fluid/inference/analysis/analyzer.h

@@ -66,7 +66,10 @@ class Analyzer : public OrderedRegistry<PassManager> {
   // merged in a larger fuse op. The small fusion will not break the pattern of
   // larger fusion.
   const std::vector<std::string> all_ir_passes_{{
-      // Manual update the passes here.
+// Manual update the passes here.
+#ifdef PADDLE_WITH_MKLDNN
+      "depthwise_conv_mkldnn_pass",  //
+#endif
       "attention_lstm_fuse_pass",       //
       "seqconv_eltadd_relu_fuse_pass",  //
       "embedding_fc_lstm_fuse_pass",    //
@@ -79,7 +82,6 @@ class Analyzer : public OrderedRegistry<PassManager> {
       "conv_bn_fuse_pass",              //
       "conv_eltwiseadd_bn_fuse_pass",   //
 #ifdef PADDLE_WITH_MKLDNN
-      "depthwise_conv_mkldnn_pass",             //
       "conv_bias_mkldnn_fuse_pass",             //
       "conv_relu_mkldnn_fuse_pass",             //
       "conv_elementwise_add_mkldnn_fuse_pass",  //

paddle/fluid/inference/tests/api/CMakeLists.txt

@@ -82,6 +82,14 @@ inference_analysis_api_test(test_analyzer_ocr ${OCR_INSTALL_DIR} analyzer_vis_te
 inference_analysis_api_test_with_fake_data(test_analyzer_resnet50 
   "${INFERENCE_DEMO_INSTALL_DIR}/resnet50" analyzer_resnet50_tester.cc "resnet50_model.tar.gz")
 
+# mobilenet
+set(MOBILENET_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/mobilenet")
+if (NOT EXISTS ${MOBILENET_INSTALL_DIR})
+  inference_download_and_uncompress(${MOBILENET_INSTALL_DIR} "http://paddle-inference-dist.bj.bcebos.com/tensorrt_test" "mobilenet.tar.gz")
+endif()
+inference_analysis_test(test_analyzer_mobilenet SRCS analyzer_mobilenet_tester.cc
+  EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} ARGS --infer_model=${MOBILENET_INSTALL_DIR}/mobilenet)
+
 # anakin
 if (WITH_ANAKIN AND WITH_MKL) # only needed in CI
    # anakin rnn1

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

+/* 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. */
+
+#include <fstream>
+#include <iostream>
+#include "paddle/fluid/inference/tests/api/tester_helper.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+void SetConfig(AnalysisConfig *cfg) {
+  cfg->model_dir = FLAGS_infer_model;
+  cfg->use_gpu = false;
+  cfg->device = 0;
+  cfg->enable_ir_optim = true;
+  cfg->specify_input_name = true;
+}
+
+void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
+  PADDLE_ENFORCE_EQ(FLAGS_test_all_data, 0, "Only have single batch of data.");
+
+  PaddleTensor input;
+  // channel=3, height/width=318
+  std::vector<int> shape({FLAGS_batch_size, 3, 318, 318});
+  input.shape = shape;
+  input.dtype = PaddleDType::FLOAT32;
+
+  // fill input data, for profile easily, do not use random data here.
+  size_t size = FLAGS_batch_size * 3 * 318 * 318;
+  input.data.Resize(size * sizeof(float));
+  float *input_data = static_cast<float *>(input.data.data());
+  for (size_t i = 0; i < size; i++) {
+    *(input_data + i) = static_cast<float>(i) / size;
+  }
+
+  std::vector<PaddleTensor> input_slots;
+  input_slots.assign({input});
+  (*inputs).emplace_back(input_slots);
+}
+
+// Easy for profiling independently.
+void profile(bool use_mkldnn = false) {
+  AnalysisConfig cfg;
+  SetConfig(&cfg);
+  cfg._use_mkldnn = use_mkldnn;
+  std::vector<PaddleTensor> outputs;
+
+  std::vector<std::vector<PaddleTensor>> input_slots_all;
+  SetInput(&input_slots_all);
+  TestPrediction(cfg, input_slots_all, &outputs, FLAGS_num_threads);
+
+  if (FLAGS_num_threads == 1 && !FLAGS_test_all_data) {
+    PADDLE_ENFORCE_EQ(outputs.size(), 1UL);
+    size_t size = GetSize(outputs[0]);
+    // output is a 1000-dimension feature
+    EXPECT_EQ(size, 1000 * FLAGS_batch_size);
+  }
+}
+
+TEST(Analyzer_mobilenet, profile) { profile(); }
+#ifdef PADDLE_WITH_MKLDNN
+TEST(Analyzer_mobilenet, profile_mkldnn) { profile(true /* use_mkldnn */); }
+#endif
+
+// Check the depthwise_conv status
+TEST(Analyzer_mobilenet, depthwise_conv_statis) {
+  AnalysisConfig cfg;
+  SetConfig(&cfg);
+  cfg._use_mkldnn = true;
+  int num_ops;
+  auto predictor = CreatePaddlePredictor<AnalysisConfig>(cfg);
+  auto fuse_statis = GetFuseStatis(
+      static_cast<AnalysisPredictor *>(predictor.get()), &num_ops);
+  ASSERT_TRUE(fuse_statis.count("depthwise_conv_mkldnn_pass"));
+  EXPECT_EQ(fuse_statis.at("depthwise_conv_mkldnn_pass"), 13);
+}
+
+// Compare result of NativeConfig and AnalysisConfig
+void compare(bool use_mkldnn = false) {
+  AnalysisConfig cfg;
+  SetConfig(&cfg);
+  cfg._use_mkldnn = use_mkldnn;
+
+  std::vector<std::vector<PaddleTensor>> input_slots_all;
+  SetInput(&input_slots_all);
+  CompareNativeAndAnalysis(cfg, input_slots_all);
+}
+
+TEST(Analyzer_mobilenet, compare) { compare(); }
+#ifdef PADDLE_WITH_MKLDNN
+TEST(Analyzer_mobilenet, compare_mkldnn) { compare(true /* use_mkldnn */); }
+#endif
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle