[cherry-pick] fluid-lite subgraph resnet50 test. test=develop test=re…

…lease/1.7 (#22224) [cherry-pick] #22191 - 添加了fluid-lite子图方式运行resnet的单测 - 修改了依赖Lite的git commit id
PaddlePaddle · Jan 13, 2020 · fedb609 · fedb609
1 parent 3acb995
commit fedb609
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diff --git a/cmake/external/lite.cmake b/cmake/external/lite.cmake
@@ -43,7 +43,7 @@ if (NOT LITE_SOURCE_DIR OR NOT LITE_BINARY_DIR)
       ${LITE_PROJECT}
       ${EXTERNAL_PROJECT_LOG_ARGS}
       GIT_REPOSITORY      "https://github.com/PaddlePaddle/Paddle-Lite.git"
-      GIT_TAG             947cda26637d46dc23f4e39d2b52e7d9a1fa6eef
+      GIT_TAG             b30dc65b264f7bc3753ba862ff4e529ea2af6665
       PREFIX              ${LITE_SOURCES_DIR}
       UPDATE_COMMAND      ""
       BUILD_COMMAND       ${LITE_BUILD_COMMAND}

diff --git a/paddle/fluid/inference/tests/api/CMakeLists.txt b/paddle/fluid/inference/tests/api/CMakeLists.txt
@@ -367,6 +367,10 @@ download_data(${LITE_MODEL_INSTALL_DIR} "mul_model_fp32.tgz")
 inference_analysis_test(lite_mul_model_test SRCS lite_mul_model_test.cc
         EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
         ARGS --infer_model=${LITE_MODEL_INSTALL_DIR})
+inference_analysis_test(lite_resnet50_test SRCS lite_resnet50_test.cc
+        EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
+        ARGS --infer_model=${RESNET50_MODEL_DIR})
+
 inference_analysis_test(test_analyzer_capi SRCS analyzer_capi_tester.cc
             EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} paddle_fluid_c
             ARGS --infer_model=${RESNET50_MODEL_DIR}/model)

diff --git a/paddle/fluid/inference/tests/api/lite_resnet50_test.cc b/paddle/fluid/inference/tests/api/lite_resnet50_test.cc
@@ -0,0 +1,72 @@
+/* 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 <gflags/gflags.h>
+#include <glog/logging.h>
+#include <gtest/gtest.h>
+#include <cmath>
+
+#include "paddle/fluid/inference/tests/api/tester_helper.h"
+
+namespace paddle {
+namespace inference {
+
+TEST(AnalysisPredictor, use_gpu) {
+  std::string model_dir = FLAGS_infer_model + "/" + "model";
+  AnalysisConfig config;
+  config.EnableUseGpu(100, 0);
+  config.SetModel(model_dir + "/model", model_dir + "/params");
+  config.EnableLiteEngine(paddle::AnalysisConfig::Precision::kFloat32);
+
+  std::vector<PaddleTensor> inputs;
+  auto predictor = CreatePaddlePredictor(config);
+  const int batch = 1;
+  const int channel = 3;
+  const int height = 318;
+  const int width = 318;
+  const int input_num = batch * channel * height * width;
+  std::vector<float> input(input_num, 1);
+
+  PaddleTensor in;
+  in.shape = {1, 3, 318, 318};
+  in.data =
+      PaddleBuf(static_cast<void*>(input.data()), input_num * sizeof(float));
+  in.dtype = PaddleDType::FLOAT32;
+  inputs.emplace_back(in);
+
+  std::vector<PaddleTensor> outputs;
+  ASSERT_TRUE(predictor->Run(inputs, &outputs));
+
+  const std::vector<float> truth_values = {
+      127.780396, 738.16656,  1013.2264,  -438.17206, 366.4022,   927.66187,
+      736.2241,   -633.68567, -329.92737, -430.15637, -633.0639,  -146.54858,
+      -1324.2804, -1349.3661, -242.67671, 117.44864,  -801.7251,  -391.51495,
+      -404.8202,  454.16132,  515.48206,  -133.03114, 69.293076,  590.09753,
+      -1434.6917, -1070.8903, 307.0744,   400.52573,  -316.12177, -587.1265,
+      -161.05742, 800.3663,   -96.47157,  748.708,    868.17645,  -447.9403,
+      112.73656,  1127.1992,  47.43518,   677.7219,   593.1881,   -336.4011,
+      551.3634,   397.82474,  78.39835,   -715.4006,  405.96988,  404.25684,
+      246.01978,  -8.430191,  131.36617,  -648.0528};
+
+  const size_t expected_size = 1;
+  EXPECT_EQ(outputs.size(), expected_size);
+  float* data_o = static_cast<float*>(outputs[0].data.data());
+  for (size_t j = 0; j < outputs[0].data.length() / sizeof(float); j += 10) {
+    EXPECT_NEAR((data_o[j] - truth_values[j / 10]) / truth_values[j / 10], 0.,
+                10e-5);
+  }
+}
+
+}  // namespace inference
+}  // namespace paddle