Add test for int16 quantized model (#4387)

* Add test for int16 quantized model, test=develop

lite/CMakeLists.txt

@@ -40,7 +40,8 @@ endif()
 if (WITH_TESTING)
     lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "lite_naive_model.tar.gz")
     if(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
-	lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v1.tar.gz")
+	    lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v1.tar.gz")
+	    lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v1_int16.tar.gz")
         lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "mobilenet_v2_relu.tar.gz")
         lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "resnet50.tar.gz")
         lite_download_and_uncompress(${LITE_MODEL_DIR} ${LITE_URL} "inception_v4_simple.tar.gz")

lite/api/CMakeLists.txt

@@ -291,6 +291,14 @@ if(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK AND WITH_TESTING)
        set(LINK_FLAGS "-Wl,--version-script ${PADDLE_SOURCE_DIR}/lite/core/lite.map")
        set_target_properties(test_mobilenetv1 PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
     endif()
+    
+    lite_cc_test(test_mobilenetv1_int16 SRCS mobilenetv1_int16_test.cc
+       DEPS ${lite_model_test_DEPS} ${light_lib_DEPS}
+       CL_DEPS ${opencl_kernels}
+       NPU_DEPS ${npu_kernels} ${npu_bridges}
+       ARGS --cl_path=${CMAKE_SOURCE_DIR}/lite/backends/opencl
+            --model_dir=${LITE_MODEL_DIR}/mobilenet_v1_int16 SERIAL)
+    add_dependencies(test_mobilenetv1 extern_lite_download_mobilenet_v1_int16_tar_gz)
 
     lite_cc_test(test_mobilenetv2 SRCS mobilenetv2_test.cc
        DEPS ${lite_model_test_DEPS}

lite/api/mobilenetv1_int16_test.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 <gflags/gflags.h>
+#include <gtest/gtest.h>
+#include <vector>
+#include "lite/api/cxx_api.h"
+#include "lite/api/light_api.h"
+#include "lite/api/paddle_use_kernels.h"
+#include "lite/api/paddle_use_ops.h"
+#include "lite/api/paddle_use_passes.h"
+#include "lite/api/test_helper.h"
+#include "lite/core/op_registry.h"
+
+DEFINE_string(optimized_model,
+              "/data/local/tmp/int16_model",
+              "optimized_model");
+DEFINE_int32(N, 1, "input_batch");
+DEFINE_int32(C, 3, "input_channel");
+DEFINE_int32(H, 224, "input_height");
+DEFINE_int32(W, 224, "input_width");
+
+namespace paddle {
+namespace lite {
+
+void TestModel(const std::vector<Place>& valid_places,
+               const std::string& model_dir) {
+  DeviceInfo::Init();
+  DeviceInfo::Global().SetRunMode(lite_api::LITE_POWER_NO_BIND, FLAGS_threads);
+
+  LOG(INFO) << "Optimize model.";
+  lite::Predictor cxx_predictor;
+  cxx_predictor.Build(model_dir, "", "", valid_places);
+  cxx_predictor.SaveModel(FLAGS_optimized_model,
+                          paddle::lite_api::LiteModelType::kNaiveBuffer);
+
+  LOG(INFO) << "Load optimized model.";
+  lite::LightPredictor predictor(FLAGS_optimized_model + ".nb", false);
+
+  auto* input_tensor = predictor.GetInput(0);
+  input_tensor->Resize(DDim(
+      std::vector<DDim::value_type>({FLAGS_N, FLAGS_C, FLAGS_H, FLAGS_W})));
+  auto* data = input_tensor->mutable_data<float>();
+  auto item_size = FLAGS_N * FLAGS_C * FLAGS_H * FLAGS_W;
+  for (int i = 0; i < item_size; i++) {
+    data[i] = 1.;
+  }
+
+  LOG(INFO) << "Predictor run.";
+  predictor.Run();
+
+  auto* out = predictor.GetOutput(0);
+  const auto* pdata = out->data<float>();
+
+  std::vector<float> ref = {
+      0.000191383, 0.000592063, 0.000112282, 6.27426e-05, 0.000127522};
+  double eps = 1e-5;
+  for (int i = 0; i < ref.size(); ++i) {
+    EXPECT_NEAR(pdata[i], ref[i], eps);
+  }
+}
+
+TEST(MobileNetV1_Int16, test_arm) {
+  std::vector<Place> valid_places({
+      Place{TARGET(kARM), PRECISION(kFloat)},
+  });
+  std::string model_dir = FLAGS_model_dir;
+  TestModel(valid_places, model_dir);
+}
+
+}  // namespace lite
+}  // namespace paddle

lite/tools/ci_build.sh

@@ -466,7 +466,7 @@ function test_arm_android {
     echo "test name: ${test_name}"
     adb_work_dir="/data/local/tmp"
 
-    skip_list=("test_model_parser" "test_mobilenetv1" "test_mobilenetv2" "test_resnet50" "test_inceptionv4" "test_light_api" "test_apis" "test_paddle_api" "test_cxx_api" "test_gen_code" "test_mobilenetv1_int8" "test_subgraph_pass" "test_grid_sampler_image_opencl" "test_lrn_image_opencl" "test_pad2d_image_opencl" "test_transformer_with_mask_fp32_arm")
+    skip_list=("test_model_parser" "test_mobilenetv1" "test_mobilenetv2" "test_resnet50" "test_inceptionv4" "test_light_api" "test_apis" "test_paddle_api" "test_cxx_api" "test_gen_code" "test_mobilenetv1_int8" "test_subgraph_pass" "test_grid_sampler_image_opencl" "test_lrn_image_opencl" "test_pad2d_image_opencl" "test_transformer_with_mask_fp32_arm" "test_mobilenetv1_int16")
     for skip_name in ${skip_list[@]} ; do
         [[ $skip_name =~ (^|[[:space:]])$test_name($|[[:space:]]) ]] && echo "skip $test_name" && return
     done
@@ -1251,6 +1251,7 @@ function main {
                 build_test_arm_subtask_android
                 build_test_arm_subtask_model test_mobilenetv1 mobilenet_v1
                 build_test_arm_subtask_model test_mobilenetv1_int8 MobileNetV1_quant
+                build_test_arm_subtask_model test_mobilenetv1_int16 mobilenet_v1_int16
                 build_test_arm_subtask_model test_mobilenetv2 mobilenet_v2_relu
                 build_test_arm_subtask_model test_resnet50 resnet50
                 build_test_arm_subtask_model test_inceptionv4 inception_v4_simple