chore: import upstream snapshot with attribution

test/cpp/inference/api/trt_split_converter_test.cc

@@ -0,0 +1,46 @@
+/* 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 <glog/logging.h>
+#include <gtest/gtest.h>
+
+#include "paddle/common/flags.h"
+#include "test/cpp/inference/api/trt_test_helper.h"
+
+namespace paddle {
+namespace inference {
+
+TEST(TensorRT, split_converter) {
+  std::string model_dir = FLAGS_infer_model + "/split_converter";
+  std::string opt_cache_dir = model_dir + "/_opt_cache";
+  delete_cache_files(opt_cache_dir);
+
+  AnalysisConfig config;
+  int batch_size = 4;
+  int channels = 4;
+  int height = 4;
+  int width = 4;
+  config.EnableUseGpu(100, 0);
+  config.SetModel(model_dir);
+  config.EnableTensorRtEngine(
+      1 << 20, batch_size, 1, AnalysisConfig::Precision::kInt8, false, true);
+
+  std::map<std::string, std::vector<int>> input_shape;
+  input_shape["x"] = {batch_size, channels, height, width};
+  config.SetTRTDynamicShapeInfo(input_shape, input_shape, input_shape, false);
+  auto predictor = CreatePaddlePredictor(config);
+}
+
+}  // namespace inference
+}  // namespace paddle