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99 lines
3.6 KiB
99 lines
3.6 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "gflags/gflags.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/inference/tests/test_helper.h"
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DEFINE_string(dirname, "", "Directory of the inference model.");
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DEFINE_string(fp16_dirname, "", "Directory of the float16 inference model.");
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DEFINE_int32(batch_size, 1, "Batch size of input data");
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DEFINE_int32(repeat, 1, "Running the inference program repeat times");
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DEFINE_bool(skip_cpu, false, "Skip the cpu test");
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TEST(inference, image_classification) {
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if (FLAGS_dirname.empty() || FLAGS_batch_size < 1 || FLAGS_repeat < 1) {
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LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model "
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"--batch_size=1 --repeat=1";
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}
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LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl;
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std::string dirname = FLAGS_dirname;
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// 0. Call `paddle::framework::InitDevices()` initialize all the devices
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// In unittests, this is done in paddle/testing/paddle_gtest_main.cc
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const bool is_combined = false;
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std::vector<std::vector<int64_t>> feed_target_shapes =
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GetFeedTargetShapes(dirname, is_combined);
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paddle::framework::LoDTensor input;
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// Use normilized image pixels as input data,
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// which should be in the range [0.0, 1.0].
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feed_target_shapes[0][0] = FLAGS_batch_size;
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paddle::framework::DDim input_dims =
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paddle::framework::make_ddim(feed_target_shapes[0]);
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LOG(INFO) << input_dims;
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SetupTensor<float>(&input, input_dims, static_cast<float>(0),
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static_cast<float>(1));
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std::vector<paddle::framework::LoDTensor*> cpu_feeds;
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cpu_feeds.push_back(&input);
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paddle::framework::LoDTensor output1;
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if (!FLAGS_skip_cpu) {
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std::vector<paddle::framework::LoDTensor*> cpu_fetchs1;
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cpu_fetchs1.push_back(&output1);
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// Run inference on CPU
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LOG(INFO) << "--- CPU Runs: ---";
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LOG(INFO) << "Batch size is " << FLAGS_batch_size;
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TestInference<paddle::platform::CPUPlace, false, true>(
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dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, is_combined);
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LOG(INFO) << output1.dims();
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}
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#ifdef PADDLE_WITH_CUDA
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paddle::framework::LoDTensor output2;
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std::vector<paddle::framework::LoDTensor*> cpu_fetchs2;
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cpu_fetchs2.push_back(&output2);
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// Run inference on CUDA GPU
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LOG(INFO) << "--- GPU Runs: ---";
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LOG(INFO) << "Batch size is " << FLAGS_batch_size;
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TestInference<paddle::platform::CUDAPlace, false, true>(
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dirname, cpu_feeds, cpu_fetchs2, FLAGS_repeat, is_combined);
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LOG(INFO) << output2.dims();
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if (!FLAGS_skip_cpu) {
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CheckError<float>(output1, output2);
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}
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// float16 inference requires cuda GPUs with >= 5.3 compute capability
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if (!FLAGS_fp16_dirname.empty() &&
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paddle::platform::GetCUDAComputeCapability(0) >= 53) {
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paddle::framework::LoDTensor output3;
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std::vector<paddle::framework::LoDTensor*> cpu_fetchs3;
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cpu_fetchs3.push_back(&output3);
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LOG(INFO) << "--- GPU Runs in float16 mode: ---";
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LOG(INFO) << "Batch size is " << FLAGS_batch_size;
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TestInference<paddle::platform::CUDAPlace, false, true>(
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FLAGS_fp16_dirname, cpu_feeds, cpu_fetchs3, FLAGS_repeat);
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CheckError<float>(output2, output3);
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}
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#endif
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}
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