mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-11 19:40:25 +08:00
d38aa4560c
* add poros to fastdeploy * update readme * update readme & add license for all files * update benchmark * update copyright for some files Co-authored-by: tianjinjin <tianjinjin@baidu.com>
66 lines
2.5 KiB
C++
66 lines
2.5 KiB
C++
// Copyright (c) 2022 Baidu, Inc. 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.
|
|
|
|
/**
|
|
* @file meshgrid_test.cpp
|
|
* @author wangrui39@baidu.com
|
|
* @date Monday November 27 11:36:11 CST 2021
|
|
* @brief
|
|
**/
|
|
#include <gflags/gflags.h>
|
|
#include <gtest/gtest.h>
|
|
|
|
#include "poros/converter/gpu/meshgrid.h"
|
|
#include "poros/util/test_util.h"
|
|
|
|
static void add_test_helper(const std::string& graph_IR,
|
|
baidu::mirana::poros::IConverter* converter,
|
|
std::vector<float> value1 = {1.0, 2.0, 3.0},
|
|
std::vector<float> value2 = {4.0, 5.0}){
|
|
std::vector<at::Tensor> input_data;
|
|
auto options_pyt = torch::TensorOptions().device(torch::kCUDA, 0);//.dtype(torch::kInt32);
|
|
input_data.push_back(at::tensor(value1, options_pyt));
|
|
input_data.push_back(at::tensor(value2, options_pyt));
|
|
|
|
baidu::mirana::poros::PorosOptions poros_option; // default device GPU
|
|
// 运行原图与engine获取结果
|
|
std::vector<at::Tensor> graph_output;
|
|
std::vector<at::Tensor> poros_output;
|
|
ASSERT_TRUE(baidu::mirana::poros::testutil::run_graph_and_poros(graph_IR, poros_option, converter,
|
|
input_data, graph_output, poros_output));
|
|
|
|
ASSERT_EQ(1, graph_output.size());
|
|
ASSERT_EQ(1, poros_output.size());
|
|
ASSERT_TRUE(baidu::mirana::poros::testutil::almost_equal(graph_output[0], poros_output[0], 2e-6));
|
|
}
|
|
|
|
static std::string gen_meshgrid_graph() {
|
|
std::string graph = R"IR(
|
|
graph(%x.1 : Tensor,
|
|
%y.1 : Tensor):
|
|
%10 : int = prim::Constant[value=1]()
|
|
%4 : Tensor[] = prim::ListConstruct(%x.1, %y.1)
|
|
%5 : Tensor[] = aten::meshgrid(%4)
|
|
%grid_x.1 : Tensor, %grid_y.1 : Tensor = prim::ListUnpack(%5)
|
|
%11 : Tensor = aten::add(%grid_x.1, %grid_y.1, %10)
|
|
return (%11))IR";
|
|
|
|
return graph;
|
|
}
|
|
|
|
TEST(Converters, ATenMeshgridConvertsCorrectly) {
|
|
const auto graph_IR = gen_meshgrid_graph();
|
|
baidu::mirana::poros::MeshgridConverter meshgridconverter;
|
|
add_test_helper(graph_IR, &meshgridconverter);
|
|
} |