mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-28 18:51:58 +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>
85 lines
3.5 KiB
C++
85 lines
3.5 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 topk_test.cpp
|
|
* @author tianshaoqing@baidu.com
|
|
* @date Wed Sep 27 11:24:21 CST 2021
|
|
* @brief
|
|
**/
|
|
#include <gflags/gflags.h>
|
|
#include <gtest/gtest.h>
|
|
|
|
#include "poros/converter/gpu/topk.h"
|
|
#include "poros/util/test_util.h"
|
|
|
|
static void topk_test_helper(const std::string& graph_IR,
|
|
std::vector<int64_t> shape) {
|
|
std::vector<at::Tensor> input_data;
|
|
input_data.push_back(at::randn(shape, {at::kCUDA}));
|
|
baidu::mirana::poros::PorosOptions poros_option; // default device GPU
|
|
baidu::mirana::poros::TopkConverter topkconverter;
|
|
|
|
// 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, &topkconverter,
|
|
input_data, graph_output, poros_output));
|
|
|
|
ASSERT_EQ(2, graph_output.size());
|
|
ASSERT_EQ(2, poros_output.size());
|
|
|
|
// ASSERT_TRUE(baidu::mirana::poros::testutil::almostEqual(graph_output[0], poros_output[0], 2e-6));
|
|
ASSERT_TRUE(graph_output[0].equal(poros_output[0]));
|
|
ASSERT_TRUE(graph_output[1].equal(poros_output[1]));
|
|
}
|
|
static std::string gen_topk_graph(const std::string& k,
|
|
const std::string& dim,
|
|
const std::string& largest,
|
|
const std::string& sorted) {
|
|
return R"IR(
|
|
graph(%0 : Tensor):
|
|
%1 : int = prim::Constant[value=)IR" + k + R"IR(]()
|
|
%2 : int = prim::Constant[value=)IR" + dim + R"IR(]()
|
|
%3 : bool = prim::Constant[value=)IR" + largest + R"IR(]()
|
|
%4 : bool = prim::Constant[value=)IR" + sorted + R"IR(]()
|
|
%5 : Tensor, %6 : Tensor = aten::topk(%0, %1, %2, %3, %4)
|
|
return (%5, %6))IR";
|
|
}
|
|
|
|
TEST(Converters, ATenTopkConvertsCorrectly) {
|
|
// aten::topk(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
|
|
const auto graph_IR = gen_topk_graph("10", "0", "1", "1");
|
|
topk_test_helper(graph_IR, {20, 10});
|
|
}
|
|
|
|
TEST(Converters, ATenTopkDimConvertsCorrectly) {
|
|
// aten::topk(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
|
|
const auto graph_IR = gen_topk_graph("5", "1", "1", "1");
|
|
topk_test_helper(graph_IR, {20, 10});
|
|
}
|
|
|
|
TEST(Converters, ATenTopkDimNegtiveConvertsCorrectly) {
|
|
// aten::topk(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
|
|
const auto graph_IR = gen_topk_graph("5", "-1", "1", "1");
|
|
topk_test_helper(graph_IR, {20, 10});
|
|
}
|
|
|
|
TEST(Converters, ATenTopklargestConvertsCorrectly) {
|
|
// aten::topk(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True) -> (Tensor values, Tensor indices)
|
|
const auto graph_IR = gen_topk_graph("10", "0", "0", "1");
|
|
topk_test_helper(graph_IR, {20, 10});
|
|
}
|
|
|
|
// sorted argument is not used in TensorRT for aten::topk
|