mirror of https://github.com/JDAI-CV/fast-reid.git
64 lines
2.0 KiB
C
64 lines
2.0 KiB
C
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#pragma once
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#include <map>
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#include <chrono>
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#include <memory>
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#include <vector>
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#include <fstream>
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#include <iostream>
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#include "assert.h"
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#include "NvInfer.h"
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#include "cuda_runtime_api.h"
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#include "fastrt/struct.h"
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#define CHECK(status) \
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do \
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{ \
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auto ret = (status); \
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if (ret != 0) \
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{ \
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std::cout << "Cuda failure: " << ret; \
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abort(); \
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} \
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} while (0)
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#define TRTASSERT(CONDITION) \
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do \
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{ \
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auto cond = (CONDITION); \
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if (!cond) \
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{ \
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std::cerr << "Condition failure.\n"; \
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abort(); \
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} \
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} while (0)
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using Time = std::chrono::high_resolution_clock;
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using TimePoint = std::chrono::time_point<std::chrono::high_resolution_clock>;
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template<typename T, typename... Args>
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std::unique_ptr<T> make_unique(Args&&... args) {
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return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
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}
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namespace io {
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std::vector<std::string> fileGlob(const std::string& pattern);
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}
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namespace trt {
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/*
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* Load weights from files shared with TensorRT samples.
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* TensorRT weight files have a simple space delimited format:
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* [type] [size] <data x size in hex>
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*/
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std::map<std::string, nvinfer1::Weights> loadWeights(const std::string file);
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std::ostream& operator<<(std::ostream& os, const ModelConfig& modelCfg);
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}
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namespace fastrt {
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std::ostream& operator<<(std::ostream& os, const FastreidConfig& fastreidCfg);
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}
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