standalone code

#ifndef BATCH_STREAM_PPM_H

#define BATCH_STREAM_PPM_H

#include <vector>

#include <assert.h>

#include <algorithm>

#include <iomanip>

#include <fstream>

#include "NvInfer.h"

#include "common.h"

std::string locateFile(const std::string& input);

static constexpr int INPUT_C = 3;

static constexpr int INPUT_H = 300;

static constexpr int INPUT_W = 300;

extern const char* INPUT_BLOB_NAME;

class BatchStream

{

public:

	BatchStream(int batchSize, int maxBatches) : mBatchSize(batchSize), mMaxBatches(maxBatches)

	{

		mDims = nvinfer1::DimsNCHW{batchSize, 3, 300, 300 };

		mImageSize = mDims.c() * mDims.h() * mDims.w();

		mBatch.resize(mBatchSize * mImageSize, 0);

		mLabels.resize(mBatchSize, 0);

		mFileBatch.resize(mDims.n() * mImageSize, 0);

		mFileLabels.resize(mDims.n(), 0);

		reset(0);

	}

	void reset(int firstBatch)

	{

		mBatchCount = 0;

		mFileCount = 0;

		mFileBatchPos = mDims.n();

		skip(firstBatch);

	}

	bool next()

	{

		if (mBatchCount == mMaxBatches)

			return false;

		for (int csize = 1, batchPos = 0; batchPos < mBatchSize; batchPos += csize, mFileBatchPos += csize)

		{

			assert(mFileBatchPos > 0 && mFileBatchPos <= mDims.n());

			if (mFileBatchPos == mDims.n() && !update())

				return false;

			// copy the smaller of: elements left to fulfill the request, or elements left in the file buffer.

			csize = std::min(mBatchSize - batchPos, mDims.n() - mFileBatchPos);

			std::copy_n(getFileBatch() + mFileBatchPos * mImageSize, csize * mImageSize, getBatch() + batchPos * mImageSize);

		}

		mBatchCount++;

		return true;

	}

	void skip(int skipCount)

	{

		if (mBatchSize >= mDims.n() && mBatchSize % mDims.n() == 0 && mFileBatchPos == mDims.n())

		{

			mFileCount += skipCount * mBatchSize / mDims.n();

			return;

		}

		int x = mBatchCount;

		for (int i = 0; i < skipCount; i++)

			next();

		mBatchCount = x;

	}

	float *getBatch() { return mBatch.data(); }

	float *getLabels() { return mLabels.data(); }

	int getBatchesRead() const { return mBatchCount; }

	int getBatchSize() const { return mBatchSize; }

	nvinfer1::DimsNCHW getDims() const { return mDims; }

private:

	float* getFileBatch() { return mFileBatch.data(); }

	float* getFileLabels() { return mFileLabels.data(); }

	bool update()

	{

        std::vector<std::string> fNames;

	    std::ifstream file(locateFile("list.txt"));

        if(file)

        {

            std::cout  << "Batch #" << mFileCount << "\n";

            file.seekg(mCurPos);

        }

        for(int i = 1; i <= mBatchSize; i++)

        {

            std::string sName;

            std::getline(file, sName);

            sName = sName + ".ppm";

            std::cout << "Calibrating with file " << sName << std::endl;

            fNames.emplace_back(sName);

        }

        mCurPos = file.tellg();

        mFileCount++;

        std::vector<samplesCommon::PPM<INPUT_C, INPUT_H, INPUT_W>> ppms(fNames.size());

        for (uint32_t i = 0; i < fNames.size(); ++i)

        {

            readPPMFile(locateFile(fNames[i]), ppms[i]);

        }

        std::vector<float> data(samplesCommon::volume(mDims));

        long int volChl = mDims.h() * mDims.w();

        for (int i = 0, volImg = mDims.c() * mDims.h() * mDims.w(); i < mBatchSize; ++i)

        {

            for (int c = 0; c < mDims.c(); ++c)

            {

                for (int j = 0; j < volChl; ++j)

                {

                    data[i * volImg + c * volChl + j] = (2.0 / 255.0) * float(ppms[i].buffer[j * mDims.c() + c]) - 1.0;

                }

            }

        }

        std::copy_n(data.data(), mDims.n() * mImageSize, getFileBatch());

		mFileBatchPos = 0;

		return true;

	}

	int mBatchSize{0};

	int mMaxBatches{0};

	int mBatchCount{0};

	int mFileCount{0}, mFileBatchPos{0};

	int mImageSize{0};

    int mCurPos{0};

	nvinfer1::DimsNCHW mDims;

	std::vector<float> mBatch;

	std::vector<float> mLabels;

	std::vector<float> mFileBatch;

	std::vector<float> mFileLabels;

};

class Int8EntropyCalibrator : public nvinfer1::IInt8EntropyCalibrator

{

public:

    Int8EntropyCalibrator(BatchStream& stream, int firstBatch, std::string calibrationTableName, bool readCache = true)

        : mStream(stream),

        mCalibrationTableName(std::move(calibrationTableName)),

        mReadCache(readCache)

    {

    	nvinfer1::DimsNCHW dims = mStream.getDims();

        mInputCount = samplesCommon::volume(dims);

        CHECK_TRT(cudaMalloc(&mDeviceInput, mInputCount * sizeof(float)));

        mStream.reset(firstBatch);

    }

    virtual ~Int8EntropyCalibrator()

    {

        CHECK_TRT(cudaFree(mDeviceInput));

    }

    int getBatchSize() const override { return mStream.getBatchSize(); }

    bool getBatch(void* bindings[], const char* names[], int nbBindings) override

    {

        if (!mStream.next())

            return false;

        CHECK_TRT(cudaMemcpy(mDeviceInput, mStream.getBatch(), mInputCount * sizeof(float), cudaMemcpyHostToDevice));

        assert(!strcmp(names[0], INPUT_BLOB_NAME));

        bindings[0] = mDeviceInput;

        return true;

    }

    const void* readCalibrationCache(size_t& length) override

    {

        mCalibrationCache.clear();

        std::ifstream input(mCalibrationTableName, std::ios::binary);

        input >> std::noskipws;

        if (mReadCache && input.good())

            std::copy(std::istream_iterator<char>(input), std::istream_iterator<char>(), std::back_inserter(mCalibrationCache));

        length = mCalibrationCache.size();

        return length ? mCalibrationCache.data() : nullptr;

    }

    void writeCalibrationCache(const void* cache, size_t length) override

    {

        std::ofstream output(mCalibrationTableName, std::ios::binary);

        output.write(reinterpret_cast<const char*>(cache), length);

    }

private:

    BatchStream mStream;

    std::string mCalibrationTableName;

    bool mReadCache{true};

    size_t mInputCount;

    void* mDeviceInput{nullptr};

    std::vector<char> mCalibrationCache;

};

#endif

cmake_minimum_required(VERSION 3.16)

set(ENV{CUDACXX} /usr/local/cuda/bin/nvcc)

project(tf_detector_example LANGUAGES CXX CUDA)

project(tf-gpu-feed LANGUAGES CXX CUDA)

cmake_policy(SET CMP0074 OLD)

set(CMAKE_CXX_STANDARD 11)

# CUDA for cudacodec ops

set(CUDACXX /usr/local/cuda/bin/nvcc)

find_package(CUDA 9.0 REQUIRED)

set(SOURCE_FILES

    main.cpp

    utils.cpp 

    utils.h 

    dynlink_nvcuvid.cpp

    infer_with_trt.cpp

    inference_base.cpp 

    inference_tf.cpp

    channel_first.cu

    array.cu

    )

# Tensorflow directories and libraries

set(TENSORFLOW_LIBS libtensorflow_cc.so libtensorflow_framework.so)

set(MYHOME $ENV{HOME})

message("-- Home set to: " ${MYHOME})

link_directories("/usr/local/tensorflow/lib")

add_executable(tf_detector_example ${SOURCE_FILES})

set_target_properties(tf_detector_example PROPERTIES CUDA_SEPARABLE_COMPILATION ON)

# OpenCV libs

find_package(OpenCV REQUIRED)

add_executable(tf-gpu-feed ${SOURCE_FILES})

set_target_properties(tf-gpu-feed PROPERTIES CUDA_SEPARABLE_COMPILATION ON)

include_directories(${OpenCV_INCLUDE_DIRS} ${CUDA_INCLUDE_DIRS})

# ==================== PATHS TO SPECIFY! ==================== #

include_directories(${CUDA_INCLUDE_DIRS})

# TensorFlow headers

include_directories("/usr/local/tensorflow/include/tensorflow/")

include_directories("/usr/local/tensorflow/include/third-party/")

include_directories("/usr/local/tensorflow/include/")

# IMPORTANT: Protobuf includes. Depends on the anaconda path

# This is Azure DLVM (not sure if DSVM is the same)

#include_directories("/data/anaconda/envs/py36/lib/python3.6/site-packages/tensorflow/include/")

# This is a standard install of Anaconda with p36 environment

#include_directories("${MYHOME}/anaconda3/envs/py36/lib/python3.6/site-packages/tensorflow/include/")

target_link_libraries(tf_detector_example

target_link_libraries(tf-gpu-feed

    ${CUDA_LIBRARIES}

    cuda

    cublas

    nvinfer_plugin

    nvonnxparser

    ${CMAKE_DL_LIBS}

    ${OpenCV_LIBS} 

    ${TENSORFLOW_LIBS})

1

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FeatureExtractor/InceptionV2/InceptionV2/Conv2d_2c_3x3/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4e/Branch_2/Conv2d_0a_1x1/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/MaxPool_2a_3x3/MaxPool: 3d418f1e

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GridAnchor_1: 3a500341

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FeatureExtractor/InceptionV2/InceptionV2/Mixed_4e/Branch_1/Conv2d_0b_3x3/Relu6: 3d3ceddc

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FeatureExtractor/InceptionV2/InceptionV2/Mixed_5a/Branch_1/Conv2d_1a_3x3/Relu6: 3d418f1e

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FeatureExtractor/InceptionV2/InceptionV2/Mixed_3b/Branch_2/Conv2d_0b_3x3/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4d/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

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FeatureExtractor/InceptionV2/InceptionV2/Mixed_4b/Branch_1/Conv2d_0b_3x3/Relu6: 3d418f1e

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FeatureExtractor/InceptionV2/InceptionV2/Mixed_5b/Branch_3/Conv2d_0b_1x1/Relu6: 3d4af27d

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GridAnchor_4: 3c3aa18a

(Unnamed ITensor* 360): 3d88c0ec

(Unnamed ITensor* 25): 3d418f1e

(Unnamed ITensor* 288): 3d6b9ef7

(Unnamed ITensor* 226): 3d418f1e

(Unnamed ITensor* 456): 3d418f1e

(Unnamed ITensor* 46): 3d86ba82

BoxPredictor_0/BoxEncodingPredictor/BiasAdd: 3df34968

(Unnamed ITensor* 232): 3ddb36a3

(Unnamed ITensor* 521): 3cb42ac7

GridAnchor_3 copy: 3c348982

(Unnamed ITensor* 296): 3d418f1e

BoxPredictor_0/ClassPredictor/BiasAdd: 3e13296c

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4b/Branch_2/Conv2d_0a_1x1/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_3b/Branch_3/Conv2d_0b_1x1/Relu6: 3d2dcb21

(Unnamed ITensor* 202): 3d87a00a

FeatureExtractor/InceptionV2/InceptionV2/Mixed_3c/Branch_2/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 269): 3d418f1e

GridAnchor_3: 3c348982

(Unnamed ITensor* 218): 3d418f1e

(Unnamed ITensor* 203): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4c/Branch_2/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 486): 3d418f1e

(Unnamed ITensor* 268): 3d0e4f64

Squeeze_5: 3cdbc092

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4b/Branch_1/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 254): 3d418f1e

(Unnamed ITensor* 182): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4d/Branch_3/AvgPool_0a_3x3/AvgPool: 3cb90e57

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4b/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 175): 3d418f1e

(Unnamed ITensor* 98): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_3b/Branch_2/Conv2d_0c_3x3/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4e/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4e/Branch_3/AvgPool_0a_3x3/AvgPool: 3d04ebdf

(Unnamed ITensor* 354): 3d418f1e

(Unnamed ITensor* 181): 3d8ef349

(Unnamed ITensor* 353): 3d3ce1d6

(Unnamed ITensor* 174): 3d5b5745

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5a/Branch_1/Conv2d_0b_3x3/Relu6: 3d418f1e

GridAnchor_1 copy: 3a500341

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5c/Branch_3/Conv2d_0b_1x1/Relu6: 3cb42ac7

(Unnamed ITensor* 149): 3d869442

(Unnamed ITensor* 68): 3d418f1e

(Unnamed ITensor* 17): 3d9d3367

(Unnamed ITensor* 404): 3d9d92ab

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4e/Branch_2/Conv2d_0b_3x3/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_3b/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 309): 3d8ac690

BoxPredictor_1/BoxEncodingPredictor/BiasAdd: 3d2f0384

(Unnamed ITensor* 60): 3d74b08e

(Unnamed ITensor* 189): 3d418f1e

(Unnamed ITensor* 97): 3d3f7d2c

(Unnamed ITensor* 53): 3d7e3945

(Unnamed ITensor* 8): 3e350553

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5b/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

GridAnchor_5: 3c2b37e3

(Unnamed ITensor* 76): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_3c/Branch_2/Conv2d_0b_3x3/Relu6: 3d418f1e

(Unnamed ITensor* 522): 3d418f1e

(Unnamed ITensor* 39): 3da0973e

(Unnamed ITensor* 127): 3d418f1e

(Unnamed ITensor* 54): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4b/Branch_2/Conv2d_0b_3x3/Relu6: 3d418f1e

(Unnamed ITensor* 576): 3d418f1e

(Unnamed ITensor* 332): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Conv2d_2b_1x1/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_3b/Branch_1/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 47): 3d418f1e

(Unnamed ITensor* 40): 3d418f1e

(Unnamed ITensor* 246): 3d7bd2d9

FeatureExtractor/InceptionV2/InceptionV2/Conv2d_1a_7x7/Relu6: 3d418f1e

(Unnamed ITensor* 398): 3d418f1e

(Unnamed ITensor* 383): 3d418f1e

(Unnamed ITensor* 427): 3d541a3f

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5a/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

(Unnamed ITensor* 397): 3d523857

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5a/Branch_0/Conv2d_1a_3x3/Relu6: 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5c/Branch_0/Conv2d_0a_1x1/Relu6: 3d333265

(Unnamed ITensor* 442): 3d418f1e

(Unnamed ITensor* 470): 3d71a2ed

(Unnamed ITensor* 499): 3d2d4927

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5b/Branch_2/Conv2d_0c_3x3/Relu6: 3d3d75f1

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5c/Branch_1/Conv2d_0a_1x1/Relu6: 3d1d4f1e

(Unnamed ITensor* 434): 3d439787

(Unnamed ITensor* 629): 3d418f1e

(Unnamed ITensor* 506): 3d74b7dd

(Unnamed ITensor* 428): 3d418f1e

FeatureExtractor/InceptionV2/InceptionV2/Mixed_5c/Branch_2/Conv2d_0c_3x3/Relu6: 3d418f1e

GridAnchor_2: 3c2c4ae8

FeatureExtractor/InceptionV2/InceptionV2/Mixed_4a/Branch_0/Conv2d_0a_1x1/Relu6: 3d418f1e

NMS: 3da1a245

GridAnchor copy: 3a4f5b62

FeatureExtractor/InceptionV2/Mixed_5c_1_Conv2d_4_1x1_128/Relu6: 3d418f1e

MIT License

Copyright (c) 2019 Boris

Permission is hereby granted, free of charge, to any person obtaining a copy

of this software and associated documentation files (the "Software"), to deal

in the Software without restriction, including without limitation the rights

to use, copy, modify, merge, publish, distribute, sublicense, and/or sell

copies of the Software, and to permit persons to whom the Software is

furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all

copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR

IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,

FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE

AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER

LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,

OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE

SOFTWARE.

# tensorflow-feed-from-gpu

Simple TF test

## Setup in Eclipse

From **Eclipse (2019-12)**:

* File > Open Projects from File System...

* Directory... > navigate to project's root > Finish

Tried importing a few times - indexer does not work sometimes.

# Run

```

mkdir build

cd build

cmake ..

./tf-gpu-feed

```

 No newline at end of file