441 lines
18 KiB
C
441 lines
18 KiB
C
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/*
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* Copyright (c) Meta Platforms, Inc. and affiliates.
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* All rights reserved.
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*
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* This source code is licensed under both the BSD-style license (found in the
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* LICENSE file in the root directory of this source tree) and the GPLv2 (found
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* in the COPYING file in the root directory of this source tree).
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* You may select, at your option, one of the above-listed licenses.
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*/
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/* **************************************
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* Compiler Warnings
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****************************************/
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#ifdef _MSC_VER
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# pragma warning(disable : 4127) /* disable: C4127: conditional expression is constant */
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#endif
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/*-*************************************
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* Includes
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***************************************/
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#include "platform.h" /* Large Files support */
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#include "util.h" /* UTIL_getFileSize, UTIL_getTotalFileSize */
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#include <stdlib.h> /* malloc, free */
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#include <string.h> /* memset */
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#include <stdio.h> /* fprintf, fopen, ftello64 */
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#include <errno.h> /* errno */
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#include "timefn.h" /* UTIL_time_t, UTIL_clockSpanMicro, UTIL_getTime */
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#include "../lib/common/debug.h" /* assert */
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#include "../lib/common/mem.h" /* read */
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#include "../lib/zstd_errors.h"
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#include "dibio.h"
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/*-*************************************
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* Constants
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***************************************/
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#define KB *(1 <<10)
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#define MB *(1 <<20)
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#define GB *(1U<<30)
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#define SAMPLESIZE_MAX (128 KB)
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#define MEMMULT 11 /* rough estimation : memory cost to analyze 1 byte of sample */
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#define COVER_MEMMULT 9 /* rough estimation : memory cost to analyze 1 byte of sample */
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#define FASTCOVER_MEMMULT 1 /* rough estimation : memory cost to analyze 1 byte of sample */
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static const size_t g_maxMemory = (sizeof(size_t) == 4) ? (2 GB - 64 MB) : ((size_t)(512 MB) << sizeof(size_t));
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#define NOISELENGTH 32
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#define MAX_SAMPLES_SIZE (2 GB) /* training dataset limited to 2GB */
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/*-*************************************
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* Console display
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***************************************/
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#define DISPLAY(...) fprintf(stderr, __VA_ARGS__)
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#define DISPLAYLEVEL(l, ...) if (displayLevel>=l) { DISPLAY(__VA_ARGS__); }
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static const U64 g_refreshRate = SEC_TO_MICRO / 6;
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static UTIL_time_t g_displayClock = UTIL_TIME_INITIALIZER;
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#define DISPLAYUPDATE(l, ...) { if (displayLevel>=l) { \
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if ((UTIL_clockSpanMicro(g_displayClock) > g_refreshRate) || (displayLevel>=4)) \
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{ g_displayClock = UTIL_getTime(); DISPLAY(__VA_ARGS__); \
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if (displayLevel>=4) fflush(stderr); } } }
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/*-*************************************
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* Exceptions
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***************************************/
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#ifndef DEBUG
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# define DEBUG 0
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#endif
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#define DEBUGOUTPUT(...) if (DEBUG) DISPLAY(__VA_ARGS__);
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#define EXM_THROW(error, ...) \
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{ \
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DEBUGOUTPUT("Error defined at %s, line %i : \n", __FILE__, __LINE__); \
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DISPLAY("Error %i : ", error); \
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DISPLAY(__VA_ARGS__); \
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DISPLAY("\n"); \
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exit(error); \
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}
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/* ********************************************************
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* Helper functions
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**********************************************************/
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#undef MIN
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#define MIN(a,b) ((a) < (b) ? (a) : (b))
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/**
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Returns the size of a file.
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If error returns -1.
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*/
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static S64 DiB_getFileSize (const char * fileName)
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{
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U64 const fileSize = UTIL_getFileSize(fileName);
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return (fileSize == UTIL_FILESIZE_UNKNOWN) ? -1 : (S64)fileSize;
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}
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/* ********************************************************
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* File related operations
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**********************************************************/
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/** DiB_loadFiles() :
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* load samples from files listed in fileNamesTable into buffer.
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* works even if buffer is too small to load all samples.
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* Also provides the size of each sample into sampleSizes table
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* which must be sized correctly, using DiB_fileStats().
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* @return : nb of samples effectively loaded into `buffer`
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* *bufferSizePtr is modified, it provides the amount data loaded within buffer.
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* sampleSizes is filled with the size of each sample.
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*/
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static int DiB_loadFiles(
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void* buffer, size_t* bufferSizePtr,
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size_t* sampleSizes, int sstSize,
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const char** fileNamesTable, int nbFiles,
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size_t targetChunkSize, int displayLevel )
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{
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char* const buff = (char*)buffer;
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size_t totalDataLoaded = 0;
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int nbSamplesLoaded = 0;
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int fileIndex = 0;
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FILE * f = NULL;
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assert(targetChunkSize <= SAMPLESIZE_MAX);
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while ( nbSamplesLoaded < sstSize && fileIndex < nbFiles ) {
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size_t fileDataLoaded;
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S64 const fileSize = DiB_getFileSize(fileNamesTable[fileIndex]);
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if (fileSize <= 0) {
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/* skip if zero-size or file error */
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++fileIndex;
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continue;
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}
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f = fopen( fileNamesTable[fileIndex], "rb");
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if (f == NULL)
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EXM_THROW(10, "zstd: dictBuilder: %s %s ", fileNamesTable[fileIndex], strerror(errno));
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DISPLAYUPDATE(2, "Loading %s... \r", fileNamesTable[fileIndex]);
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/* Load the first chunk of data from the file */
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fileDataLoaded = targetChunkSize > 0 ?
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(size_t)MIN(fileSize, (S64)targetChunkSize) :
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(size_t)MIN(fileSize, SAMPLESIZE_MAX );
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if (totalDataLoaded + fileDataLoaded > *bufferSizePtr)
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break;
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if (fread( buff+totalDataLoaded, 1, fileDataLoaded, f ) != fileDataLoaded)
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EXM_THROW(11, "Pb reading %s", fileNamesTable[fileIndex]);
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sampleSizes[nbSamplesLoaded++] = fileDataLoaded;
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totalDataLoaded += fileDataLoaded;
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/* If file-chunking is enabled, load the rest of the file as more samples */
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if (targetChunkSize > 0) {
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while( (S64)fileDataLoaded < fileSize && nbSamplesLoaded < sstSize ) {
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size_t const chunkSize = MIN((size_t)(fileSize-fileDataLoaded), targetChunkSize);
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if (totalDataLoaded + chunkSize > *bufferSizePtr) /* buffer is full */
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break;
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if (fread( buff+totalDataLoaded, 1, chunkSize, f ) != chunkSize)
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EXM_THROW(11, "Pb reading %s", fileNamesTable[fileIndex]);
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sampleSizes[nbSamplesLoaded++] = chunkSize;
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totalDataLoaded += chunkSize;
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fileDataLoaded += chunkSize;
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}
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}
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fileIndex += 1;
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fclose(f); f = NULL;
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}
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if (f != NULL)
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fclose(f);
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DISPLAYLEVEL(2, "\r%79s\r", "");
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DISPLAYLEVEL(4, "Loaded %d KB total training data, %d nb samples \n",
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(int)(totalDataLoaded / (1 KB)), nbSamplesLoaded );
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*bufferSizePtr = totalDataLoaded;
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return nbSamplesLoaded;
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}
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#define DiB_rotl32(x,r) ((x << r) | (x >> (32 - r)))
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static U32 DiB_rand(U32* src)
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{
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static const U32 prime1 = 2654435761U;
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static const U32 prime2 = 2246822519U;
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U32 rand32 = *src;
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rand32 *= prime1;
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rand32 ^= prime2;
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rand32 = DiB_rotl32(rand32, 13);
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*src = rand32;
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return rand32 >> 5;
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}
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/* DiB_shuffle() :
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* shuffle a table of file names in a semi-random way
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* It improves dictionary quality by reducing "locality" impact, so if sample set is very large,
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* it will load random elements from it, instead of just the first ones. */
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static void DiB_shuffle(const char** fileNamesTable, unsigned nbFiles) {
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U32 seed = 0xFD2FB528;
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unsigned i;
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if (nbFiles == 0)
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return;
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for (i = nbFiles - 1; i > 0; --i) {
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unsigned const j = DiB_rand(&seed) % (i + 1);
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const char* const tmp = fileNamesTable[j];
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fileNamesTable[j] = fileNamesTable[i];
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fileNamesTable[i] = tmp;
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}
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}
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/*-********************************************************
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* Dictionary training functions
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**********************************************************/
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static size_t DiB_findMaxMem(unsigned long long requiredMem)
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{
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size_t const step = 8 MB;
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void* testmem = NULL;
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requiredMem = (((requiredMem >> 23) + 1) << 23);
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requiredMem += step;
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if (requiredMem > g_maxMemory) requiredMem = g_maxMemory;
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while (!testmem) {
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testmem = malloc((size_t)requiredMem);
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requiredMem -= step;
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}
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free(testmem);
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return (size_t)requiredMem;
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}
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static void DiB_fillNoise(void* buffer, size_t length)
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{
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unsigned const prime1 = 2654435761U;
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unsigned const prime2 = 2246822519U;
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unsigned acc = prime1;
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size_t p=0;
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for (p=0; p<length; p++) {
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acc *= prime2;
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((unsigned char*)buffer)[p] = (unsigned char)(acc >> 21);
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}
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}
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static void DiB_saveDict(const char* dictFileName,
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const void* buff, size_t buffSize)
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{
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FILE* const f = fopen(dictFileName, "wb");
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if (f==NULL) EXM_THROW(3, "cannot open %s ", dictFileName);
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{ size_t const n = fwrite(buff, 1, buffSize, f);
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if (n!=buffSize) EXM_THROW(4, "%s : write error", dictFileName) }
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{ size_t const n = (size_t)fclose(f);
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if (n!=0) EXM_THROW(5, "%s : flush error", dictFileName) }
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}
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typedef struct {
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S64 totalSizeToLoad;
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int nbSamples;
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int oneSampleTooLarge;
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} fileStats;
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/*! DiB_fileStats() :
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* Given a list of files, and a chunkSize (0 == no chunk, whole files)
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* provides the amount of data to be loaded and the resulting nb of samples.
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* This is useful primarily for allocation purpose => sample buffer, and sample sizes table.
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*/
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static fileStats DiB_fileStats(const char** fileNamesTable, int nbFiles, size_t chunkSize, int displayLevel)
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{
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fileStats fs;
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int n;
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memset(&fs, 0, sizeof(fs));
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/* We assume that if chunking is requested, the chunk size is < SAMPLESIZE_MAX */
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assert( chunkSize <= SAMPLESIZE_MAX );
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for (n=0; n<nbFiles; n++) {
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S64 const fileSize = DiB_getFileSize(fileNamesTable[n]);
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/* TODO: is there a minimum sample size? What if the file is 1-byte? */
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if (fileSize == 0) {
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DISPLAYLEVEL(3, "Sample file '%s' has zero size, skipping...\n", fileNamesTable[n]);
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continue;
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}
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/* the case where we are breaking up files in sample chunks */
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if (chunkSize > 0) {
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/* TODO: is there a minimum sample size? Can we have a 1-byte sample? */
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fs.nbSamples += (int)((fileSize + chunkSize-1) / chunkSize);
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fs.totalSizeToLoad += fileSize;
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}
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else {
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/* the case where one file is one sample */
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if (fileSize > SAMPLESIZE_MAX) {
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/* flag excessively large sample files */
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fs.oneSampleTooLarge |= (fileSize > 2*SAMPLESIZE_MAX);
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/* Limit to the first SAMPLESIZE_MAX (128kB) of the file */
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DISPLAYLEVEL(3, "Sample file '%s' is too large, limiting to %d KB",
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fileNamesTable[n], SAMPLESIZE_MAX / (1 KB));
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}
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fs.nbSamples += 1;
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fs.totalSizeToLoad += MIN(fileSize, SAMPLESIZE_MAX);
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}
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}
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DISPLAYLEVEL(4, "Found training data %d files, %d KB, %d samples\n", nbFiles, (int)(fs.totalSizeToLoad / (1 KB)), fs.nbSamples);
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return fs;
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}
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int DiB_trainFromFiles(const char* dictFileName, size_t maxDictSize,
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const char** fileNamesTable, int nbFiles, size_t chunkSize,
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ZDICT_legacy_params_t* params, ZDICT_cover_params_t* coverParams,
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ZDICT_fastCover_params_t* fastCoverParams, int optimize, unsigned memLimit)
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{
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fileStats fs;
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size_t* sampleSizes; /* vector of sample sizes. Each sample can be up to SAMPLESIZE_MAX */
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int nbSamplesLoaded; /* nb of samples effectively loaded in srcBuffer */
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size_t loadedSize; /* total data loaded in srcBuffer for all samples */
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void* srcBuffer /* contiguous buffer with training data/samples */;
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void* const dictBuffer = malloc(maxDictSize);
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int result = 0;
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int const displayLevel = params ? params->zParams.notificationLevel :
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coverParams ? coverParams->zParams.notificationLevel :
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fastCoverParams ? fastCoverParams->zParams.notificationLevel : 0;
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/* Shuffle input files before we start assessing how much sample datA to load.
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The purpose of the shuffle is to pick random samples when the sample
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set is larger than what we can load in memory. */
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DISPLAYLEVEL(3, "Shuffling input files\n");
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DiB_shuffle(fileNamesTable, nbFiles);
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/* Figure out how much sample data to load with how many samples */
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fs = DiB_fileStats(fileNamesTable, nbFiles, chunkSize, displayLevel);
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{
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int const memMult = params ? MEMMULT :
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coverParams ? COVER_MEMMULT:
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FASTCOVER_MEMMULT;
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size_t const maxMem = DiB_findMaxMem(fs.totalSizeToLoad * memMult) / memMult;
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/* Limit the size of the training data to the free memory */
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/* Limit the size of the training data to 2GB */
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/* TODO: there is opportunity to stop DiB_fileStats() early when the data limit is reached */
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loadedSize = (size_t)MIN( MIN((S64)maxMem, fs.totalSizeToLoad), MAX_SAMPLES_SIZE );
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if (memLimit != 0) {
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DISPLAYLEVEL(2, "! Warning : setting manual memory limit for dictionary training data at %u MB \n",
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(unsigned)(memLimit / (1 MB)));
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loadedSize = (size_t)MIN(loadedSize, memLimit);
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}
|
||
|
|
srcBuffer = malloc(loadedSize+NOISELENGTH);
|
||
|
|
sampleSizes = (size_t*)malloc(fs.nbSamples * sizeof(size_t));
|
||
|
|
}
|
||
|
|
|
||
|
|
/* Checks */
|
||
|
|
if ((fs.nbSamples && !sampleSizes) || (!srcBuffer) || (!dictBuffer))
|
||
|
|
EXM_THROW(12, "not enough memory for DiB_trainFiles"); /* should not happen */
|
||
|
|
if (fs.oneSampleTooLarge) {
|
||
|
|
DISPLAYLEVEL(2, "! Warning : some sample(s) are very large \n");
|
||
|
|
DISPLAYLEVEL(2, "! Note that dictionary is only useful for small samples. \n");
|
||
|
|
DISPLAYLEVEL(2, "! As a consequence, only the first %u bytes of each sample are loaded \n", SAMPLESIZE_MAX);
|
||
|
|
}
|
||
|
|
if (fs.nbSamples < 5) {
|
||
|
|
DISPLAYLEVEL(2, "! Warning : nb of samples too low for proper processing ! \n");
|
||
|
|
DISPLAYLEVEL(2, "! Please provide _one file per sample_. \n");
|
||
|
|
DISPLAYLEVEL(2, "! Alternatively, split files into fixed-size blocks representative of samples, with -B# \n");
|
||
|
|
EXM_THROW(14, "nb of samples too low"); /* we now clearly forbid this case */
|
||
|
|
}
|
||
|
|
if (fs.totalSizeToLoad < (S64)maxDictSize * 8) {
|
||
|
|
DISPLAYLEVEL(2, "! Warning : data size of samples too small for target dictionary size \n");
|
||
|
|
DISPLAYLEVEL(2, "! Samples should be about 100x larger than target dictionary size \n");
|
||
|
|
}
|
||
|
|
|
||
|
|
/* init */
|
||
|
|
if ((S64)loadedSize < fs.totalSizeToLoad)
|
||
|
|
DISPLAYLEVEL(1, "Training samples set too large (%u MB); training on %u MB only...\n",
|
||
|
|
(unsigned)(fs.totalSizeToLoad / (1 MB)),
|
||
|
|
(unsigned)(loadedSize / (1 MB)));
|
||
|
|
|
||
|
|
/* Load input buffer */
|
||
|
|
nbSamplesLoaded = DiB_loadFiles(
|
||
|
|
srcBuffer, &loadedSize, sampleSizes, fs.nbSamples, fileNamesTable,
|
||
|
|
nbFiles, chunkSize, displayLevel);
|
||
|
|
|
||
|
|
{ size_t dictSize = ZSTD_error_GENERIC;
|
||
|
|
if (params) {
|
||
|
|
DiB_fillNoise((char*)srcBuffer + loadedSize, NOISELENGTH); /* guard band, for end of buffer condition */
|
||
|
|
dictSize = ZDICT_trainFromBuffer_legacy(dictBuffer, maxDictSize,
|
||
|
|
srcBuffer, sampleSizes, nbSamplesLoaded,
|
||
|
|
*params);
|
||
|
|
} else if (coverParams) {
|
||
|
|
if (optimize) {
|
||
|
|
dictSize = ZDICT_optimizeTrainFromBuffer_cover(dictBuffer, maxDictSize,
|
||
|
|
srcBuffer, sampleSizes, nbSamplesLoaded,
|
||
|
|
coverParams);
|
||
|
|
if (!ZDICT_isError(dictSize)) {
|
||
|
|
unsigned splitPercentage = (unsigned)(coverParams->splitPoint * 100);
|
||
|
|
DISPLAYLEVEL(2, "k=%u\nd=%u\nsteps=%u\nsplit=%u\n", coverParams->k, coverParams->d,
|
||
|
|
coverParams->steps, splitPercentage);
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
dictSize = ZDICT_trainFromBuffer_cover(dictBuffer, maxDictSize, srcBuffer,
|
||
|
|
sampleSizes, nbSamplesLoaded, *coverParams);
|
||
|
|
}
|
||
|
|
} else if (fastCoverParams != NULL) {
|
||
|
|
if (optimize) {
|
||
|
|
dictSize = ZDICT_optimizeTrainFromBuffer_fastCover(dictBuffer, maxDictSize,
|
||
|
|
srcBuffer, sampleSizes, nbSamplesLoaded,
|
||
|
|
fastCoverParams);
|
||
|
|
if (!ZDICT_isError(dictSize)) {
|
||
|
|
unsigned splitPercentage = (unsigned)(fastCoverParams->splitPoint * 100);
|
||
|
|
DISPLAYLEVEL(2, "k=%u\nd=%u\nf=%u\nsteps=%u\nsplit=%u\naccel=%u\n", fastCoverParams->k,
|
||
|
|
fastCoverParams->d, fastCoverParams->f, fastCoverParams->steps, splitPercentage,
|
||
|
|
fastCoverParams->accel);
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
dictSize = ZDICT_trainFromBuffer_fastCover(dictBuffer, maxDictSize, srcBuffer,
|
||
|
|
sampleSizes, nbSamplesLoaded, *fastCoverParams);
|
||
|
|
}
|
||
|
|
} else {
|
||
|
|
assert(0 /* Impossible */);
|
||
|
|
}
|
||
|
|
if (ZDICT_isError(dictSize)) {
|
||
|
|
DISPLAYLEVEL(1, "dictionary training failed : %s \n", ZDICT_getErrorName(dictSize)); /* should not happen */
|
||
|
|
result = 1;
|
||
|
|
goto _cleanup;
|
||
|
|
}
|
||
|
|
/* save dict */
|
||
|
|
DISPLAYLEVEL(2, "Save dictionary of size %u into file %s \n", (unsigned)dictSize, dictFileName);
|
||
|
|
DiB_saveDict(dictFileName, dictBuffer, dictSize);
|
||
|
|
}
|
||
|
|
|
||
|
|
/* clean up */
|
||
|
|
_cleanup:
|
||
|
|
free(srcBuffer);
|
||
|
|
free(sampleSizes);
|
||
|
|
free(dictBuffer);
|
||
|
|
return result;
|
||
|
|
}
|