FreeBSD/Linux Kernel Cross Reference
sys/contrib/zstd/lib/zdict.h

     /*
      * Copyright (c) Yann Collet, Facebook, Inc.
      * All rights reserved.
      *
      * This source code is licensed under both the BSD-style license (found in the
      * LICENSE file in the root directory of this source tree) and the GPLv2 (found
      * in the COPYING file in the root directory of this source tree).
      * You may select, at your option, one of the above-listed licenses.
      */
    
    #ifndef DICTBUILDER_H_001
    #define DICTBUILDER_H_001
    
    #if defined (__cplusplus)
    extern "C" {
    #endif
    
    
    /*======  Dependencies  ======*/
    #include <stddef.h>  /* size_t */
    
    
    /* =====   ZDICTLIB_API : control library symbols visibility   ===== */
    #ifndef ZDICTLIB_VISIBILITY
    #  if defined(__GNUC__) && (__GNUC__ >= 4)
    #    define ZDICTLIB_VISIBILITY __attribute__ ((visibility ("default")))
    #  else
    #    define ZDICTLIB_VISIBILITY
    #  endif
    #endif
    #if defined(ZSTD_DLL_EXPORT) && (ZSTD_DLL_EXPORT==1)
    #  define ZDICTLIB_API __declspec(dllexport) ZDICTLIB_VISIBILITY
    #elif defined(ZSTD_DLL_IMPORT) && (ZSTD_DLL_IMPORT==1)
    #  define ZDICTLIB_API __declspec(dllimport) ZDICTLIB_VISIBILITY /* It isn't required but allows to generate better code, saving a function pointer load from the IAT and an indirect jump.*/
    #else
    #  define ZDICTLIB_API ZDICTLIB_VISIBILITY
    #endif
    
    /*******************************************************************************
     * Zstd dictionary builder
     *
     * FAQ
     * ===
     * Why should I use a dictionary?
     * ------------------------------
     *
     * Zstd can use dictionaries to improve compression ratio of small data.
     * Traditionally small files don't compress well because there is very little
     * repetition in a single sample, since it is small. But, if you are compressing
     * many similar files, like a bunch of JSON records that share the same
     * structure, you can train a dictionary on ahead of time on some samples of
     * these files. Then, zstd can use the dictionary to find repetitions that are
     * present across samples. This can vastly improve compression ratio.
     *
     * When is a dictionary useful?
     * ----------------------------
     *
     * Dictionaries are useful when compressing many small files that are similar.
     * The larger a file is, the less benefit a dictionary will have. Generally,
     * we don't expect dictionary compression to be effective past 100KB. And the
     * smaller a file is, the more we would expect the dictionary to help.
     *
     * How do I use a dictionary?
     * --------------------------
     *
     * Simply pass the dictionary to the zstd compressor with
     * `ZSTD_CCtx_loadDictionary()`. The same dictionary must then be passed to
     * the decompressor, using `ZSTD_DCtx_loadDictionary()`. There are other
     * more advanced functions that allow selecting some options, see zstd.h for
     * complete documentation.
     *
     * What is a zstd dictionary?
     * --------------------------
     *
     * A zstd dictionary has two pieces: Its header, and its content. The header
     * contains a magic number, the dictionary ID, and entropy tables. These
     * entropy tables allow zstd to save on header costs in the compressed file,
     * which really matters for small data. The content is just bytes, which are
     * repeated content that is common across many samples.
     *
     * What is a raw content dictionary?
     * ---------------------------------
     *
     * A raw content dictionary is just bytes. It doesn't have a zstd dictionary
     * header, a dictionary ID, or entropy tables. Any buffer is a valid raw
     * content dictionary.
     *
     * How do I train a dictionary?
     * ----------------------------
     *
     * Gather samples from your use case. These samples should be similar to each
     * other. If you have several use cases, you could try to train one dictionary
     * per use case.
     *
     * Pass those samples to `ZDICT_trainFromBuffer()` and that will train your
     * dictionary. There are a few advanced versions of this function, but this
     * is a great starting point. If you want to further tune your dictionary
     * you could try `ZDICT_optimizeTrainFromBuffer_cover()`. If that is too slow
     * you can try `ZDICT_optimizeTrainFromBuffer_fastCover()`.
    *
    * If the dictionary training function fails, that is likely because you
    * either passed too few samples, or a dictionary would not be effective
    * for your data. Look at the messages that the dictionary trainer printed,
    * if it doesn't say too few samples, then a dictionary would not be effective.
    *
    * How large should my dictionary be?
    * ----------------------------------
    *
    * A reasonable dictionary size, the `dictBufferCapacity`, is about 100KB.
    * The zstd CLI defaults to a 110KB dictionary. You likely don't need a
    * dictionary larger than that. But, most use cases can get away with a
    * smaller dictionary. The advanced dictionary builders can automatically
    * shrink the dictionary for you, and select a the smallest size that
    * doesn't hurt compression ratio too much. See the `shrinkDict` parameter.
    * A smaller dictionary can save memory, and potentially speed up
    * compression.
    *
    * How many samples should I provide to the dictionary builder?
    * ------------------------------------------------------------
    *
    * We generally recommend passing ~100x the size of the dictionary
    * in samples. A few thousand should suffice. Having too few samples
    * can hurt the dictionaries effectiveness. Having more samples will
    * only improve the dictionaries effectiveness. But having too many
    * samples can slow down the dictionary builder.
    *
    * How do I determine if a dictionary will be effective?
    * -----------------------------------------------------
    *
    * Simply train a dictionary and try it out. You can use zstd's built in
    * benchmarking tool to test the dictionary effectiveness.
    *
    *   # Benchmark levels 1-3 without a dictionary
    *   zstd -b1e3 -r /path/to/my/files
    *   # Benchmark levels 1-3 with a dictionary
    *   zstd -b1e3 -r /path/to/my/files -D /path/to/my/dictionary
    *
    * When should I retrain a dictionary?
    * -----------------------------------
    *
    * You should retrain a dictionary when its effectiveness drops. Dictionary
    * effectiveness drops as the data you are compressing changes. Generally, we do
    * expect dictionaries to "decay" over time, as your data changes, but the rate
    * at which they decay depends on your use case. Internally, we regularly
    * retrain dictionaries, and if the new dictionary performs significantly
    * better than the old dictionary, we will ship the new dictionary.
    *
    * I have a raw content dictionary, how do I turn it into a zstd dictionary?
    * -------------------------------------------------------------------------
    *
    * If you have a raw content dictionary, e.g. by manually constructing it, or
    * using a third-party dictionary builder, you can turn it into a zstd
    * dictionary by using `ZDICT_finalizeDictionary()`. You'll also have to
    * provide some samples of the data. It will add the zstd header to the
    * raw content, which contains a dictionary ID and entropy tables, which
    * will improve compression ratio, and allow zstd to write the dictionary ID
    * into the frame, if you so choose.
    *
    * Do I have to use zstd's dictionary builder?
    * -------------------------------------------
    *
    * No! You can construct dictionary content however you please, it is just
    * bytes. It will always be valid as a raw content dictionary. If you want
    * a zstd dictionary, which can improve compression ratio, use
    * `ZDICT_finalizeDictionary()`.
    *
    * What is the attack surface of a zstd dictionary?
    * ------------------------------------------------
    *
    * Zstd is heavily fuzz tested, including loading fuzzed dictionaries, so
    * zstd should never crash, or access out-of-bounds memory no matter what
    * the dictionary is. However, if an attacker can control the dictionary
    * during decompression, they can cause zstd to generate arbitrary bytes,
    * just like if they controlled the compressed data.
    *
    ******************************************************************************/
   
   
   /*! ZDICT_trainFromBuffer():
    *  Train a dictionary from an array of samples.
    *  Redirect towards ZDICT_optimizeTrainFromBuffer_fastCover() single-threaded, with d=8, steps=4,
    *  f=20, and accel=1.
    *  Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
    *  supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
    *  The resulting dictionary will be saved into `dictBuffer`.
    * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
    *          or an error code, which can be tested with ZDICT_isError().
    *  Note:  Dictionary training will fail if there are not enough samples to construct a
    *         dictionary, or if most of the samples are too small (< 8 bytes being the lower limit).
    *         If dictionary training fails, you should use zstd without a dictionary, as the dictionary
    *         would've been ineffective anyways. If you believe your samples would benefit from a dictionary
    *         please open an issue with details, and we can look into it.
    *  Note: ZDICT_trainFromBuffer()'s memory usage is about 6 MB.
    *  Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
    *        It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
    *        In general, it's recommended to provide a few thousands samples, though this can vary a lot.
    *        It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
    */
   ZDICTLIB_API size_t ZDICT_trainFromBuffer(void* dictBuffer, size_t dictBufferCapacity,
                                       const void* samplesBuffer,
                                       const size_t* samplesSizes, unsigned nbSamples);
   
   typedef struct {
       int      compressionLevel;   /*< optimize for a specific zstd compression level; 0 means default */
       unsigned notificationLevel;  /*< Write log to stderr; 0 = none (default); 1 = errors; 2 = progression; 3 = details; 4 = debug; */
       unsigned dictID;             /*< force dictID value; 0 means auto mode (32-bits random value)
                                     *   NOTE: The zstd format reserves some dictionary IDs for future use.
                                     *         You may use them in private settings, but be warned that they
                                     *         may be used by zstd in a public dictionary registry in the future.
                                     *         These dictionary IDs are:
                                     *           - low range  : <= 32767
                                     *           - high range : >= (2^31)
                                     */
   } ZDICT_params_t;
   
   /*! ZDICT_finalizeDictionary():
    * Given a custom content as a basis for dictionary, and a set of samples,
    * finalize dictionary by adding headers and statistics according to the zstd
    * dictionary format.
    *
    * Samples must be stored concatenated in a flat buffer `samplesBuffer`,
    * supplied with an array of sizes `samplesSizes`, providing the size of each
    * sample in order. The samples are used to construct the statistics, so they
    * should be representative of what you will compress with this dictionary.
    *
    * The compression level can be set in `parameters`. You should pass the
    * compression level you expect to use in production. The statistics for each
    * compression level differ, so tuning the dictionary for the compression level
    * can help quite a bit.
    *
    * You can set an explicit dictionary ID in `parameters`, or allow us to pick
    * a random dictionary ID for you, but we can't guarantee no collisions.
    *
    * The dstDictBuffer and the dictContent may overlap, and the content will be
    * appended to the end of the header. If the header + the content doesn't fit in
    * maxDictSize the beginning of the content is truncated to make room, since it
    * is presumed that the most profitable content is at the end of the dictionary,
    * since that is the cheapest to reference.
    *
    * `maxDictSize` must be >= max(dictContentSize, ZSTD_DICTSIZE_MIN).
    *
    * @return: size of dictionary stored into `dstDictBuffer` (<= `maxDictSize`),
    *          or an error code, which can be tested by ZDICT_isError().
    * Note: ZDICT_finalizeDictionary() will push notifications into stderr if
    *       instructed to, using notificationLevel>0.
    * NOTE: This function currently may fail in several edge cases including:
    *         * Not enough samples
    *         * Samples are uncompressible
    *         * Samples are all exactly the same
    */
   ZDICTLIB_API size_t ZDICT_finalizeDictionary(void* dstDictBuffer, size_t maxDictSize,
                                   const void* dictContent, size_t dictContentSize,
                                   const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples,
                                   ZDICT_params_t parameters);
   
   
   /*======   Helper functions   ======*/
   ZDICTLIB_API unsigned ZDICT_getDictID(const void* dictBuffer, size_t dictSize);  /**< extracts dictID; @return zero if error (not a valid dictionary) */
   ZDICTLIB_API size_t ZDICT_getDictHeaderSize(const void* dictBuffer, size_t dictSize);  /* returns dict header size; returns a ZSTD error code on failure */
   ZDICTLIB_API unsigned ZDICT_isError(size_t errorCode);
   ZDICTLIB_API const char* ZDICT_getErrorName(size_t errorCode);
   
   
   
   #ifdef ZDICT_STATIC_LINKING_ONLY
   
   /* ====================================================================================
    * The definitions in this section are considered experimental.
    * They should never be used with a dynamic library, as they may change in the future.
    * They are provided for advanced usages.
    * Use them only in association with static linking.
    * ==================================================================================== */
   
   #define ZDICT_DICTSIZE_MIN    256
   /* Deprecated: Remove in v1.6.0 */
   #define ZDICT_CONTENTSIZE_MIN 128
   
   /*! ZDICT_cover_params_t:
    *  k and d are the only required parameters.
    *  For others, value 0 means default.
    */
   typedef struct {
       unsigned k;                  /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */
       unsigned d;                  /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */
       unsigned steps;              /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */
       unsigned nbThreads;          /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */
       double splitPoint;           /* Percentage of samples used for training: Only used for optimization : the first nbSamples * splitPoint samples will be used to training, the last nbSamples * (1 - splitPoint) samples will be used for testing, 0 means default (1.0), 1.0 when all samples are used for both training and testing */
       unsigned shrinkDict;         /* Train dictionaries to shrink in size starting from the minimum size and selects the smallest dictionary that is shrinkDictMaxRegression% worse than the largest dictionary. 0 means no shrinking and 1 means shrinking  */
       unsigned shrinkDictMaxRegression; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */
       ZDICT_params_t zParams;
   } ZDICT_cover_params_t;
   
   typedef struct {
       unsigned k;                  /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */
       unsigned d;                  /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */
       unsigned f;                  /* log of size of frequency array : constraint: 0 < f <= 31 : 1 means default(20)*/
       unsigned steps;              /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */
       unsigned nbThreads;          /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */
       double splitPoint;           /* Percentage of samples used for training: Only used for optimization : the first nbSamples * splitPoint samples will be used to training, the last nbSamples * (1 - splitPoint) samples will be used for testing, 0 means default (0.75), 1.0 when all samples are used for both training and testing */
       unsigned accel;              /* Acceleration level: constraint: 0 < accel <= 10, higher means faster and less accurate, 0 means default(1) */
       unsigned shrinkDict;         /* Train dictionaries to shrink in size starting from the minimum size and selects the smallest dictionary that is shrinkDictMaxRegression% worse than the largest dictionary. 0 means no shrinking and 1 means shrinking  */
       unsigned shrinkDictMaxRegression; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */
   
       ZDICT_params_t zParams;
   } ZDICT_fastCover_params_t;
   
   /*! ZDICT_trainFromBuffer_cover():
    *  Train a dictionary from an array of samples using the COVER algorithm.
    *  Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
    *  supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
    *  The resulting dictionary will be saved into `dictBuffer`.
    * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
    *          or an error code, which can be tested with ZDICT_isError().
    *          See ZDICT_trainFromBuffer() for details on failure modes.
    *  Note: ZDICT_trainFromBuffer_cover() requires about 9 bytes of memory for each input byte.
    *  Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
    *        It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
    *        In general, it's recommended to provide a few thousands samples, though this can vary a lot.
    *        It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
    */
   ZDICTLIB_API size_t ZDICT_trainFromBuffer_cover(
             void *dictBuffer, size_t dictBufferCapacity,
       const void *samplesBuffer, const size_t *samplesSizes, unsigned nbSamples,
             ZDICT_cover_params_t parameters);
   
   /*! ZDICT_optimizeTrainFromBuffer_cover():
    * The same requirements as above hold for all the parameters except `parameters`.
    * This function tries many parameter combinations and picks the best parameters.
    * `*parameters` is filled with the best parameters found,
    * dictionary constructed with those parameters is stored in `dictBuffer`.
    *
    * All of the parameters d, k, steps are optional.
    * If d is non-zero then we don't check multiple values of d, otherwise we check d = {6, 8}.
    * if steps is zero it defaults to its default value.
    * If k is non-zero then we don't check multiple values of k, otherwise we check steps values in [50, 2000].
    *
    * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
    *          or an error code, which can be tested with ZDICT_isError().
    *          On success `*parameters` contains the parameters selected.
    *          See ZDICT_trainFromBuffer() for details on failure modes.
    * Note: ZDICT_optimizeTrainFromBuffer_cover() requires about 8 bytes of memory for each input byte and additionally another 5 bytes of memory for each byte of memory for each thread.
    */
   ZDICTLIB_API size_t ZDICT_optimizeTrainFromBuffer_cover(
             void* dictBuffer, size_t dictBufferCapacity,
       const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples,
             ZDICT_cover_params_t* parameters);
   
   /*! ZDICT_trainFromBuffer_fastCover():
    *  Train a dictionary from an array of samples using a modified version of COVER algorithm.
    *  Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
    *  supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
    *  d and k are required.
    *  All other parameters are optional, will use default values if not provided
    *  The resulting dictionary will be saved into `dictBuffer`.
    * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
    *          or an error code, which can be tested with ZDICT_isError().
    *          See ZDICT_trainFromBuffer() for details on failure modes.
    *  Note: ZDICT_trainFromBuffer_fastCover() requires 6 * 2^f bytes of memory.
    *  Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
    *        It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
    *        In general, it's recommended to provide a few thousands samples, though this can vary a lot.
    *        It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
    */
   ZDICTLIB_API size_t ZDICT_trainFromBuffer_fastCover(void *dictBuffer,
                       size_t dictBufferCapacity, const void *samplesBuffer,
                       const size_t *samplesSizes, unsigned nbSamples,
                       ZDICT_fastCover_params_t parameters);
   
   /*! ZDICT_optimizeTrainFromBuffer_fastCover():
    * The same requirements as above hold for all the parameters except `parameters`.
    * This function tries many parameter combinations (specifically, k and d combinations)
    * and picks the best parameters. `*parameters` is filled with the best parameters found,
    * dictionary constructed with those parameters is stored in `dictBuffer`.
    * All of the parameters d, k, steps, f, and accel are optional.
    * If d is non-zero then we don't check multiple values of d, otherwise we check d = {6, 8}.
    * if steps is zero it defaults to its default value.
    * If k is non-zero then we don't check multiple values of k, otherwise we check steps values in [50, 2000].
    * If f is zero, default value of 20 is used.
    * If accel is zero, default value of 1 is used.
    *
    * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
    *          or an error code, which can be tested with ZDICT_isError().
    *          On success `*parameters` contains the parameters selected.
    *          See ZDICT_trainFromBuffer() for details on failure modes.
    * Note: ZDICT_optimizeTrainFromBuffer_fastCover() requires about 6 * 2^f bytes of memory for each thread.
    */
   ZDICTLIB_API size_t ZDICT_optimizeTrainFromBuffer_fastCover(void* dictBuffer,
                       size_t dictBufferCapacity, const void* samplesBuffer,
                       const size_t* samplesSizes, unsigned nbSamples,
                       ZDICT_fastCover_params_t* parameters);
   
   typedef struct {
       unsigned selectivityLevel;   /* 0 means default; larger => select more => larger dictionary */
       ZDICT_params_t zParams;
   } ZDICT_legacy_params_t;
   
   /*! ZDICT_trainFromBuffer_legacy():
    *  Train a dictionary from an array of samples.
    *  Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
    *  supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
    *  The resulting dictionary will be saved into `dictBuffer`.
    * `parameters` is optional and can be provided with values set to 0 to mean "default".
    * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
    *          or an error code, which can be tested with ZDICT_isError().
    *          See ZDICT_trainFromBuffer() for details on failure modes.
    *  Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
    *        It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
    *        In general, it's recommended to provide a few thousands samples, though this can vary a lot.
    *        It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
    *  Note: ZDICT_trainFromBuffer_legacy() will send notifications into stderr if instructed to, using notificationLevel>0.
    */
   ZDICTLIB_API size_t ZDICT_trainFromBuffer_legacy(
       void* dictBuffer, size_t dictBufferCapacity,
       const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples,
       ZDICT_legacy_params_t parameters);
   
   
   /* Deprecation warnings */
   /* It is generally possible to disable deprecation warnings from compiler,
      for example with -Wno-deprecated-declarations for gcc
      or _CRT_SECURE_NO_WARNINGS in Visual.
      Otherwise, it's also possible to manually define ZDICT_DISABLE_DEPRECATE_WARNINGS */
   #ifdef ZDICT_DISABLE_DEPRECATE_WARNINGS
   #  define ZDICT_DEPRECATED(message) ZDICTLIB_API   /* disable deprecation warnings */
   #else
   #  define ZDICT_GCC_VERSION (__GNUC__ * 100 + __GNUC_MINOR__)
   #  if defined (__cplusplus) && (__cplusplus >= 201402) /* C++14 or greater */
   #    define ZDICT_DEPRECATED(message) [[deprecated(message)]] ZDICTLIB_API
   #  elif defined(__clang__) || (ZDICT_GCC_VERSION >= 405)
   #    define ZDICT_DEPRECATED(message) ZDICTLIB_API __attribute__((deprecated(message)))
   #  elif (ZDICT_GCC_VERSION >= 301)
   #    define ZDICT_DEPRECATED(message) ZDICTLIB_API __attribute__((deprecated))
   #  elif defined(_MSC_VER)
   #    define ZDICT_DEPRECATED(message) ZDICTLIB_API __declspec(deprecated(message))
   #  else
   #    pragma message("WARNING: You need to implement ZDICT_DEPRECATED for this compiler")
   #    define ZDICT_DEPRECATED(message) ZDICTLIB_API
   #  endif
   #endif /* ZDICT_DISABLE_DEPRECATE_WARNINGS */
   
   ZDICT_DEPRECATED("use ZDICT_finalizeDictionary() instead")
   size_t ZDICT_addEntropyTablesFromBuffer(void* dictBuffer, size_t dictContentSize, size_t dictBufferCapacity,
                                     const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples);
   
   
   #endif   /* ZDICT_STATIC_LINKING_ONLY */
   
   #if defined (__cplusplus)
   }
   #endif
   
   #endif   /* DICTBUILDER_H_001 */

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