mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-10-30 14:40:16 +01:00
d0d5de42e5
* gguf-split: split and merge gguf files per tensor * gguf-split: build with make toolchain * gguf-split: rename `--split-tensors-size` to `--split-max-tensors`. Set general.split_count KV to all split * split : minor style + fix compile warnings * gguf-split: remove --upload not implemented --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
492 lines
16 KiB
C++
492 lines
16 KiB
C++
#include "llama.h"
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#include "ggml.h"
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#include "common.h"
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#include <algorithm>
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#include <cmath>
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#include <cstdint>
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#include <cstdlib>
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#include <fstream>
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#include <ios>
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#include <string>
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#include <vector>
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#include <stdio.h>
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#include <fcntl.h>
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#include <unistd.h>
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#include <string.h>
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#include <unistd.h>
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enum split_operation : uint8_t {
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SPLIT_OP_SPLIT,
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SPLIT_OP_MERGE,
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};
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static const char * const LLM_KV_GENERAL_SPLIT_I_SPLIT = "general.split";
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static const char * const LLM_KV_GENERAL_SPLIT_N_SPLIT = "general.split_count";
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static const int SPLIT_FILENAME_MAX = 256;
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static const char * const SPLIT_FILENAME_FORMAT = "%s-%05d-of-%05d.gguf";
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struct split_params {
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split_operation operation = SPLIT_OP_SPLIT;
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int n_split_tensors = 128;
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std::string input;
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std::string output;
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};
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static void split_print_usage(const char * executable) {
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const split_params default_params;
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printf("\n");
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printf("usage: %s [options] GGUF_IN GGUF_OUT\n", executable);
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printf("\n");
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printf("Apply a GGUF operation on IN to OUT.");
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printf("\n");
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printf("options:\n");
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printf(" -h, --help show this help message and exit\n");
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printf(" --version show version and build info\n");
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printf(" --split split GGUF to multiple GGUF (default)\n");
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printf(" --split-max-tensors max tensors in each split: default(%d)\n", default_params.n_split_tensors);
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printf(" --merge merge multiple GGUF to a single GGUF\n");
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printf("\n");
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}
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static bool split_params_parse_ex(int argc, const char ** argv, split_params & params) {
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std::string arg;
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const std::string arg_prefix = "--";
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bool invalid_param = false;
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int arg_idx = 1;
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for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) {
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arg = argv[arg_idx];
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if (arg.compare(0, arg_prefix.size(), arg_prefix) == 0) {
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std::replace(arg.begin(), arg.end(), '_', '-');
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}
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bool arg_found = false;
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if (arg == "-h" || arg == "--help") {
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split_print_usage(argv[0]);
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exit(0);
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}
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if (arg == "--version") {
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fprintf(stderr, "version: %d (%s)\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT);
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fprintf(stderr, "built with %s for %s\n", LLAMA_COMPILER, LLAMA_BUILD_TARGET);
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exit(0);
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}
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if (arg == "--merge") {
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arg_found = true;
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params.operation = SPLIT_OP_MERGE;
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}
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if (arg == "--split") {
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arg_found = true;
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params.operation = SPLIT_OP_SPLIT;
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}
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if (arg == "--split-max-tensors") {
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if (++arg_idx >= argc) {
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invalid_param = true;
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break;
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}
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arg_found = true;
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params.n_split_tensors = atoi(argv[arg_idx]);
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}
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if (!arg_found) {
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throw std::invalid_argument("error: unknown argument: " + arg);
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}
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}
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if (invalid_param) {
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throw std::invalid_argument("error: invalid parameter for argument: " + arg);
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}
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if (argc - arg_idx < 2) {
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printf("%s: bad arguments\n", argv[0]);
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split_print_usage(argv[0]);
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return false;
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}
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params.input = argv[arg_idx++];
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params.output = argv[arg_idx++];
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return true;
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}
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static bool split_params_parse(int argc, const char ** argv, split_params & params) {
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bool result = true;
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try {
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if (!split_params_parse_ex(argc, argv, params)) {
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split_print_usage(argv[0]);
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exit(1);
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}
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}
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catch (const std::invalid_argument & ex) {
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fprintf(stderr, "%s\n", ex.what());
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split_print_usage(argv[0]);
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exit(1);
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}
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return result;
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}
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static void zeros(std::ofstream & file, size_t n) {
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char zero = 0;
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for (size_t i = 0; i < n; ++i) {
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file.write(&zero, 1);
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}
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}
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static std::string split_file_name(const std::string & path, int i_split, int n_split) {
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char f_split[SPLIT_FILENAME_MAX] = {0};
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snprintf(f_split, sizeof(f_split), SPLIT_FILENAME_FORMAT, path.c_str(), i_split + 1, n_split);
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return std::string(f_split);
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}
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struct split_strategy {
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const split_params params;
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std::ifstream & f_input;
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struct gguf_context * ctx_gguf;
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struct ggml_context * ctx_meta = NULL;
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const int n_tensors;
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const int n_split;
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int i_split = 0;
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int i_tensor = 0;
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std::vector<uint8_t> read_data;
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struct gguf_context * ctx_out;
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std::ofstream fout;
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split_strategy(const split_params & params,
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std::ifstream & f_input,
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struct gguf_context * ctx_gguf,
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struct ggml_context * ctx_meta) :
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params(params),
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f_input(f_input),
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ctx_gguf(ctx_gguf),
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ctx_meta(ctx_meta),
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n_tensors(gguf_get_n_tensors(ctx_gguf)),
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n_split(std::ceil(1. * n_tensors / params.n_split_tensors)) {
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}
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bool should_split() const {
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return i_tensor < n_tensors && i_tensor % params.n_split_tensors == 0;
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}
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void split_start() {
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ctx_out = gguf_init_empty();
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// Save all metadata in first split only
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if (i_split == 0) {
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gguf_set_kv(ctx_out, ctx_gguf);
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}
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gguf_set_val_u8(ctx_out, LLM_KV_GENERAL_SPLIT_I_SPLIT, i_split);
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gguf_set_val_u8(ctx_out, LLM_KV_GENERAL_SPLIT_N_SPLIT, n_split);
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// populate the original tensors, so we get an initial metadata
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for (int i = i_split * params.n_split_tensors; i < n_tensors && i < (i_split + 1) * params.n_split_tensors; ++i) {
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struct ggml_tensor * meta = ggml_get_tensor(ctx_meta, gguf_get_tensor_name(ctx_gguf, i));
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gguf_add_tensor(ctx_out, meta);
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}
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auto split_name = split_file_name(params.output, i_split, n_split);
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fprintf(stderr, "%s: %s ...", __func__, split_name.c_str());
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fout = std::ofstream(split_name, std::ios::binary);
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fout.exceptions(std::ofstream::failbit); // fail fast on write errors
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auto meta_size = gguf_get_meta_size(ctx_out);
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// placeholder for the meta data
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::zeros(fout, meta_size);
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i_split++;
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}
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void next_tensor() {
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const char * t_name = gguf_get_tensor_name(ctx_gguf, i_tensor);
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struct ggml_tensor * t = ggml_get_tensor(ctx_meta, t_name);
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auto n_bytes = ggml_nbytes(t);
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if (read_data.size() < n_bytes) {
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read_data.resize(n_bytes);
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}
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auto offset = gguf_get_data_offset(ctx_gguf) + gguf_get_tensor_offset(ctx_gguf, i_tensor);
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f_input.seekg(offset);
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f_input.read((char *)read_data.data(), n_bytes);
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t->data = read_data.data();
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// write tensor data + padding
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fout.write((const char *)t->data, n_bytes);
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zeros(fout, GGML_PAD(n_bytes, GGUF_DEFAULT_ALIGNMENT) - n_bytes);
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i_tensor++;
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}
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void split_end() {
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// go back to beginning of file and write the updated metadata
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fout.seekp(0);
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std::vector<uint8_t> data(gguf_get_meta_size(ctx_out));
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gguf_get_meta_data(ctx_out, data.data());
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fout.write((const char *)data.data(), data.size());
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fout.close();
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gguf_free(ctx_out);
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fprintf(stderr, "\033[3Ddone\n");
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}
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};
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static void gguf_split(const split_params & split_params) {
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struct ggml_context * ctx_meta = NULL;
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struct gguf_init_params params = {
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/*.no_alloc = */ true,
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/*.ctx = */ &ctx_meta,
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};
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std::ifstream f_input(split_params.input.c_str(), std::ios::binary);
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if (!f_input.is_open()) {
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fprintf(stderr, "%s: failed to open input GGUF from %s\n", __func__, split_params.input.c_str());
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exit(1);
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}
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auto * ctx_gguf = gguf_init_from_file(split_params.input.c_str(), params);
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if (!ctx_gguf) {
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fprintf(stderr, "%s: failed to load input GGUF from %s\n", __func__, split_params.input.c_str());
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exit(1);
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}
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split_strategy strategy(split_params, f_input, ctx_gguf, ctx_meta);
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fprintf(stderr, "%s: %s -> %s (%d tensors per file)\n",
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__func__, split_params.input.c_str(),
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split_file_name(split_params.output, strategy.i_split, strategy.n_split).c_str(),
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split_params.n_split_tensors);
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strategy.split_start();
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while (strategy.i_tensor < strategy.n_tensors) {
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strategy.next_tensor();
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if (strategy.should_split()) {
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strategy.split_end();
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strategy.split_start();
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}
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}
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strategy.split_end();
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gguf_free(ctx_gguf);
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f_input.close();
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fprintf(stderr, "%s: %d gguf split written with a total of %d tensors.\n",
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__func__, strategy.n_split, strategy.n_tensors);
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}
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static void gguf_merge(const split_params & split_params) {
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fprintf(stderr, "%s: %s -> %s\n",
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__func__, split_params.input.c_str(),
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split_params.output.c_str());
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int n_split = 1;
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int total_tensors = 0;
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auto * ctx_out = gguf_init_empty();
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std::ofstream fout(split_params.output.c_str(), std::ios::binary);
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fout.exceptions(std::ofstream::failbit); // fail fast on write errors
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std::vector<uint8_t> read_data;
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std::vector<ggml_context *> ctx_metas;
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std::vector<gguf_context *> ctx_ggufs;
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std::string split_prefix;
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// First pass to find KV and tensors metadata
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for (int i_split = 0; i_split < n_split; i_split++) {
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struct ggml_context * ctx_meta = NULL;
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struct gguf_init_params params = {
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/*.no_alloc = */ true,
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/*.ctx = */ &ctx_meta,
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};
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auto split_name = split_params.input;
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if (i_split > 0) {
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split_name = split_file_name(split_prefix, i_split, n_split);
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}
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fprintf(stderr, "%s: reading metadata %s ...", __func__, split_name.c_str());
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auto * ctx_gguf = gguf_init_from_file(split_name.c_str(), params);
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if (!ctx_gguf) {
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fprintf(stderr, "\n%s: failed to load input GGUF from %s\n", __func__, split_params.input.c_str());
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exit(1);
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}
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ctx_ggufs.push_back(ctx_gguf);
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ctx_metas.push_back(ctx_meta);
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if (i_split == 0) {
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auto key_n_split = gguf_find_key(ctx_gguf, LLM_KV_GENERAL_SPLIT_N_SPLIT);
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if (key_n_split < 0) {
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fprintf(stderr,
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"\n%s: input file does not contain %s metadata\n",
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__func__,
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LLM_KV_GENERAL_SPLIT_N_SPLIT);
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gguf_free(ctx_gguf);
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gguf_free(ctx_out);
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fout.close();
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exit(1);
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}
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n_split = gguf_get_val_u8(ctx_gguf, key_n_split);
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if (n_split < 1) {
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fprintf(stderr,
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"\n%s: input file does not contain a valid split count %d\n",
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__func__,
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n_split);
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gguf_free(ctx_gguf);
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gguf_free(ctx_out);
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fout.close();
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exit(1);
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}
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// Do not trigger merge if we try to merge again the output
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gguf_set_val_u8(ctx_out, LLM_KV_GENERAL_SPLIT_N_SPLIT, 0);
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// Set metadata from the first split
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gguf_set_kv(ctx_out, ctx_gguf);
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}
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// Verify the file naming
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{
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int i_split_file = 0;
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int n_split_file = 0;
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const char * i_split_format = "-00000-of-00000.gguf";
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if (split_name.size() < strlen(i_split_format)) {
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fprintf(stderr, "\n%s: unexpected input file name: %s\n", __func__, split_params.input.c_str());
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for (auto * _ctx_gguf : ctx_ggufs) {
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gguf_free(_ctx_gguf);
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}
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gguf_free(ctx_out);
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fout.close();
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exit(1);
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}
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split_prefix = split_name.substr(0, split_name.size() - strlen(i_split_format));
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const char * split_name_c_str = split_name.c_str();
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int n_part = sscanf(&split_name_c_str[0] + split_prefix.size(), "-%d-of-%d", &i_split_file, &n_split_file);
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if (n_part != 2 || i_split_file - 1 != i_split || n_split_file != n_split) {
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fprintf(stderr, "\n%s: unexpected input file name: %s"
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" i_split=%d i_split_file=%d"
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" n_split=%d n_split_file=%d\n", __func__,
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split_params.input.c_str(),
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i_split, i_split_file,
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n_split, n_split_file);
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for (auto * _ctx_gguf : ctx_ggufs) {
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gguf_free(_ctx_gguf);
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}
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gguf_free(ctx_out);
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fout.close();
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exit(1);
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}
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}
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auto n_tensors = gguf_get_n_tensors(ctx_gguf);
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for (int i_tensor = 0; i_tensor < n_tensors; i_tensor++) {
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const char * t_name = gguf_get_tensor_name(ctx_gguf, i_tensor);
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struct ggml_tensor * t = ggml_get_tensor(ctx_meta, t_name);
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gguf_add_tensor(ctx_out, t);
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}
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total_tensors += n_tensors;
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fprintf(stderr, "\033[3Ddone\n");
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}
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// placeholder for the meta data
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{
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auto meta_size = gguf_get_meta_size(ctx_out);
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::zeros(fout, meta_size);
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}
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// Write tensors data
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for (int i_split = 0; i_split < n_split; i_split++) {
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auto split_name = split_file_name(split_prefix, i_split, n_split);
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std::ifstream f_input(split_name.c_str(), std::ios::binary);
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if (!f_input.is_open()) {
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fprintf(stderr, "%s: failed to open input GGUF from %s\n", __func__, split_name.c_str());
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for (auto * _ctx_gguf : ctx_ggufs) {
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gguf_free(_ctx_gguf);
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}
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gguf_free(ctx_out);
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fout.close();
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exit(1);
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}
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fprintf(stderr, "%s: writing tensors %s ...", __func__, split_name.c_str());
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auto * ctx_gguf = ctx_ggufs[i_split];
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auto * ctx_meta = ctx_metas[i_split];
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auto n_tensors = gguf_get_n_tensors(ctx_gguf);
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for (int i_tensor = 0; i_tensor < n_tensors; i_tensor++) {
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const char * t_name = gguf_get_tensor_name(ctx_gguf, i_tensor);
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struct ggml_tensor * t = ggml_get_tensor(ctx_meta, t_name);
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auto n_bytes = ggml_nbytes(t);
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if (read_data.size() < n_bytes) {
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read_data.resize(n_bytes);
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}
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auto offset = gguf_get_data_offset(ctx_gguf) + gguf_get_tensor_offset(ctx_gguf, i_tensor);
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f_input.seekg(offset);
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f_input.read((char *)read_data.data(), n_bytes);
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// write tensor data + padding
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fout.write((const char *)read_data.data(), n_bytes);
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zeros(fout, GGML_PAD(n_bytes, GGUF_DEFAULT_ALIGNMENT) - n_bytes);
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}
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gguf_free(ctx_gguf);
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ggml_free(ctx_meta);
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f_input.close();
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fprintf(stderr, "\033[3Ddone\n");
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}
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{
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// go back to beginning of file and write the updated metadata
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fout.seekp(0);
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std::vector<uint8_t> data(gguf_get_meta_size(ctx_out));
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gguf_get_meta_data(ctx_out, data.data());
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fout.write((const char *)data.data(), data.size());
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|
|
fout.close();
|
|
gguf_free(ctx_out);
|
|
}
|
|
|
|
fprintf(stderr, "%s: %s merged from %d split with %d tensors.\n",
|
|
__func__, split_params.output.c_str(), n_split, total_tensors);
|
|
}
|
|
|
|
int main(int argc, const char ** argv) {
|
|
if (argc < 3) {
|
|
split_print_usage(argv[0]);
|
|
}
|
|
|
|
split_params params;
|
|
split_params_parse(argc, argv, params);
|
|
|
|
switch (params.operation) {
|
|
case SPLIT_OP_SPLIT: gguf_split(params);
|
|
break;
|
|
case SPLIT_OP_MERGE: gguf_merge(params);
|
|
break;
|
|
default:split_print_usage(argv[0]);
|
|
exit(1);
|
|
}
|
|
|
|
return 0;
|
|
}
|