From bce54642c8ac6ff41a55140d4f477bee77048e21 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 20 Aug 2024 15:17:24 -0400 Subject: [PATCH 01/16] imatrix : allow processing multiple chunks per batch * perplexity : simplify filling the batch --- examples/imatrix/imatrix.cpp | 94 ++++++++++++++++++++++-------- examples/perplexity/perplexity.cpp | 16 ++--- 2 files changed, 75 insertions(+), 35 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 83b85d72b043a..7b91a7e306f57 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -432,10 +432,9 @@ static void process_logits( } } -static bool compute_imatrix(llama_context * ctx, const gpt_params & params) { +static bool compute_imatrix(llama_context * ctx, const gpt_params & params, const int32_t n_ctx) { const bool add_bos = llama_add_bos_token(llama_get_model(ctx)); GGML_ASSERT(!llama_add_eos_token(llama_get_model(ctx))); - const int n_ctx = llama_n_ctx(ctx); auto tim1 = std::chrono::high_resolution_clock::now(); fprintf(stderr, "%s: tokenizing the input ..\n", __func__); @@ -479,22 +478,28 @@ static bool compute_imatrix(llama_context * ctx, const gpt_params & params) { double nll = 0.0; double nll2 = 0.0; - fprintf(stderr, "%s: computing over %d chunks with batch_size %d\n", __func__, n_chunk, n_batch); - std::vector workers(std::thread::hardware_concurrency() - 1); const int num_batches = (n_ctx + n_batch - 1) / n_batch; + const int n_seq = std::max(1, n_batch / n_ctx); + + GGML_ASSERT(n_batch < n_ctx || n_batch % n_ctx == 0); + GGML_ASSERT(params.n_ctx == n_seq * n_ctx); + + llama_batch batch = llama_batch_init(std::min(n_batch, n_ctx*n_seq), 0, 1); std::vector logits; if (params.compute_ppl && num_batches > 1) { logits.reserve((size_t)n_ctx * n_vocab); } - for (int i = 0; i < n_chunk; ++i) { + fprintf(stderr, "%s: computing over %d chunks, n_ctx=%d, batch_size=%d, n_seq=%d\n", __func__, n_chunk, n_ctx, n_batch, n_seq); + + for (int i = 0; i < n_chunk; i += n_seq) { const int start = i * n_ctx; const int end = start + n_ctx; - std::vector logits; + const int n_seq_batch = std::min(n_seq, n_chunk - i); const auto t_start = std::chrono::high_resolution_clock::now(); @@ -505,35 +510,50 @@ static bool compute_imatrix(llama_context * ctx, const gpt_params & params) { const int batch_start = start + j * n_batch; const int batch_size = std::min(end - batch_start, n_batch); - // save original token and restore it after eval - const auto token_org = tokens[batch_start]; + // clear the batch + llama_batch_clear(batch); + + for (int seq = 0; seq < n_seq_batch; seq++) { + int seq_start = batch_start + seq*n_ctx; + + // save original token and restore it after eval + const auto token_org = tokens[seq_start]; - // add BOS token for the first batch of each chunk - if (add_bos && j == 0) { - tokens[batch_start] = llama_token_bos(llama_get_model(ctx)); + // add BOS token for the first batch of each chunk + if (add_bos && j == 0) { + tokens[seq_start] = llama_token_bos(llama_get_model(ctx)); + } + + for (int k = 0; k < batch_size; ++k) { + // NOTE: specifying all logits to get activations for the output.weight tensor + // and also for the perplexity calculation. + // TODO: only get outputs when (params.process_output || params.compute_ppl) + // (not possible when this skips FFN computation of the last layer) + llama_batch_add(batch, tokens[seq_start + k], j*n_batch + k, { seq }, true); + } + + // restore the original token in case it was set to BOS + tokens[seq_start] = token_org; } - // TODO: use batch.logits to save computations instead of relying on logits_all == true - if (llama_decode(ctx, llama_batch_get_one(tokens.data() + batch_start, batch_size, j * n_batch, 0))) { + if (llama_decode(ctx, batch)) { fprintf(stderr, "%s : failed to eval\n", __func__); return false; } - // restore the original token in case it was set to BOS - tokens[batch_start] = token_org; - if (params.compute_ppl && num_batches > 1) { const auto * batch_logits = llama_get_logits(ctx); logits.insert(logits.end(), batch_logits, batch_logits + batch_size * n_vocab); } } - const auto t_end = std::chrono::high_resolution_clock::now(); if (i == 0) { + llama_synchronize(ctx); + const auto t_end = std::chrono::high_resolution_clock::now(); const float t_total = std::chrono::duration(t_end - t_start).count(); fprintf(stderr, "%s: %.2f seconds per pass - ETA ", __func__, t_total); - int total_seconds = (int)(t_total * n_chunk); + int total_seconds = (int)(t_total*n_chunk/n_seq); if (total_seconds >= 60*60) { fprintf(stderr, "%d hours ", total_seconds / (60*60)); total_seconds = total_seconds % (60*60); @@ -543,12 +563,21 @@ static bool compute_imatrix(llama_context * ctx, const gpt_params & params) { if (params.compute_ppl) { const int first = n_ctx/2; - const auto all_logits = num_batches > 1 ? logits.data() : llama_get_logits(ctx); - process_logits(n_vocab, all_logits + first*n_vocab, tokens.data() + start + first, n_ctx - 1 - first, - workers, nll, nll2, logit_history.data() + start + first, prob_history.data() + start + first); - count += n_ctx - first - 1; + for (int seq = 0; seq < n_seq_batch; seq++) { + const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits_ith(ctx, seq*n_ctx + first); + + llama_token * tokens_data = tokens.data() + start + seq*n_ctx + first; - printf("[%d]%.4lf,", i + 1, std::exp(nll / count)); + process_logits(n_vocab, all_logits + first*n_vocab, + tokens_data, n_ctx - 1 - first, + workers, nll, nll2, + logit_history.data() + start + seq*n_ctx + first, + prob_history.data() + start + seq*n_ctx + first); + + count += n_ctx - first - 1; + + printf("[%d]%.4lf,", i + seq + 1, std::exp(nll / count)); + } fflush(stdout); logits.clear(); @@ -584,7 +613,22 @@ int main(int argc, char ** argv) { return 1; } - params.n_batch = std::min(params.n_batch, params.n_ctx); + const int32_t n_ctx = params.n_ctx; + + if (n_ctx <= 0) { + fprintf(stderr, "%s: imatrix tool requires '--ctx-size' > 0\n", __func__); + return 1; + } + + { + const int32_t n_seq = std::max(1, params.n_batch / n_ctx); + const int32_t n_kv = n_seq * n_ctx; + + params.n_parallel = n_seq; + params.n_ctx = n_kv; + + params.n_batch = std::min(params.n_batch, n_kv); + } g_collector.set_params(params); @@ -632,7 +676,7 @@ int main(int argc, char ** argv) { fprintf(stderr, "%s\n", gpt_params_get_system_info(params).c_str()); } - if (!compute_imatrix(ctx, params)) { + if (!compute_imatrix(ctx, params, n_ctx)) { return 1; } diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp index 484dd589109c7..0bc0778fc6466 100644 --- a/examples/perplexity/perplexity.cpp +++ b/examples/perplexity/perplexity.cpp @@ -583,7 +583,9 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par int n_outputs = 0; - batch.n_tokens = 0; + // clear the batch + llama_batch_clear(batch); + for (int seq = 0; seq < n_seq_batch; seq++) { int seq_start = batch_start + seq*n_ctx; @@ -596,16 +598,10 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par } for (int k = 0; k < batch_size; ++k) { - const int idx = seq*n_ctx + k; - batch.token [idx] = tokens[seq_start + k]; - batch.pos [idx] = j*n_batch + k; - batch.n_seq_id[idx] = 1; - batch.seq_id [idx][0] = seq; - batch.logits [idx] = batch.pos[idx] >= first ? 1 : 0; - - n_outputs += batch.logits[idx] != 0; + llama_pos pos = j*n_batch + k; + llama_batch_add(batch, tokens[seq_start + k], pos, { seq }, pos >= first); + n_outputs += (int) (pos >= first); } - batch.n_tokens += batch_size; // restore the original token in case it was set to BOS tokens[seq_start] = token_org; From 347247a24ec0db754216b7d466bac021bef9ae6a Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 20 Aug 2024 15:35:56 -0400 Subject: [PATCH 02/16] imatrix : fix segfault when using a single chunk per batch --- examples/imatrix/imatrix.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 7b91a7e306f57..6135f00a7e8c1 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -564,7 +564,7 @@ static bool compute_imatrix(llama_context * ctx, const gpt_params & params, cons if (params.compute_ppl) { const int first = n_ctx/2; for (int seq = 0; seq < n_seq_batch; seq++) { - const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits_ith(ctx, seq*n_ctx + first); + const float * all_logits = num_batches > 1 ? logits.data() : llama_get_logits_ith(ctx, seq*n_ctx); llama_token * tokens_data = tokens.data() + start + seq*n_ctx + first; From 3de9300c3786d52fb709596a0c5ac1dc65c9f08d Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Fri, 6 Sep 2024 17:17:25 -0400 Subject: [PATCH 03/16] imatrix : use GGUF to store imatrix data --- convert_legacy_imatrix_to_gguf.py | 118 +++++++++++++++ examples/imatrix/imatrix.cpp | 241 ++++++++++++++++++------------ examples/quantize/quantize.cpp | 127 ++++++++++------ gguf-py/gguf/constants.py | 7 + 4 files changed, 348 insertions(+), 145 deletions(-) create mode 100644 convert_legacy_imatrix_to_gguf.py diff --git a/convert_legacy_imatrix_to_gguf.py b/convert_legacy_imatrix_to_gguf.py new file mode 100644 index 0000000000000..939d3695b23ce --- /dev/null +++ b/convert_legacy_imatrix_to_gguf.py @@ -0,0 +1,118 @@ +#!/usr/bin/env python3 + +from __future__ import annotations + +import os +import sys +import logging +import argparse + +from typing import Any +from pathlib import Path +from dataclasses import dataclass + +import numpy as np +import numpy.typing as npt + +if 'NO_LOCAL_GGUF' not in os.environ: + sys.path.insert(1, str(Path(__file__).parent / 'gguf-py')) +import gguf + + +logger = logging.getLogger("imatrix-to-gguf") + + +class IMatrixWriter(gguf.GGUFWriter): + def add_architecture(self) -> None: + # no arch is stored in imatrix files + pass + + +@dataclass +class IMatrixEntry: + values: np.ndarray[Any, np.dtype[np.float32]] + counts: np.ndarray[Any, np.dtype[np.float32]] + + +class IMatrixReader: + chunk_size: int = 512 # guess + offset: int = 0 + data: np.ndarray[Any, np.dtype[np.uint8]] + n_enties: int + entries: dict[str, IMatrixEntry] + chunk_count: int + dataset: str + + def _get(self, dtype: npt.DTypeLike, count: int = 1) -> npt.NDArray[Any]: + count = int(count) + itemsize = int(np.empty([], dtype=dtype).itemsize) + offset = self.offset + self.offset = offset + itemsize * count + return self.data[offset:self.offset].view(dtype=dtype)[:count] + + def __init__(self, imatrix: Path): + self.offset = 0 + self.entries = {} + self.data = np.memmap(imatrix) + n_entries = self._get(np.int32).item() + assert n_entries >= 0 + for _ in range(n_entries): + len = self._get(np.int32).item() + name = self._get(np.uint8, len).tobytes().decode("utf-8") + ncall = self._get(np.int32).item() + nval = self._get(np.int32).item() + data = self._get(np.float32, nval) + assert name not in self.entries, f"duplicated name: {name!r}" + + self.entries[name] = IMatrixEntry(data, np.array([ncall * self.chunk_size], dtype=np.float32)) + + self.chunk_count = self._get(np.int32).item() + self.dataset = self._get(np.uint8, self._get(np.int32).item()).tobytes().decode("utf-8") + + def to_writer(self, outfile: Path) -> IMatrixWriter: + writer = IMatrixWriter(path=outfile, arch="") + + writer.add_type(gguf.GGUFType.IMATRIX) + writer.add_key_value(gguf.Keys.IMatrix.CHUNK_COUNT, self.chunk_count, gguf.GGUFValueType.UINT32) + writer.add_key_value(gguf.Keys.IMatrix.CHUNK_SIZE, self.chunk_size, gguf.GGUFValueType.UINT32) + writer.add_key_value(gguf.Keys.IMatrix.DATASET, self.dataset, gguf.GGUFValueType.STRING) + + for name, entry in self.entries.items(): + writer.add_tensor(name + ".sums", entry.values) + writer.add_tensor(name + ".counts", entry.counts) + + return writer + + +def parse_args(): + parser = argparse.ArgumentParser( + description="Convert an old imatrix.dat file to a GGUF compatible file") + parser.add_argument( + "--outfile", type=Path, + help="path to write to; default: based on input.", + ) + parser.add_argument( + "--verbose", action="store_true", + help="increase output verbosity", + ) + parser.add_argument( + "imatrix", type=Path, + help="path to an imatrix file", + ) + return parser.parse_args() + + +if __name__ == "__main__": + args = parse_args() + logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO) + + if args.outfile is None: + input_file: Path = args.imatrix + if input_file.suffix != ".gguf": + args.outfile = input_file.with_suffix(".gguf") + + writer = IMatrixReader(args.imatrix).to_writer(args.outfile) + + writer.write_header_to_file(args.outfile) + writer.write_kv_data_to_file() + writer.write_tensors_to_file() diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 6135f00a7e8c1..2314a035d04fe 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -5,11 +5,9 @@ #include #include #include -#include #include #include #include -#include #include #include @@ -22,16 +20,19 @@ static void print_usage(int argc, char ** argv, const gpt_params & params) { LOG_TEE("\nexample usage:\n"); LOG_TEE("\n %s \\\n" - " -m model.gguf -f some-text.txt [-o imatrix.dat] [--process-output] [--verbosity 1] \\\n" + " -m model.gguf -f some-text.txt [-o imatrix.gguf] [--process-output] [--verbosity 1] \\\n" " [--no-ppl] [--chunk 123] [--output-frequency 10] [--save-frequency 0] \\\n" - " [--in-file imatrix-prev-0.dat --in-file imatrix-prev-1.dat ...]\n" , argv[0]); + " [--in-file imatrix-prev-0.gguf --in-file imatrix-prev-1.gguf ...]\n" , argv[0]); LOG_TEE("\n"); } +static const char * const LLM_KV_IMATRIX_DATASET = "imatrix.dataset"; +static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count"; +static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size"; + struct Stats { - std::vector values; - std::vector counts; - int ncall = 0; + std::vector values; + std::vector counts; }; class IMatrixCollector { @@ -39,13 +40,13 @@ class IMatrixCollector { IMatrixCollector() = default; void set_params(gpt_params params) { m_params = std::move(params); } bool collect_imatrix(struct ggml_tensor * t, bool ask, void * user_data); - void save_imatrix(int ncall = -1) const; + void save_imatrix(int32_t n_chunk = -1) const; bool load_imatrix(const char * file_name); private: std::unordered_map m_stats; gpt_params m_params; std::mutex m_mutex; - int m_last_call = 0; + int32_t m_last_chunk = 0; std::vector m_src1_data; std::vector m_ids; // the expert ids from ggml_mul_mat_id }; @@ -119,18 +120,24 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * auto & e = m_stats[wname]; - ++e.ncall; - + if (e.counts.size() == 1 && n_as > 1) { + // broadcast, when loading an old imatrix + e.counts.resize(n_as, e.counts[0]); + } if (e.values.empty()) { e.values.resize(src1->ne[0]*n_as, 0); - e.counts.resize(src1->ne[0]*n_as, 0); + e.counts.resize(n_as, 0); } else if (e.values.size() != (size_t)src1->ne[0]*n_as) { fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]*n_as); exit(1); //GGML_ABORT("fatal error"); } + else if (e.counts.size() != (size_t)n_as) { + fprintf(stderr, "Oops: inconsistent expert count for %s (%d vs %d)\n", wname.c_str(), (int)e.counts.size(), (int)n_as); + exit(1); //GGML_ABORT("fatal error"); + } if (m_params.verbosity > 1) { - printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_call, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[2], (int)src1->type); + printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_chunk, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[2], (int)src1->type); } // loop over all possible experts, regardless if they are used or not in the batch for (int ex = 0; ex < n_as; ++ex) { @@ -148,23 +155,26 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * const int64_t i12 = row; const float * x = (const float *)((const char *)data + i11*src1->nb[1] + i12*src1->nb[2]); + e.counts[ex]++; + for (int j = 0; j < (int)src1->ne[0]; ++j) { e.values[e_start + j] += x[j]*x[j]; - e.counts[e_start + j]++; - if (!std::isfinite(e.values[e_start + j])) { - fprintf(stderr, "%f detected in %s\n", e.values[e_start + j], wname.c_str()); + if (!std::isfinite((float)e.values[e_start + j])) { + fprintf(stderr, "%f detected in %s\n", (float)e.values[e_start + j], wname.c_str()); exit(1); } } } } - if (e.ncall > m_last_call) { - m_last_call = e.ncall; - if (m_last_call % m_params.n_out_freq == 0) { + const int32_t n_chunk = e.counts[ex] / (m_params.n_ctx / m_params.n_parallel); + if (n_chunk > m_last_chunk) { + const int32_t chunk_step = n_chunk - m_last_chunk; + m_last_chunk = n_chunk; + if ((m_last_chunk % m_params.n_out_freq) / chunk_step == 0) { save_imatrix(); } - if (m_params.n_save_freq > 0 && m_last_call%m_params.n_save_freq == 0) { - save_imatrix(m_last_call); + if (m_params.n_save_freq > 0 && (m_last_chunk % m_params.n_save_freq) / chunk_step == 0) { + save_imatrix(m_last_chunk); } } } @@ -172,34 +182,40 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * auto & e = m_stats[wname]; if (e.values.empty()) { e.values.resize(src1->ne[0], 0); - e.counts.resize(src1->ne[0], 0); + e.counts.resize(1, 0); } else if (e.values.size() != (size_t)src1->ne[0]) { fprintf(stderr, "Oops: inconsistent size for %s (%d vs %d)\n", wname.c_str(), (int)e.values.size(), (int)src1->ne[0]); exit(1); //GGML_ABORT("fatal error"); } - ++e.ncall; + else if (e.counts.size() != 1) { + fprintf(stderr, "Oops: inconsistent expert count for %s (%d vs %d)\n", wname.c_str(), (int)e.counts.size(), 1); + exit(1); //GGML_ABORT("fatal error"); + } if (m_params.verbosity > 1) { - printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_call, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); + printf("%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_chunk, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); } + // TODO: higher dimensions for (int row = 0; row < (int)src1->ne[1]; ++row) { const float * x = data + row * src1->ne[0]; + e.counts[0]++; for (int j = 0; j < (int)src1->ne[0]; ++j) { e.values[j] += x[j]*x[j]; - e.counts[j]++; - if (!std::isfinite(e.values[j])) { - fprintf(stderr, "%f detected in %s\n", e.values[j], wname.c_str()); + if (!std::isfinite((float)e.values[j])) { + fprintf(stderr, "%f detected in %s\n", (float)e.values[j], wname.c_str()); exit(1); } } } - if (e.ncall > m_last_call) { - m_last_call = e.ncall; - if (m_last_call % m_params.n_out_freq == 0) { + const int32_t n_chunk = e.counts[0] / (m_params.n_ctx / m_params.n_parallel); + if (n_chunk > m_last_chunk) { + const int32_t chunk_step = n_chunk - m_last_chunk; + m_last_chunk = n_chunk; + if ((m_last_chunk % m_params.n_out_freq) / chunk_step == 0) { save_imatrix(); } - if (m_params.n_save_freq > 0 && m_last_call%m_params.n_save_freq == 0) { - save_imatrix(m_last_call); + if (m_params.n_save_freq > 0 && (m_last_chunk % m_params.n_save_freq) / chunk_step == 0) { + save_imatrix(m_last_chunk); } } } @@ -207,15 +223,15 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * return true; } -void IMatrixCollector::save_imatrix(int ncall) const { +void IMatrixCollector::save_imatrix(int32_t n_chunk) const { auto fname = m_params.out_file; if (fname.empty()) { - fname = "imatrix.dat"; + fname = "imatrix.gguf"; } - if (ncall > 0) { + if (n_chunk > 0) { fname += ".at_"; - fname += std::to_string(ncall); + fname += std::to_string(n_chunk); } // avoid writing imatrix entries that do not have full data @@ -223,6 +239,7 @@ void IMatrixCollector::save_imatrix(int ncall) const { int n_entries = 0; std::vector to_store; + size_t data_size = 0; bool is_first = true; // for printing for (const auto & kv : m_stats) { @@ -256,100 +273,132 @@ void IMatrixCollector::save_imatrix(int ncall) const { n_entries++; to_store.push_back(kv.first); + data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.values.size(), GGML_MEM_ALIGN); + data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.counts.size(), GGML_MEM_ALIGN); } if (to_store.size() < m_stats.size()) { fprintf(stderr, "%s: warning: storing only %zu out of %zu entries\n", __func__, to_store.size(), m_stats.size()); } - std::ofstream out(fname, std::ios::binary); - out.write((const char *) &n_entries, sizeof(n_entries)); + struct ggml_init_params params = { + .mem_size = data_size, + .mem_buffer = NULL, + .no_alloc = false, + }; + struct ggml_context * ctx = ggml_init(params); + struct gguf_context * ctx_gguf = gguf_init_empty(); + + gguf_set_val_str(ctx_gguf, "general.type", "imatrix"); + // Write the input filename to later on specify it in quantize + gguf_set_val_str(ctx_gguf, LLM_KV_IMATRIX_DATASET, m_params.prompt_file.c_str()); + // Write the number of chunks the matrix was computed with + gguf_set_val_u32(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT, m_last_chunk); + gguf_set_val_u32(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE, m_params.n_ctx / m_params.n_parallel); + for (const auto & name : to_store) { const auto & stat = m_stats.at(name); - int len = name.size(); - out.write((const char *) &len, sizeof(len)); - out.write(name.c_str(), len); - out.write((const char *) &stat.ncall, sizeof(stat.ncall)); - int nval = stat.values.size(); - out.write((const char *) &nval, sizeof(nval)); + const int32_t nval = (int32_t) stat.values.size(); + const int32_t nmat = (int32_t) stat.counts.size(); if (nval > 0) { - std::vector tmp(nval); - for (int i = 0; i < nval; i++) { - tmp[i] = (stat.values[i] / static_cast(stat.counts[i])) * static_cast(stat.ncall); + struct ggml_tensor * sums = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, nval / nmat, nmat); + struct ggml_tensor * counts = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, nmat); + ggml_set_name(sums, (name + ".sums").c_str()); + ggml_set_name(counts, (name + ".counts").c_str()); + + for (int32_t j = 0; j < nval; ++j) { + ((float *) sums->data)[j] = (float) stat.values[j]; + } + for (int32_t j = 0; j < nmat; ++j) { + ((float *) counts->data)[j] = (float) stat.counts[j]; } - out.write((const char*)tmp.data(), nval*sizeof(float)); + + gguf_add_tensor(ctx_gguf, sums); + gguf_add_tensor(ctx_gguf, counts); } } - // Write the number of call the matrix was computed with - out.write((const char *) &m_last_call, sizeof(m_last_call)); - - // Write the input filename at the end of the file to later on specify it in quantize - { - int len = m_params.prompt_file.size(); - out.write((const char *) &len, sizeof(len)); - out.write(m_params.prompt_file.c_str(), len); - } + gguf_write_to_file(ctx_gguf, fname.c_str(), false); if (m_params.verbosity > 0) { - fprintf(stderr, "\n%s: stored collected data after %d chunks in %s\n", __func__, m_last_call, fname.c_str()); + fprintf(stderr, "\n%s: stored collected data after %d chunks in %s\n", __func__, m_last_chunk, fname.c_str()); } + + gguf_free(ctx_gguf); + ggml_free(ctx); } -bool IMatrixCollector::load_imatrix(const char * fname) { - std::ifstream in(fname, std::ios::binary); - if (!in) { - printf("%s: failed to open %s\n",__func__, fname); +bool IMatrixCollector::load_imatrix(const char * file_name) { + struct ggml_context * ctx = nullptr; + struct gguf_init_params meta_gguf_params = { + /* .no_alloc = */ false, // the data is needed + /* .ctx = */ &ctx, + }; + struct gguf_context * ctx_gguf = gguf_init_from_file(file_name, meta_gguf_params); + if (!ctx_gguf) { return false; } - int n_entries; - in.read((char*)&n_entries, sizeof(n_entries)); - if (in.fail() || n_entries < 1) { - printf("%s: no data in file %s\n", __func__, fname); + const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); + if (n_entries < 2) { + fprintf(stderr, "%s: no data in file %s\n", __func__, file_name); + gguf_free(ctx_gguf); + ggml_free(ctx); return false; } - for (int i = 0; i < n_entries; ++i) { - int len; in.read((char *)&len, sizeof(len)); - std::vector name_as_vec(len+1); - in.read((char *)name_as_vec.data(), len); - if (in.fail()) { - printf("%s: failed reading name for entry %d from %s\n",__func__,i+1, fname); + + const std::string sums_suffix{".sums"}; + const std::string counts_suffix{".counts"}; + + // TODO: allow loading from mis-ordered imatrix files + for (int32_t i = 0; i < n_entries - 1; i += 2) { + std::string sums_name{gguf_get_tensor_name(ctx_gguf, i + 0)}; + std::string counts_name{gguf_get_tensor_name(ctx_gguf, i + 1)}; + + if (sums_name.size() < sums_suffix.size() || + counts_name.size() < counts_suffix.size() || + !std::equal(sums_name.begin(), sums_name.end() - sums_suffix.size(), counts_name.begin()) || + !std::equal(sums_suffix.rbegin(), sums_suffix.rend(), sums_name.rbegin()) || + !std::equal(counts_suffix.rbegin(), counts_suffix.rend(), counts_name.rbegin())) { + fprintf(stderr, "%s: mismatched sums and counts for entry %d\n", __func__, i / 2); + gguf_free(ctx_gguf); + ggml_free(ctx); return false; } - name_as_vec[len] = 0; - std::string name{name_as_vec.data()}; - auto & e = m_stats[std::move(name)]; - int ncall; - in.read((char*)&ncall, sizeof(ncall)); - int nval; - in.read((char *)&nval, sizeof(nval)); - if (in.fail() || nval < 1) { - printf("%s: failed reading number of values for entry %d\n",__func__,i); - m_stats = {}; + + struct ggml_tensor * sums = ggml_get_tensor(ctx, sums_name.c_str()); + struct ggml_tensor * counts = ggml_get_tensor(ctx, counts_name.c_str()); + if (!sums || !counts) { + fprintf(stderr, "%s: failed reading data for entry %d\n", __func__, i / 2); + gguf_free(ctx_gguf); + ggml_free(ctx); return false; } + std::string name = sums_name.substr(0, sums_name.size() - sums_suffix.size()); + auto & e = m_stats[name]; + + int32_t nval = ggml_nelements(sums); if (e.values.empty()) { e.values.resize(nval, 0); - e.counts.resize(nval, 0); } - - std::vector tmp(nval); - in.read((char*)tmp.data(), nval*sizeof(float)); - if (in.fail()) { - printf("%s: failed reading data for entry %d\n",__func__,i); - m_stats = {}; - return false; + int32_t ncounts = ggml_nelements(counts); + if (e.counts.empty()) { + e.counts.resize(ncounts, 0); + } else if (e.counts.size() == 1 && ncounts > 1) { + // broadcast, when loading an old imatrix + e.counts.resize(ncounts, e.counts[0]); } - // Recreate the state as expected by save_imatrix(), and corerct for weighted sum. - for (int i = 0; i < nval; i++) { - e.values[i] += tmp[i]; - e.counts[i] += ncall; + // Recreate the state as expected by save_imatrix() + for (int32_t j = 0; j < nval; j++) { + e.values[j] += ((const float *) sums->data)[j]; + } + for (int32_t j = 0; j < ncounts; j++) { + e.counts[j] += std::lround(((const float *) counts->data)[j]); } - e.ncall += ncall; - } + gguf_free(ctx_gguf); + ggml_free(ctx); return true; } diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 7312309aeef98..2df073d45e8f1 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -6,8 +6,6 @@ #include #include #include -#include -#include struct quant_option { std::string name; @@ -61,6 +59,11 @@ static const char * const LLM_KV_QUANTIZE_IMATRIX_DATASET = "quantize.imatrix static const char * const LLM_KV_QUANTIZE_IMATRIX_N_ENTRIES = "quantize.imatrix.entries_count"; static const char * const LLM_KV_QUANTIZE_IMATRIX_N_CHUNKS = "quantize.imatrix.chunks_count"; +// TODO: share with imatrix.cpp +static const char * const LLM_KV_IMATRIX_DATASET = "imatrix.dataset"; +static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count"; +static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size"; + static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftype, std::string & ftype_str_out) { std::string ftype_str; @@ -121,66 +124,92 @@ static void usage(const char * executable) { } static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_dataset, std::unordered_map> & imatrix_data) { - std::ifstream in(imatrix_file.c_str(), std::ios::binary); - if (!in) { - printf("%s: failed to open %s\n",__func__, imatrix_file.c_str()); + + struct ggml_context * ctx = nullptr; + struct gguf_init_params meta_gguf_params = { + /* .no_alloc = */ false, // the data is needed + /* .ctx = */ &ctx, + }; + struct gguf_context * ctx_gguf = gguf_init_from_file(imatrix_file.c_str(), meta_gguf_params); + if (!ctx_gguf) { exit(1); } - int n_entries; - in.read((char *)&n_entries, sizeof(n_entries)); - if (in.fail() || n_entries < 1) { - printf("%s: no data in file %s\n", __func__, imatrix_file.c_str()); + const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); + if (n_entries < 2) { + fprintf(stderr, "%s: no data in file %s\n", __func__, imatrix_file.c_str()); + gguf_free(ctx_gguf); + ggml_free(ctx); exit(1); } - for (int i = 0; i < n_entries; ++i) { - int len; in.read((char *)&len, sizeof(len)); - std::vector name_as_vec(len+1); - in.read((char *)name_as_vec.data(), len); - if (in.fail()) { - printf("%s: failed reading name for entry %d from %s\n", __func__, i+1, imatrix_file.c_str()); - exit(1); - } - name_as_vec[len] = 0; - std::string name{name_as_vec.data()}; - auto & e = imatrix_data[name]; - int ncall; - in.read((char *)&ncall, sizeof(ncall)); - int nval; - in.read((char *)&nval, sizeof(nval)); - if (in.fail() || nval < 1) { - printf("%s: failed reading number of values for entry %d\n", __func__, i); - imatrix_data = {}; + + const int dataset_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASET); + const int chunk_count_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT); + const int chunk_size_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE); + if (dataset_idx < 0 || chunk_count_idx < 0 || chunk_size_idx < 0) { + fprintf(stderr, "%s: missing imatrix metadata in file %s\n", __func__, imatrix_file.c_str()); + gguf_free(ctx_gguf); + ggml_free(ctx); + exit(1); + } + + const uint32_t chunk_size = gguf_get_val_u32(ctx_gguf, chunk_size_idx); + + const std::string sums_suffix{".sums"}; + const std::string counts_suffix{".counts"}; + + // TODO: allow loading from mis-ordered imatrix files + for (int32_t i = 0; i < n_entries - 1; i += 2) { + std::string sums_name{gguf_get_tensor_name(ctx_gguf, i + 0)}; + std::string counts_name{gguf_get_tensor_name(ctx_gguf, i + 1)}; + + if (sums_name.size() < sums_suffix.size() || + counts_name.size() < counts_suffix.size() || + !std::equal(sums_name.begin(), sums_name.end() - sums_suffix.size(), counts_name.begin()) || + !std::equal(sums_suffix.rbegin(), sums_suffix.rend(), sums_name.rbegin()) || + !std::equal(counts_suffix.rbegin(), counts_suffix.rend(), counts_name.rbegin())) { + fprintf(stderr, "%s: mismatched sums and counts for entry %d\n", __func__, i / 2); + gguf_free(ctx_gguf); + ggml_free(ctx); exit(1); } - e.resize(nval); - in.read((char *)e.data(), nval*sizeof(float)); - if (in.fail()) { - printf("%s: failed reading data for entry %d\n", __func__, i); - imatrix_data = {}; + + struct ggml_tensor * sums = ggml_get_tensor(ctx, sums_name.c_str()); + struct ggml_tensor * counts = ggml_get_tensor(ctx, counts_name.c_str()); + if (!sums || !counts) { + fprintf(stderr, "%s: failed reading data for entry %d\n", __func__, i / 2); + gguf_free(ctx_gguf); + ggml_free(ctx); exit(1); } - if (ncall > 0) { - for (auto& v : e) v /= ncall; - } + const int64_t ne0 = sums->ne[0]; + const int64_t ne1 = sums->ne[1]; + std::string name = sums_name.substr(0, sums_name.size() - sums_suffix.size()); + auto & e = imatrix_data[name]; + e.resize(ggml_nelements(sums)); + float max_count = 0.0f; + for (int64_t j = 0; j < ne1; ++j) { + const float count = ((const float *) counts->data)[ne1]; + for (int64_t i = 0; i < ne0; ++i) { + e[ne1*ne0 + ne0] = ((const float *) sums->data)[ne1*ne0 + ne0] / count; + } + if (count > max_count) { + max_count = count; + } + } if (getenv("LLAMA_TRACE")) { - printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), ncall, name.c_str()); + printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), int(max_count / chunk_size), name.c_str()); } } + gguf_free(ctx_gguf); + ggml_free(ctx); - // latest imatrix version contains the dataset filename at the end of the file - int m_last_call = 0; - if (in.peek() != EOF) { - in.read((char *)&m_last_call, sizeof(m_last_call)); - int dataset_len; - in.read((char *)&dataset_len, sizeof(dataset_len)); - std::vector dataset_as_vec(dataset_len); - in.read(dataset_as_vec.data(), dataset_len); - imatrix_dataset.assign(dataset_as_vec.begin(), dataset_as_vec.end()); - printf("%s: imatrix dataset='%s'\n", __func__, imatrix_dataset.c_str()); - } - printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_call); - return m_last_call; + int m_last_chunk = gguf_get_val_u32(ctx_gguf, chunk_count_idx); + imatrix_dataset = gguf_get_val_str(ctx_gguf, dataset_idx); + + printf("%s: imatrix dataset='%s'\n", __func__, imatrix_dataset.c_str()); + printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_chunk); + return m_last_chunk; } static int prepare_imatrix(const std::string & imatrix_file, diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 5541972ce52b0..4fdeddb7c6648 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -167,6 +167,12 @@ class Adapter: TYPE = "adapter.type" LORA_ALPHA = "adapter.lora.alpha" + class IMatrix: + CHUNK_COUNT = "imatrix.chunk_count" + CHUNK_SIZE = "imatrix.chunk_size" + DATASET = "imatrix.dataset" + + # # recommended mapping of model tensor names for storage in gguf # @@ -175,6 +181,7 @@ class Adapter: class GGUFType: MODEL = "model" ADAPTER = "adapter" + IMATRIX = "imatrix" class MODEL_ARCH(IntEnum): From c8ab6a3ba356e902b94499baaf7ab0191c3b6afe Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Sun, 8 Sep 2024 10:04:01 -0400 Subject: [PATCH 04/16] imatrix : fix conversion problems --- convert_legacy_imatrix_to_gguf.py | 8 ++++++-- examples/imatrix/imatrix.cpp | 2 +- examples/quantize/quantize.cpp | 11 +++++++---- 3 files changed, 14 insertions(+), 7 deletions(-) diff --git a/convert_legacy_imatrix_to_gguf.py b/convert_legacy_imatrix_to_gguf.py index 939d3695b23ce..bd72655bf2cc7 100644 --- a/convert_legacy_imatrix_to_gguf.py +++ b/convert_legacy_imatrix_to_gguf.py @@ -64,10 +64,11 @@ def __init__(self, imatrix: Path): data = self._get(np.float32, nval) assert name not in self.entries, f"duplicated name: {name!r}" - self.entries[name] = IMatrixEntry(data, np.array([ncall * self.chunk_size], dtype=np.float32)) + self.entries[name] = IMatrixEntry(data * np.float32(self.chunk_size), np.array([ncall * self.chunk_size], dtype=np.float32)) self.chunk_count = self._get(np.int32).item() - self.dataset = self._get(np.uint8, self._get(np.int32).item()).tobytes().decode("utf-8") + dataset_len = self._get(np.int32).item() + self.dataset = self._get(np.uint8, dataset_len).tobytes().decode("utf-8") def to_writer(self, outfile: Path) -> IMatrixWriter: writer = IMatrixWriter(path=outfile, arch="") @@ -110,6 +111,9 @@ def parse_args(): input_file: Path = args.imatrix if input_file.suffix != ".gguf": args.outfile = input_file.with_suffix(".gguf") + if args.outfile.exists(): + logger.error(f"default file exists, specify with --outfile to overwrite: {args.outfile}") + exit(1) writer = IMatrixReader(args.imatrix).to_writer(args.outfile) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 2314a035d04fe..fea97918a682d 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -31,7 +31,7 @@ static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count"; static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size"; struct Stats { - std::vector values; + std::vector values; std::vector counts; }; diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 2df073d45e8f1..4f7003194d54b 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -132,6 +132,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ }; struct gguf_context * ctx_gguf = gguf_init_from_file(imatrix_file.c_str(), meta_gguf_params); if (!ctx_gguf) { + fprintf(stderr, "%s: if this is an older imatrix file, make sure to convert it to the GGUF-based imatrix format\n", __func__); exit(1); } const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); @@ -189,9 +190,9 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ e.resize(ggml_nelements(sums)); float max_count = 0.0f; for (int64_t j = 0; j < ne1; ++j) { - const float count = ((const float *) counts->data)[ne1]; + const float count = ((const float *) counts->data)[j]; for (int64_t i = 0; i < ne0; ++i) { - e[ne1*ne0 + ne0] = ((const float *) sums->data)[ne1*ne0 + ne0] / count; + e[j*ne0 + i] = ((const float *) sums->data)[j*ne0 + i] / count; } if (count > max_count) { max_count = count; @@ -201,14 +202,16 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), int(max_count / chunk_size), name.c_str()); } } - gguf_free(ctx_gguf); - ggml_free(ctx); int m_last_chunk = gguf_get_val_u32(ctx_gguf, chunk_count_idx); imatrix_dataset = gguf_get_val_str(ctx_gguf, dataset_idx); printf("%s: imatrix dataset='%s'\n", __func__, imatrix_dataset.c_str()); printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_chunk); + + gguf_free(ctx_gguf); + ggml_free(ctx); + return m_last_chunk; } From d19101c9a0e38359a303127bb5ccde47395ee083 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Sun, 8 Sep 2024 11:03:59 -0400 Subject: [PATCH 05/16] imatrix : use FMA and sort tensor names --- examples/imatrix/imatrix.cpp | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index e170714d84871..90ff9280cdda8 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -156,7 +156,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * e.counts[ex]++; for (int j = 0; j < (int)src1->ne[0]; ++j) { - e.values[e_start + j] += x[j]*x[j]; + e.values[e_start + j] = std::fma(x[j], x[j], e.values[e_start + j]); if (!std::isfinite((float)e.values[e_start + j])) { fprintf(stderr, "%f detected in %s\n", (float)e.values[e_start + j], wname.c_str()); exit(1); @@ -198,7 +198,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * const float * x = data + row * src1->ne[0]; e.counts[0]++; for (int j = 0; j < (int)src1->ne[0]; ++j) { - e.values[j] += x[j]*x[j]; + e.values[j] = std::fma(x[j], x[j], e.values[j]); if (!std::isfinite((float)e.values[j])) { fprintf(stderr, "%f detected in %s\n", (float)e.values[j], wname.c_str()); exit(1); @@ -279,6 +279,9 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { fprintf(stderr, "%s: warning: storing only %zu out of %zu entries\n", __func__, to_store.size(), m_stats.size()); } + // deterministic tensor name order + std::sort(to_store.begin(), to_store.end()); + struct ggml_init_params params = { .mem_size = data_size, .mem_buffer = NULL, From 503630e88a782184ecf42aaeb34cddd6cf6e9107 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Mon, 9 Sep 2024 21:56:04 -0400 Subject: [PATCH 06/16] py : add requirements for legacy imatrix convert script --- requirements/requirements-convert_legacy_imatrix_to_gguf.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 requirements/requirements-convert_legacy_imatrix_to_gguf.txt diff --git a/requirements/requirements-convert_legacy_imatrix_to_gguf.txt b/requirements/requirements-convert_legacy_imatrix_to_gguf.txt new file mode 100644 index 0000000000000..afe2747d448d4 --- /dev/null +++ b/requirements/requirements-convert_legacy_imatrix_to_gguf.txt @@ -0,0 +1 @@ +-r ./requirements-convert_legacy_llama.txt From 9e6b0e9419eb9738af12c8425d979831704c0d4b Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Mon, 9 Sep 2024 22:00:37 -0400 Subject: [PATCH 07/16] perplexity : revert changes --- examples/perplexity/perplexity.cpp | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/examples/perplexity/perplexity.cpp b/examples/perplexity/perplexity.cpp index ab5c51352fdf4..570ee8aeba4ae 100644 --- a/examples/perplexity/perplexity.cpp +++ b/examples/perplexity/perplexity.cpp @@ -583,9 +583,7 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par int n_outputs = 0; - // clear the batch - llama_batch_clear(batch); - + batch.n_tokens = 0; for (int seq = 0; seq < n_seq_batch; seq++) { int seq_start = batch_start + seq*n_ctx; @@ -598,10 +596,16 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par } for (int k = 0; k < batch_size; ++k) { - llama_pos pos = j*n_batch + k; - llama_batch_add(batch, tokens[seq_start + k], pos, { seq }, pos >= first); - n_outputs += (int) (pos >= first); + const int idx = seq*n_ctx + k; + batch.token [idx] = tokens[seq_start + k]; + batch.pos [idx] = j*n_batch + k; + batch.n_seq_id[idx] = 1; + batch.seq_id [idx][0] = seq; + batch.logits [idx] = batch.pos[idx] >= first ? 1 : 0; + + n_outputs += batch.logits[idx] != 0; } + batch.n_tokens += batch_size; // restore the original token in case it was set to BOS tokens[seq_start] = token_org; From 894ed8d7b68164852ab1b61600dbc6126d3deb40 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Mon, 9 Sep 2024 22:20:18 -0400 Subject: [PATCH 08/16] py : include imatrix converter requirements in toplevel requirements --- requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements.txt b/requirements.txt index 9e190ae27de38..98c53db8179e2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,5 +8,6 @@ -r ./requirements/requirements-convert_hf_to_gguf.txt -r ./requirements/requirements-convert_hf_to_gguf_update.txt +-r ./requirements/requirements-convert_legacy_imatrix_to_gguf.txt -r ./requirements/requirements-convert_llama_ggml_to_gguf.txt -r ./requirements/requirements-convert_lora_to_gguf.txt From efa9186dc861bed7f06057480ab3f208e588a99f Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Mon, 9 Sep 2024 22:33:10 -0400 Subject: [PATCH 09/16] imatrix : avoid using designated initializers in C++ --- examples/imatrix/imatrix.cpp | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 90ff9280cdda8..758542905f610 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -283,9 +283,9 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { std::sort(to_store.begin(), to_store.end()); struct ggml_init_params params = { - .mem_size = data_size, - .mem_buffer = NULL, - .no_alloc = false, + /* .mem_size = */ data_size, + /* .mem_buffer = */ NULL, + /* .no_alloc = */ false, }; struct ggml_context * ctx = ggml_init(params); struct gguf_context * ctx_gguf = gguf_init_empty(); From 221724705191554b14f112162414f276bfeb2b17 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Mon, 9 Sep 2024 22:35:47 -0400 Subject: [PATCH 10/16] imatrix : remove unused n_entries --- examples/imatrix/imatrix.cpp | 2 -- 1 file changed, 2 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 758542905f610..bcdc711533d83 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -235,7 +235,6 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { // avoid writing imatrix entries that do not have full data // this can happen with MoE models where some of the experts end up not being exercised by the provided training data - int n_entries = 0; std::vector to_store; size_t data_size = 0; @@ -269,7 +268,6 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { continue; } - n_entries++; to_store.push_back(kv.first); data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.values.size(), GGML_MEM_ALIGN); data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.counts.size(), GGML_MEM_ALIGN); From 8c13e16bb0f6b654ff4774e54fbc3b125ae495a6 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 10 Sep 2024 11:31:49 -0400 Subject: [PATCH 11/16] imatrix : allow loading mis-ordered tensors Sums and counts tensors no longer need to be consecutive. * imatrix : more sanity checks when loading multiple imatrix files * imatrix : use ggml_format_name instead of std::string concatenation Co-authored-by: Xuan Son Nguyen --- examples/imatrix/imatrix.cpp | 75 ++++++++++++++++++++++++---------- examples/quantize/quantize.cpp | 53 ++++++++++++++++-------- 2 files changed, 89 insertions(+), 39 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index bcdc711533d83..0e4cc8e683ec4 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -9,6 +9,7 @@ #include #include #include +#include #include #if defined(_MSC_VER) @@ -24,6 +25,14 @@ static void print_usage(int, char ** argv) { LOG_TEE("\n"); } +static bool str_remove_suffix(std::string & str, const std::string & suffix) { + bool has_suffix = str.size() >= suffix.size() && str.compare(str.size() - suffix.size(), str.size(), suffix) == 0; + if (has_suffix) { + str = str.substr(0, str.size() - suffix.size()); + } + return has_suffix; +} + static const char * const LLM_KV_IMATRIX_DATASET = "imatrix.dataset"; static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count"; static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size"; @@ -302,8 +311,8 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { if (nval > 0) { struct ggml_tensor * sums = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, nval / nmat, nmat); struct ggml_tensor * counts = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, nmat); - ggml_set_name(sums, (name + ".sums").c_str()); - ggml_set_name(counts, (name + ".counts").c_str()); + ggml_format_name(sums, "%s.sums", name.c_str()); + ggml_format_name(counts, "%s.counts", name.c_str()); for (int32_t j = 0; j < nval; ++j) { ((float *) sums->data)[j] = (float) stat.values[j]; @@ -338,7 +347,7 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { return false; } const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); - if (n_entries < 2) { + if (n_entries < 1) { fprintf(stderr, "%s: no data in file %s\n", __func__, file_name); gguf_free(ctx_gguf); ggml_free(ctx); @@ -348,51 +357,73 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { const std::string sums_suffix{".sums"}; const std::string counts_suffix{".counts"}; - // TODO: allow loading from mis-ordered imatrix files - for (int32_t i = 0; i < n_entries - 1; i += 2) { - std::string sums_name{gguf_get_tensor_name(ctx_gguf, i + 0)}; - std::string counts_name{gguf_get_tensor_name(ctx_gguf, i + 1)}; - - if (sums_name.size() < sums_suffix.size() || - counts_name.size() < counts_suffix.size() || - !std::equal(sums_name.begin(), sums_name.end() - sums_suffix.size(), counts_name.begin()) || - !std::equal(sums_suffix.rbegin(), sums_suffix.rend(), sums_name.rbegin()) || - !std::equal(counts_suffix.rbegin(), counts_suffix.rend(), counts_name.rbegin())) { - fprintf(stderr, "%s: mismatched sums and counts for entry %d\n", __func__, i / 2); + // Could re-use m_stats instead, but this allows + // checking for completeness of *each* loaded imatrix file + // and also makes it easier to re-use a similar implementation in quantize.cpp + // Using an ordered map to get a deterministic iteration order. + std::map> sums_counts_for; + + for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) { + std::string name = cur->name; + + if (name.empty()) { continue; } + + if (str_remove_suffix(name, sums_suffix)) { + // sums + sums_counts_for[name].first = cur; + } else if (str_remove_suffix(name, counts_suffix)) { + // counts + sums_counts_for[name].second = cur; + } else { + fprintf(stderr, "%s: invalid imatrix tensor name: %s\n", __func__, name.c_str()); gguf_free(ctx_gguf); ggml_free(ctx); return false; } + } + + for (const auto & sc : sums_counts_for) { + const std::string & name = sc.first; + const struct ggml_tensor * sums = sc.second.first; + const struct ggml_tensor * counts = sc.second.second; - struct ggml_tensor * sums = ggml_get_tensor(ctx, sums_name.c_str()); - struct ggml_tensor * counts = ggml_get_tensor(ctx, counts_name.c_str()); if (!sums || !counts) { - fprintf(stderr, "%s: failed reading data for entry %d\n", __func__, i / 2); + fprintf(stderr, "%s: mismatched sums and counts for %s\n", __func__, name.c_str()); gguf_free(ctx_gguf); ggml_free(ctx); return false; } - std::string name = sums_name.substr(0, sums_name.size() - sums_suffix.size()); auto & e = m_stats[name]; - int32_t nval = ggml_nelements(sums); + int64_t nval = ggml_nelements(sums); if (e.values.empty()) { e.values.resize(nval, 0); + } else if ((size_t) nval != e.values.size()) { + fprintf(stderr, "%s: mismatched sums size for %s: %zu != %zu\n", __func__, name.c_str(), (size_t) nval, e.values.size()); + gguf_free(ctx_gguf); + ggml_free(ctx); + return false; } - int32_t ncounts = ggml_nelements(counts); + + int64_t ncounts = ggml_nelements(counts); if (e.counts.empty()) { e.counts.resize(ncounts, 0); } else if (e.counts.size() == 1 && ncounts > 1) { // broadcast, when loading an old imatrix e.counts.resize(ncounts, e.counts[0]); + } else if ((size_t) ncounts != e.counts.size()) { + fprintf(stderr, "%s: mismatched counts size for %s: %zu != %zu\n", __func__, name.c_str(), (size_t) ncounts, e.counts.size()); + gguf_free(ctx_gguf); + ggml_free(ctx); + return false; } // Recreate the state as expected by save_imatrix() - for (int32_t j = 0; j < nval; j++) { + for (int64_t j = 0; j < nval; j++) { e.values[j] += ((const float *) sums->data)[j]; } - for (int32_t j = 0; j < ncounts; j++) { + for (int64_t j = 0; j < ncounts; j++) { e.counts[j] += std::lround(((const float *) counts->data)[j]); } } diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 78f55c4dfe556..99887cc7e1590 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -6,6 +6,7 @@ #include #include #include +#include struct quant_option { std::string name; @@ -125,6 +126,15 @@ static void usage(const char * executable) { exit(1); } +// TODO: share with implementation in imatrix.cpp +static bool str_remove_suffix(std::string & str, const std::string & suffix) { + bool has_suffix = str.size() >= suffix.size() && str.compare(str.size() - suffix.size(), str.size(), suffix) == 0; + if (has_suffix) { + str = str.substr(0, str.size() - suffix.size()); + } + return has_suffix; +} + static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_dataset, std::unordered_map> & imatrix_data) { struct ggml_context * ctx = nullptr; @@ -138,7 +148,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ exit(1); } const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); - if (n_entries < 2) { + if (n_entries < 1) { fprintf(stderr, "%s: no data in file %s\n", __func__, imatrix_file.c_str()); gguf_free(ctx_gguf); ggml_free(ctx); @@ -160,26 +170,35 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ const std::string sums_suffix{".sums"}; const std::string counts_suffix{".counts"}; - // TODO: allow loading from mis-ordered imatrix files - for (int32_t i = 0; i < n_entries - 1; i += 2) { - std::string sums_name{gguf_get_tensor_name(ctx_gguf, i + 0)}; - std::string counts_name{gguf_get_tensor_name(ctx_gguf, i + 1)}; - - if (sums_name.size() < sums_suffix.size() || - counts_name.size() < counts_suffix.size() || - !std::equal(sums_name.begin(), sums_name.end() - sums_suffix.size(), counts_name.begin()) || - !std::equal(sums_suffix.rbegin(), sums_suffix.rend(), sums_name.rbegin()) || - !std::equal(counts_suffix.rbegin(), counts_suffix.rend(), counts_name.rbegin())) { - fprintf(stderr, "%s: mismatched sums and counts for entry %d\n", __func__, i / 2); + // Using an ordered map to get a deterministic iteration order. + std::map> sums_counts_for; + + for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur; cur = ggml_get_next_tensor(ctx, cur)) { + std::string name = cur->name; + + if (name.empty()) { continue; } + + if (str_remove_suffix(name, sums_suffix)) { + // sums + sums_counts_for[name].first = cur; + } else if (str_remove_suffix(name, counts_suffix)) { + // counts + sums_counts_for[name].second = cur; + } else { + fprintf(stderr, "%s: invalid imatrix tensor name: %s\n", __func__, name.c_str()); gguf_free(ctx_gguf); ggml_free(ctx); exit(1); } + } + + for (const auto & sc : sums_counts_for) { + const std::string & name = sc.first; + const struct ggml_tensor * sums = sc.second.first; + const struct ggml_tensor * counts = sc.second.second; - struct ggml_tensor * sums = ggml_get_tensor(ctx, sums_name.c_str()); - struct ggml_tensor * counts = ggml_get_tensor(ctx, counts_name.c_str()); if (!sums || !counts) { - fprintf(stderr, "%s: failed reading data for entry %d\n", __func__, i / 2); + fprintf(stderr, "%s: mismatched sums and counts for %s\n", __func__, name.c_str()); gguf_free(ctx_gguf); ggml_free(ctx); exit(1); @@ -187,7 +206,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ const int64_t ne0 = sums->ne[0]; const int64_t ne1 = sums->ne[1]; - std::string name = sums_name.substr(0, sums_name.size() - sums_suffix.size()); + auto & e = imatrix_data[name]; e.resize(ggml_nelements(sums)); float max_count = 0.0f; @@ -201,7 +220,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ } } if (getenv("LLAMA_TRACE")) { - printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), int(max_count / chunk_size), name.c_str()); + printf("%s: loaded data (size = %6d, n_tokens = %6d) for '%s'\n", __func__, int(e.size()), int(max_count), name.c_str()); } } From 2d79a7077cb9a7218c1f40d637233658db7349e0 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 10 Sep 2024 12:09:17 -0400 Subject: [PATCH 12/16] quantize : use unused imatrix chunk_size with LLAMA_TRACE --- examples/quantize/quantize.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 99887cc7e1590..0cde695ed5046 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -220,7 +220,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ } } if (getenv("LLAMA_TRACE")) { - printf("%s: loaded data (size = %6d, n_tokens = %6d) for '%s'\n", __func__, int(e.size()), int(max_count), name.c_str()); + printf("%s: loaded data (size = %6d, n_tokens = %6d, n_chunks = %6d) for '%s'\n", __func__, int(e.size()), int(max_count), int(max_count / chunk_size), name.c_str()); } } From c7a32e761dc96c559d6227b1fe4996ae1445b07a Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Thu, 30 Jan 2025 19:56:20 -0500 Subject: [PATCH 13/16] common : use GGUF for imatrix output by default --- common/common.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/common/common.h b/common/common.h index d7c08f20a124b..d10ec6235ed18 100644 --- a/common/common.h +++ b/common/common.h @@ -275,7 +275,7 @@ struct gpt_params { int32_t i_pos = -1; // position of the passkey in the junk text // imatrix params - std::string out_file = "imatrix.dat"; // save the resulting imatrix to this file + std::string out_file = "imatrix.gguf"; // save the resulting imatrix to this file int32_t n_out_freq = 10; // output the imatrix every n_out_freq iterations int32_t n_save_freq = 0; // save the imatrix every n_save_freq iterations From a5165a6ca93a16270deda5feea7a1ae3f876b793 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 15 Apr 2025 17:29:57 -0400 Subject: [PATCH 14/16] imatrix : two-way conversion between old format and GGUF --- examples/imatrix/imatrix.cpp | 293 ++++++++++++++++++++++++++++----- examples/quantize/quantize.cpp | 145 ++++++++++++---- 2 files changed, 365 insertions(+), 73 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index 1b537407f5fcb..f49bf9ec41e18 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -12,6 +12,7 @@ #include #include #include +#include #include #include #include @@ -29,15 +30,19 @@ static void print_usage(int, char ** argv) { LOG("\n"); } +static bool str_has_suffix(const std::string & str, const std::string & suffix) { + return str.size() >= suffix.size() && str.compare(str.size() - suffix.size(), str.size(), suffix) == 0; +} + static bool str_remove_suffix(std::string & str, const std::string & suffix) { - bool has_suffix = str.size() >= suffix.size() && str.compare(str.size() - suffix.size(), str.size(), suffix) == 0; + bool has_suffix = str_has_suffix(str, suffix); if (has_suffix) { str = str.substr(0, str.size() - suffix.size()); } return has_suffix; } -static const char * const LLM_KV_IMATRIX_DATASET = "imatrix.dataset"; +static const char * const LLM_KV_IMATRIX_DATASETS = "imatrix.datasets"; static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count"; static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size"; @@ -51,12 +56,15 @@ class IMatrixCollector { IMatrixCollector() = default; void set_params(common_params params) { m_params = std::move(params); } bool collect_imatrix(struct ggml_tensor * t, bool ask, void * user_data); + void save_imatrix_legacy(int32_t ncall = -1) const; void save_imatrix(int32_t n_chunk = -1) const; + bool load_imatrix_legacy(const char * fname); bool load_imatrix(const char * file_name); private: std::unordered_map m_stats; common_params m_params; std::mutex m_mutex; + std::vector m_datasets; int32_t m_last_chunk = 0; std::vector m_src1_data; std::vector m_ids; // the expert ids from ggml_mul_mat_id @@ -88,6 +96,8 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * const struct ggml_tensor * src1 = t->src[1]; std::string wname = filter_tensor_name(src0->name); + const int32_t chunk_size = m_params.n_ctx / m_params.n_parallel; + // when ask is true, the scheduler wants to know if we are interested in data from this tensor // if we return true, a follow-up call will be made with ask=false in which we can do the actual collection if (ask) { @@ -175,7 +185,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * } } } - const int32_t n_chunk = e.counts[ex] / (m_params.n_ctx / m_params.n_parallel); + const int32_t n_chunk = e.counts[ex] / chunk_size; if (n_chunk > m_last_chunk) { const int32_t chunk_step = n_chunk - m_last_chunk; m_last_chunk = n_chunk; @@ -214,7 +224,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * } } } - const int32_t n_chunk = e.counts[0] / (m_params.n_ctx / m_params.n_parallel); + const int32_t n_chunk = e.counts[0] / chunk_size; if (n_chunk > m_last_chunk) { const int32_t chunk_step = n_chunk - m_last_chunk; m_last_chunk = n_chunk; @@ -230,19 +240,19 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * return true; } -void IMatrixCollector::save_imatrix(int32_t n_chunk) const { +void IMatrixCollector::save_imatrix_legacy(int32_t ncall) const { auto fname = m_params.out_file; - if (n_chunk > 0) { + if (ncall > 0) { fname += ".at_"; - fname += std::to_string(n_chunk); + fname += std::to_string(ncall); } // avoid writing imatrix entries that do not have full data // this can happen with MoE models where some of the experts end up not being exercised by the provided training data + int n_entries = 0; std::vector to_store; - size_t data_size = 0; bool is_first = true; // for printing for (const auto & kv : m_stats) { @@ -274,9 +284,8 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { continue; } + n_entries++; to_store.push_back(kv.first); - data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.values.size(), GGML_MEM_ALIGN); - data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.counts.size(), GGML_MEM_ALIGN); } if (to_store.size() < m_stats.size()) { @@ -286,6 +295,79 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { // deterministic tensor name order std::sort(to_store.begin(), to_store.end()); + const int32_t chunk_size = m_params.n_ctx / m_params.n_parallel; + + std::ofstream out(fname, std::ios::binary); + out.write((const char *) &n_entries, sizeof(n_entries)); + for (const auto & name : to_store) { + const auto & stat = m_stats.at(name); + const int32_t len = name.size(); + out.write((const char *) &len, sizeof(len)); + out.write(name.c_str(), len); + const int32_t ncall = *std::max_element(stat.counts.begin(), stat.counts.end()) / chunk_size; + out.write((const char *) &ncall, sizeof(ncall)); + const int32_t nval = stat.values.size(); + const int32_t nmat = stat.counts.size(); + out.write((const char *) &nval, sizeof(nval)); + if (nval > 0 && nmat > 0) { + std::vector tmp(nval); + for (int32_t i = 0; i < nval; i++) { + const float counts = static_cast(stat.counts[i / (nval / nmat)]); + tmp[i] = (stat.values[i] / counts) * static_cast(ncall); + } + out.write((const char *) tmp.data(), nval * sizeof(float)); + } + } + + // Write the number of call the matrix was computed with + out.write((const char *) &m_last_chunk, sizeof(m_last_chunk)); + + // Write the input filename at the end of the file to later on specify it in quantize + { + const char * dataset_file = m_params.prompt_file.c_str(); + int32_t len = m_params.prompt_file.size(); + // When there is no prompt but there were other imatrix files loaded, use the last dataset + if (m_params.prompt_file.empty() && !m_datasets.empty()) { + const std::string & dataset_str = m_datasets[m_datasets.size() - 1]; + dataset_file = dataset_str.c_str(); + len = dataset_str.size(); + } + out.write((const char *) &len, sizeof(len)); + out.write(dataset_file, len); + } + + LOGV(1, "\n"); + LOG_DBGV(1, "%s: stored collected data after %d chunks in %s\n", __func__, m_last_chunk, fname.c_str()); +} + +void IMatrixCollector::save_imatrix(int32_t n_chunk) const { + auto fname = m_params.out_file; + + // TODO: use the new format by default also for .imatrix + if (!str_has_suffix(fname, ".gguf")) { + return this->save_imatrix_legacy(n_chunk); + } + + if (n_chunk > 0) { + fname += ".at_"; + fname += std::to_string(n_chunk); + } + + // write imatrix entries even if they don't have full data. (can be corrected when reading) + // this can happen with MoE models where some of the experts end up not being exercised by the provided training data + + std::vector to_store; + size_t data_size = 0; + + for (const auto & kv : m_stats) { + to_store.push_back(kv.first); + data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.values.size(), GGML_MEM_ALIGN); + data_size += GGML_PAD(ggml_tensor_overhead() + sizeof(float) * kv.second.counts.size(), GGML_MEM_ALIGN); + } + + // deterministic tensor name order + std::sort(to_store.begin(), to_store.end()); + struct ggml_init_params params = { /* .mem_size = */ data_size, /* .mem_buffer = */ NULL, @@ -294,31 +376,42 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { struct ggml_context * ctx = ggml_init(params); struct gguf_context * ctx_gguf = gguf_init_empty(); - gguf_set_val_str(ctx_gguf, "general.type", "imatrix"); - // Write the input filename to later on specify it in quantize - gguf_set_val_str(ctx_gguf, LLM_KV_IMATRIX_DATASET, m_params.prompt_file.c_str()); - // Write the number of chunks the matrix was computed with - gguf_set_val_u32(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT, m_last_chunk); - gguf_set_val_u32(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE, m_params.n_ctx / m_params.n_parallel); + { + std::vector datasets; + datasets.reserve(m_datasets.size() + 1); + for (size_t i = 0; i < m_datasets.size(); ++i) { + datasets.push_back(m_datasets[i].c_str()); + } + if (!m_params.prompt_file.empty()) { + datasets.push_back(m_params.prompt_file.c_str()); + } + + gguf_set_val_str(ctx_gguf, "general.type", "imatrix"); + // Write the dataset paths + gguf_set_arr_str(ctx_gguf, LLM_KV_IMATRIX_DATASETS, datasets.data(), datasets.size()); + // Write the number of chunks the matrix was computed with + gguf_set_val_u32(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT, m_last_chunk); + gguf_set_val_u32(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE, m_params.n_ctx / m_params.n_parallel); + } for (const auto & name : to_store) { const auto & stat = m_stats.at(name); const int32_t nval = (int32_t) stat.values.size(); const int32_t nmat = (int32_t) stat.counts.size(); - if (nval > 0) { - struct ggml_tensor * sums = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, nval / nmat, nmat); - struct ggml_tensor * counts = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, nmat); - ggml_format_name(sums, "%s.sums", name.c_str()); + if (nval > 0 && nmat > 0) { + struct ggml_tensor * in_sum2 = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, nval / nmat, nmat); + struct ggml_tensor * counts = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, nmat); + ggml_format_name(in_sum2, "%s.in_sum2", name.c_str()); ggml_format_name(counts, "%s.counts", name.c_str()); for (int32_t j = 0; j < nval; ++j) { - ((float *) sums->data)[j] = (float) stat.values[j]; + ((float *) in_sum2->data)[j] = (float) stat.values[j]; } for (int32_t j = 0; j < nmat; ++j) { ((float *) counts->data)[j] = (float) stat.counts[j]; } - gguf_add_tensor(ctx_gguf, sums); + gguf_add_tensor(ctx_gguf, in_sum2); gguf_add_tensor(ctx_gguf, counts); } } @@ -332,6 +425,105 @@ void IMatrixCollector::save_imatrix(int32_t n_chunk) const { ggml_free(ctx); } +bool IMatrixCollector::load_imatrix_legacy(const char * fname) { + std::ifstream in(fname, std::ios::binary); + if (!in) { + LOG_ERR("%s: failed to open %s\n", __func__, fname); + return false; + } + int n_entries; + in.read((char *) &n_entries, sizeof(n_entries)); + if (in.fail() || n_entries < 1) { + LOG_ERR("%s: no data in file %s\n", __func__, fname); + return false; + } + // Guess the chunk size because it's not stored in the file + const int32_t chunk_size = m_params.n_ctx / m_params.n_parallel; + + for (int i = 0; i < n_entries; ++i) { + int32_t len = 0; + in.read((char *) &len, sizeof(len)); + std::vector name_as_vec(len + 1); + in.read((char *) name_as_vec.data(), len); + if (in.fail()) { + LOG_ERR("%s: failed reading name for entry %d from %s\n", __func__, i + 1, fname); + return false; + } + name_as_vec[len] = 0; + std::string name{ name_as_vec.data() }; + auto & e = m_stats[std::move(name)]; + int32_t ncall = 0; + in.read((char *) &ncall, sizeof(ncall)); + int32_t nval = 0; + in.read((char *) &nval, sizeof(nval)); + if (in.fail() || nval < 1) { + LOG_ERR("%s: failed reading number of values for entry %d\n", __func__, i); + m_stats = {}; + return false; + } + + if (e.values.empty()) { + e.values.resize(nval, 0.0f); + e.counts.resize(1, 0); + } + + std::vector tmp(nval); + in.read((char *) tmp.data(), nval * sizeof(float)); + if (in.fail()) { + LOG_ERR("%s: failed reading data for entry %d\n", __func__, i); + m_stats = {}; + return false; + } + + // Recreate the state as expected by save_imatrix(), and correct for weighted sum. + for (int i = 0; i < nval; i++) { + e.values[i] += tmp[i] * chunk_size; + } + // The legacy format doesn't distinguish the counts for different experts + for (size_t j = 0; j < e.counts.size(); ++j) { + e.counts[j] += ncall * chunk_size; + } + } + + { + // TODO: extract into its own method; this is also used by the GGUF-based format + // Calculate the last chunk count + int64_t max_count = 0; + for (const auto & stats : m_stats) { + for (int64_t count : stats.second.counts) { + if (count > max_count) { + max_count = count; + } + } + } + m_last_chunk = max_count / (chunk_size); + } + + { + // Read the number of calls the matrix was computed with + int32_t n_calls; + in.read((char *) &n_calls, sizeof(n_calls)); + // ignore it because it's not important + } + + // Read the dataset path to include it when writing to GGUF + if (!in.fail()){ + int32_t len = 0; + in.read((char *) &len, sizeof(len)); + if (!in.fail()) { + std::vector dataset; + dataset.resize(len + 1, 0); + in.read(dataset.data(), len); + if (!in.fail()) { + m_datasets.push_back(dataset.data()); + } + } + } + + return true; +} + +// Using GGUF as the file format, for greater extensibility bool IMatrixCollector::load_imatrix(const char * file_name) { struct ggml_context * ctx = nullptr; struct gguf_init_params meta_gguf_params = { @@ -340,7 +532,7 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { }; struct gguf_context * ctx_gguf = gguf_init_from_file(file_name, meta_gguf_params); if (!ctx_gguf) { - return false; + return this->load_imatrix_legacy(file_name); } const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); if (n_entries < 1) { @@ -350,8 +542,17 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { return false; } - const std::string sums_suffix{".sums"}; - const std::string counts_suffix{".counts"}; + const int64_t datasets_key = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASETS); + if (datasets_key != -1 && gguf_get_arr_type(ctx_gguf, datasets_key) == GGUF_TYPE_STRING) { + const int64_t n = gguf_get_arr_n(ctx_gguf, datasets_key); + m_datasets.reserve(m_datasets.size() + n); + for (int64_t i = 0; i < n; ++i) { + m_datasets.push_back(gguf_get_arr_str(ctx_gguf, datasets_key, i)); + } + } + + const std::string in_sum2_suffix{ ".in_sum2" }; + const std::string counts_suffix{ ".counts" }; // Could re-use m_stats instead, but this allows // checking for completeness of *each* loaded imatrix file @@ -364,26 +565,23 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { if (name.empty()) { continue; } - if (str_remove_suffix(name, sums_suffix)) { - // sums - sums_counts_for[name].first = cur; + if (str_remove_suffix(name, in_sum2_suffix)) { + // in_sum2 + sums_counts_for[std::move(name)].first = cur; } else if (str_remove_suffix(name, counts_suffix)) { // counts - sums_counts_for[name].second = cur; + sums_counts_for[std::move(name)].second = cur; } else { - LOG_ERR("%s: invalid imatrix tensor name: %s\n", __func__, name.c_str()); - gguf_free(ctx_gguf); - ggml_free(ctx); - return false; + // ignore other tensors } } for (const auto & sc : sums_counts_for) { - const std::string & name = sc.first; - const struct ggml_tensor * sums = sc.second.first; - const struct ggml_tensor * counts = sc.second.second; + const std::string & name = sc.first; + const struct ggml_tensor * in_sum2 = sc.second.first; + const struct ggml_tensor * counts = sc.second.second; - if (!sums || !counts) { + if (!in_sum2 || !counts) { LOG_ERR("%s: mismatched sums and counts for %s\n", __func__, name.c_str()); gguf_free(ctx_gguf); ggml_free(ctx); @@ -392,9 +590,9 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { auto & e = m_stats[name]; - int64_t nval = ggml_nelements(sums); + int64_t nval = ggml_nelements(in_sum2); if (e.values.empty()) { - e.values.resize(nval, 0); + e.values.resize(nval, 0.0f); } else if ((size_t) nval != e.values.size()) { LOG_ERR("%s: mismatched sums size for %s: %zu != %zu\n", __func__, name.c_str(), (size_t) nval, e.values.size()); gguf_free(ctx_gguf); @@ -417,12 +615,25 @@ bool IMatrixCollector::load_imatrix(const char * file_name) { // Recreate the state as expected by save_imatrix() for (int64_t j = 0; j < nval; j++) { - e.values[j] += ((const float *) sums->data)[j]; + e.values[j] += ((const float *) in_sum2->data)[j]; } for (int64_t j = 0; j < ncounts; j++) { e.counts[j] += std::lround(((const float *) counts->data)[j]); } } + + // TODO: extract into its own method; this is also used by the legacy format + // Calculate the last chunk count + int64_t max_count = 0; + for (const auto & stats : m_stats) { + for (int64_t count : stats.second.counts) { + if (count > max_count) { + max_count = count; + } + } + } + m_last_chunk = max_count / (m_params.n_ctx / m_params.n_parallel); + gguf_free(ctx_gguf); ggml_free(ctx); return true; @@ -685,7 +896,7 @@ static bool compute_imatrix(llama_context * ctx, const common_params & params, c int main(int argc, char ** argv) { common_params params; - params.out_file = "imatrix.dat" ; + params.out_file = "imatrix.gguf" ; params.n_ctx = 512; params.logits_all = true; diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 7f2afe6575677..1a37cf316f4de 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -64,7 +64,7 @@ static const char * const LLM_KV_QUANTIZE_IMATRIX_N_ENTRIES = "quantize.imatrix static const char * const LLM_KV_QUANTIZE_IMATRIX_N_CHUNKS = "quantize.imatrix.chunks_count"; // TODO: share with imatrix.cpp -static const char * const LLM_KV_IMATRIX_DATASET = "imatrix.dataset"; +static const char * const LLM_KV_IMATRIX_DATASETS = "imatrix.datasets"; static const char * const LLM_KV_IMATRIX_CHUNK_COUNT = "imatrix.chunk_count"; static const char * const LLM_KV_IMATRIX_CHUNK_SIZE = "imatrix.chunk_size"; @@ -84,7 +84,7 @@ static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftyp for (auto ch : ftype_str_in) { ftype_str.push_back(std::toupper(ch)); } - for (auto & it : QUANT_OPTIONS) { + for (const auto & it : QUANT_OPTIONS) { if (striequals(it.name.c_str(), ftype_str.c_str())) { ftype = it.ftype; ftype_str_out = it.name; @@ -93,7 +93,7 @@ static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftyp } try { int ftype_int = std::stoi(ftype_str); - for (auto & it : QUANT_OPTIONS) { + for (const auto & it : QUANT_OPTIONS) { if (it.ftype == ftype_int) { ftype = it.ftype; ftype_str_out = it.name; @@ -126,7 +126,7 @@ static void usage(const char * executable) { printf(" Advanced option to override model metadata by key in the quantized model. May be specified multiple times.\n"); printf("Note: --include-weights and --exclude-weights cannot be used together\n"); printf("\nAllowed quantization types:\n"); - for (auto & it : QUANT_OPTIONS) { + for (const auto & it : QUANT_OPTIONS) { if (it.name != "COPY") { printf(" %2d or ", it.ftype); } else { @@ -146,7 +146,71 @@ static bool str_remove_suffix(std::string & str, const std::string & suffix) { return has_suffix; } -static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_dataset, std::unordered_map> & imatrix_data) { +static int load_legacy_imatrix(const std::string & imatrix_file, std::vector & imatrix_datasets, std::unordered_map> & imatrix_data) { + std::ifstream in(imatrix_file.c_str(), std::ios::binary); + if (!in) { + printf("%s: failed to open %s\n",__func__, imatrix_file.c_str()); + exit(1); + } + int n_entries; + in.read((char *)&n_entries, sizeof(n_entries)); + if (in.fail() || n_entries < 1) { + printf("%s: no data in file %s\n", __func__, imatrix_file.c_str()); + exit(1); + } + for (int i = 0; i < n_entries; ++i) { + int len; in.read((char *)&len, sizeof(len)); + std::vector name_as_vec(len+1); + in.read((char *)name_as_vec.data(), len); + if (in.fail()) { + printf("%s: failed reading name for entry %d from %s\n", __func__, i+1, imatrix_file.c_str()); + exit(1); + } + name_as_vec[len] = 0; + std::string name{name_as_vec.data()}; + auto & e = imatrix_data[name]; + int ncall; + in.read((char *)&ncall, sizeof(ncall)); + int nval; + in.read((char *)&nval, sizeof(nval)); + if (in.fail() || nval < 1) { + printf("%s: failed reading number of values for entry %d\n", __func__, i); + imatrix_data = {}; + exit(1); + } + e.resize(nval); + in.read((char *)e.data(), nval*sizeof(float)); + if (in.fail()) { + printf("%s: failed reading data for entry %d\n", __func__, i); + imatrix_data = {}; + exit(1); + } + if (ncall > 0) { + for (auto& v : e) v /= ncall; + } + + if (getenv("LLAMA_TRACE")) { + printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), ncall, name.c_str()); + } + } + + // latest imatrix version contains the dataset filename at the end of the file + int m_last_call = 0; + if (in.peek() != EOF) { + in.read((char *)&m_last_call, sizeof(m_last_call)); + int dataset_len; + in.read((char *)&dataset_len, sizeof(dataset_len)); + std::vector dataset_as_vec(dataset_len); + in.read(dataset_as_vec.data(), dataset_len); + imatrix_datasets.resize(1); + imatrix_datasets[0].assign(dataset_as_vec.begin(), dataset_as_vec.end()); + printf("%s: imatrix dataset='%s'\n", __func__, imatrix_datasets[0].c_str()); + } + printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_call); + return m_last_call; +} + +static int load_imatrix(const std::string & imatrix_file, std::vector & imatrix_datasets, std::unordered_map> & imatrix_data) { struct ggml_context * ctx = nullptr; struct gguf_init_params meta_gguf_params = { @@ -155,8 +219,8 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ }; struct gguf_context * ctx_gguf = gguf_init_from_file(imatrix_file.c_str(), meta_gguf_params); if (!ctx_gguf) { - fprintf(stderr, "%s: if this is an older imatrix file, make sure to convert it to the GGUF-based imatrix format\n", __func__); - exit(1); + fprintf(stderr, "%s: imatrix file '%s' is using old format\n", __func__, imatrix_file.c_str()); + return load_legacy_imatrix(imatrix_file, imatrix_datasets, imatrix_data); } const int32_t n_entries = gguf_get_n_tensors(ctx_gguf); if (n_entries < 1) { @@ -166,7 +230,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ exit(1); } - const int dataset_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASET); + const int dataset_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_DATASETS); const int chunk_count_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_COUNT); const int chunk_size_idx = gguf_find_key(ctx_gguf, LLM_KV_IMATRIX_CHUNK_SIZE); if (dataset_idx < 0 || chunk_count_idx < 0 || chunk_size_idx < 0) { @@ -178,8 +242,8 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ const uint32_t chunk_size = gguf_get_val_u32(ctx_gguf, chunk_size_idx); - const std::string sums_suffix{".sums"}; - const std::string counts_suffix{".counts"}; + const std::string sums_suffix{ ".in_sum2" }; + const std::string counts_suffix{ ".counts" }; // Using an ordered map to get a deterministic iteration order. std::map> sums_counts_for; @@ -190,16 +254,13 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ if (name.empty()) { continue; } if (str_remove_suffix(name, sums_suffix)) { - // sums - sums_counts_for[name].first = cur; + // in_sum2 + sums_counts_for[std::move(name)].first = cur; } else if (str_remove_suffix(name, counts_suffix)) { // counts - sums_counts_for[name].second = cur; + sums_counts_for[std::move(name)].second = cur; } else { - fprintf(stderr, "%s: invalid imatrix tensor name: %s\n", __func__, name.c_str()); - gguf_free(ctx_gguf); - ggml_free(ctx); - exit(1); + // ignore other tensors } } @@ -223,8 +284,15 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ float max_count = 0.0f; for (int64_t j = 0; j < ne1; ++j) { const float count = ((const float *) counts->data)[j]; - for (int64_t i = 0; i < ne0; ++i) { - e[j*ne0 + i] = ((const float *) sums->data)[j*ne0 + i] / count; + if (count > 0.0f) { + for (int64_t i = 0; i < ne0; ++i) { + e[j*ne0 + i] = ((const float *) sums->data)[j*ne0 + i] / count; + } + } else { + // Partial imatrix data, this tensor never got any input during calibration + for (int64_t i = 0; i < ne0; ++i) { + e[j*ne0 + i] = 1; + } } if (count > max_count) { max_count = count; @@ -236,9 +304,18 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ } int m_last_chunk = gguf_get_val_u32(ctx_gguf, chunk_count_idx); - imatrix_dataset = gguf_get_val_str(ctx_gguf, dataset_idx); - printf("%s: imatrix dataset='%s'\n", __func__, imatrix_dataset.c_str()); + int64_t n_datasets = gguf_get_arr_n(ctx_gguf, dataset_idx); + imatrix_datasets.resize(n_datasets); + for (int64_t i = 0; i < n_datasets; ++i) { + imatrix_datasets.push_back(gguf_get_val_str(ctx_gguf, dataset_idx)); + } + printf("%s: imatrix datasets=['%s'", __func__, imatrix_datasets[0].c_str()); + for (size_t i = 1; i < imatrix_datasets.size(); ++i) { + printf(", '%s'", imatrix_datasets[i].c_str()); + } + printf("]\n"); + printf("%s: loaded %d importance matrix entries from %s computed on %d chunks\n", __func__, int(imatrix_data.size()), imatrix_file.c_str(), m_last_chunk); gguf_free(ctx_gguf); @@ -248,7 +325,7 @@ static int load_imatrix(const std::string & imatrix_file, std::string & imatrix_ } static int prepare_imatrix(const std::string & imatrix_file, - std::string & imatrix_dataset, + std::vector & imatrix_dataset, const std::vector & included_weights, const std::vector & excluded_weights, std::unordered_map> & imatrix_data) { @@ -260,18 +337,21 @@ static int prepare_imatrix(const std::string & imatrix_file, return m_last_call; } if (!excluded_weights.empty()) { - for (auto& name : excluded_weights) { - for (auto it = imatrix_data.begin(); it != imatrix_data.end(); ) { + for (const auto & name : excluded_weights) { + for (auto it = imatrix_data.begin(); it != imatrix_data.end();) { auto pos = it->first.find(name); - if (pos != std::string::npos) it = imatrix_data.erase(it); - else ++it; + if (pos != std::string::npos) { + it = imatrix_data.erase(it); + } else { + ++it; + } } } } if (!included_weights.empty()) { std::unordered_map> tmp; - for (auto& name : included_weights) { - for (auto& e : imatrix_data) { + for (const auto & name : included_weights) { + for (auto & e : imatrix_data) { auto pos = e.first.find(name); if (pos != std::string::npos) { tmp.emplace(std::move(e)); @@ -372,9 +452,9 @@ int main(int argc, char ** argv) { usage(argv[0]); } - std::string imatrix_dataset; + std::vector imatrix_datasets; std::unordered_map> imatrix_data; - int m_last_call = prepare_imatrix(imatrix_file, imatrix_dataset, included_weights, excluded_weights, imatrix_data); + int m_last_call = prepare_imatrix(imatrix_file, imatrix_datasets, included_weights, excluded_weights, imatrix_data); if (!imatrix_data.empty()) { params.imatrix = &imatrix_data; { @@ -385,11 +465,12 @@ int main(int argc, char ** argv) { kvo.val_str[127] = '\0'; kv_overrides.emplace_back(std::move(kvo)); } - if (!imatrix_dataset.empty()) { + if (!imatrix_datasets.empty()) { llama_model_kv_override kvo; + // TODO: list multiple datasets when there are more than one std::strcpy(kvo.key, LLM_KV_QUANTIZE_IMATRIX_DATASET); kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR; - strncpy(kvo.val_str, imatrix_dataset.c_str(), 127); + strncpy(kvo.val_str, imatrix_datasets[0].c_str(), 127); kvo.val_str[127] = '\0'; kv_overrides.emplace_back(std::move(kvo)); } From 635f945ed12ae95d55c733f81e8d96e4802a2a93 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 15 Apr 2025 17:42:26 -0400 Subject: [PATCH 15/16] convert : remove imatrix to gguf python script --- convert_legacy_imatrix_to_gguf.py | 122 ------------------ gguf-py/gguf/constants.py | 2 +- requirements.txt | 1 - ...rements-convert_legacy_imatrix_to_gguf.txt | 1 - 4 files changed, 1 insertion(+), 125 deletions(-) delete mode 100644 convert_legacy_imatrix_to_gguf.py delete mode 100644 requirements/requirements-convert_legacy_imatrix_to_gguf.txt diff --git a/convert_legacy_imatrix_to_gguf.py b/convert_legacy_imatrix_to_gguf.py deleted file mode 100644 index bd72655bf2cc7..0000000000000 --- a/convert_legacy_imatrix_to_gguf.py +++ /dev/null @@ -1,122 +0,0 @@ -#!/usr/bin/env python3 - -from __future__ import annotations - -import os -import sys -import logging -import argparse - -from typing import Any -from pathlib import Path -from dataclasses import dataclass - -import numpy as np -import numpy.typing as npt - -if 'NO_LOCAL_GGUF' not in os.environ: - sys.path.insert(1, str(Path(__file__).parent / 'gguf-py')) -import gguf - - -logger = logging.getLogger("imatrix-to-gguf") - - -class IMatrixWriter(gguf.GGUFWriter): - def add_architecture(self) -> None: - # no arch is stored in imatrix files - pass - - -@dataclass -class IMatrixEntry: - values: np.ndarray[Any, np.dtype[np.float32]] - counts: np.ndarray[Any, np.dtype[np.float32]] - - -class IMatrixReader: - chunk_size: int = 512 # guess - offset: int = 0 - data: np.ndarray[Any, np.dtype[np.uint8]] - n_enties: int - entries: dict[str, IMatrixEntry] - chunk_count: int - dataset: str - - def _get(self, dtype: npt.DTypeLike, count: int = 1) -> npt.NDArray[Any]: - count = int(count) - itemsize = int(np.empty([], dtype=dtype).itemsize) - offset = self.offset - self.offset = offset + itemsize * count - return self.data[offset:self.offset].view(dtype=dtype)[:count] - - def __init__(self, imatrix: Path): - self.offset = 0 - self.entries = {} - self.data = np.memmap(imatrix) - n_entries = self._get(np.int32).item() - assert n_entries >= 0 - for _ in range(n_entries): - len = self._get(np.int32).item() - name = self._get(np.uint8, len).tobytes().decode("utf-8") - ncall = self._get(np.int32).item() - nval = self._get(np.int32).item() - data = self._get(np.float32, nval) - assert name not in self.entries, f"duplicated name: {name!r}" - - self.entries[name] = IMatrixEntry(data * np.float32(self.chunk_size), np.array([ncall * self.chunk_size], dtype=np.float32)) - - self.chunk_count = self._get(np.int32).item() - dataset_len = self._get(np.int32).item() - self.dataset = self._get(np.uint8, dataset_len).tobytes().decode("utf-8") - - def to_writer(self, outfile: Path) -> IMatrixWriter: - writer = IMatrixWriter(path=outfile, arch="") - - writer.add_type(gguf.GGUFType.IMATRIX) - writer.add_key_value(gguf.Keys.IMatrix.CHUNK_COUNT, self.chunk_count, gguf.GGUFValueType.UINT32) - writer.add_key_value(gguf.Keys.IMatrix.CHUNK_SIZE, self.chunk_size, gguf.GGUFValueType.UINT32) - writer.add_key_value(gguf.Keys.IMatrix.DATASET, self.dataset, gguf.GGUFValueType.STRING) - - for name, entry in self.entries.items(): - writer.add_tensor(name + ".sums", entry.values) - writer.add_tensor(name + ".counts", entry.counts) - - return writer - - -def parse_args(): - parser = argparse.ArgumentParser( - description="Convert an old imatrix.dat file to a GGUF compatible file") - parser.add_argument( - "--outfile", type=Path, - help="path to write to; default: based on input.", - ) - parser.add_argument( - "--verbose", action="store_true", - help="increase output verbosity", - ) - parser.add_argument( - "imatrix", type=Path, - help="path to an imatrix file", - ) - return parser.parse_args() - - -if __name__ == "__main__": - args = parse_args() - logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO) - - if args.outfile is None: - input_file: Path = args.imatrix - if input_file.suffix != ".gguf": - args.outfile = input_file.with_suffix(".gguf") - if args.outfile.exists(): - logger.error(f"default file exists, specify with --outfile to overwrite: {args.outfile}") - exit(1) - - writer = IMatrixReader(args.imatrix).to_writer(args.outfile) - - writer.write_header_to_file(args.outfile) - writer.write_kv_data_to_file() - writer.write_tensors_to_file() diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py index 5b4b0e9edb48a..c2dbf7b643dc5 100644 --- a/gguf-py/gguf/constants.py +++ b/gguf-py/gguf/constants.py @@ -219,7 +219,7 @@ class Adapter: class IMatrix: CHUNK_COUNT = "imatrix.chunk_count" CHUNK_SIZE = "imatrix.chunk_size" - DATASET = "imatrix.dataset" + DATASETS = "imatrix.datasets" # diff --git a/requirements.txt b/requirements.txt index cf3116c6cb6ac..f2a18d62879b4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,7 +8,6 @@ -r ./requirements/requirements-convert_hf_to_gguf.txt -r ./requirements/requirements-convert_hf_to_gguf_update.txt --r ./requirements/requirements-convert_legacy_imatrix_to_gguf.txt -r ./requirements/requirements-convert_llama_ggml_to_gguf.txt -r ./requirements/requirements-convert_lora_to_gguf.txt -r ./requirements/requirements-tool_bench.txt diff --git a/requirements/requirements-convert_legacy_imatrix_to_gguf.txt b/requirements/requirements-convert_legacy_imatrix_to_gguf.txt deleted file mode 100644 index afe2747d448d4..0000000000000 --- a/requirements/requirements-convert_legacy_imatrix_to_gguf.txt +++ /dev/null @@ -1 +0,0 @@ --r ./requirements-convert_legacy_llama.txt From 1d19025909ae3abbc26c50bb8795c2f351fe4ba1 Mon Sep 17 00:00:00 2001 From: Francis Couture-Harpin Date: Tue, 15 Apr 2025 17:48:06 -0400 Subject: [PATCH 16/16] imatrix : use the function name in more error messages --- examples/imatrix/imatrix.cpp | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/examples/imatrix/imatrix.cpp b/examples/imatrix/imatrix.cpp index f49bf9ec41e18..fdbc97a5e1513 100644 --- a/examples/imatrix/imatrix.cpp +++ b/examples/imatrix/imatrix.cpp @@ -154,7 +154,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * exit(1); //GGML_ABORT("fatal error"); } else if (e.counts.size() != (size_t)n_as) { - LOG_ERR("Oops: inconsistent expert count for %s (%d vs %d)\n", wname.c_str(), (int)e.counts.size(), (int)n_as); + LOG_ERR("%s: inconsistent expert count for %s (%d vs %d)\n", __func__, wname.c_str(), (int)e.counts.size(), (int)n_as); exit(1); //GGML_ABORT("fatal error"); } LOG_DBGV(2, "%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_chunk, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[2], (int)src1->type); @@ -208,7 +208,7 @@ bool IMatrixCollector::collect_imatrix(struct ggml_tensor * t, bool ask, void * exit(1); //GGML_ABORT("fatal error"); } else if (e.counts.size() != 1) { - LOG_ERR("Oops: inconsistent expert count for %s (%d vs %d)\n", wname.c_str(), (int)e.counts.size(), 1); + LOG_ERR("%s: inconsistent expert count for %s (%d vs %d)\n", __func__, wname.c_str(), (int)e.counts.size(), 1); exit(1); //GGML_ABORT("fatal error"); } LOG_DBGV(2, "%s[%d]: %32s, %s, %5d x %5d, %d\n", __func__, m_last_chunk, wname.c_str(), ggml_op_name(t->op), (int)src1->ne[0], (int)src1->ne[1], (int)src1->type); @@ -819,7 +819,7 @@ static bool compute_imatrix(llama_context * ctx, const common_params & params, c // (not possible when this skips FFN computation of the last layer) common_batch_add(batch, tokens[seq_start + k], j*n_batch + k, { seq }, true); } - + // restore the original token in case it was set to BOS tokens[seq_start] = token_org; } @@ -896,7 +896,7 @@ static bool compute_imatrix(llama_context * ctx, const common_params & params, c int main(int argc, char ** argv) { common_params params; - params.out_file = "imatrix.gguf" ; + params.out_file = "imatrix.gguf"; params.n_ctx = 512; params.logits_all = true;