ggml : remove bit shuffling (#1405)
* ggml : remove Q4_0 bit shufling (ARM NEON)
* ggml : remove Q4_1 bit shuffling (ARM NEON + reference)
* ggml : nibbles_from_floats() + bytes_from_nibbles() (ARM NEON)
* ggml : remove Q4_2 bit shuffling (WIP, BROKEN)
* ggml : remove Q5_0 bit shuffling (ARM NEON)
* ggml : 2x faster scalar implementations
* ggml : remove Q5_1 bit shuffling (ARM NEON + scalar)
* ggml : simplify scalar dot
* ggml : remove WASM SIMD bit shuffling + remove vzip for ARM 32-bit
* ggml : fix Q4_1 quantization
* ggml : update cuBLAS + normalize variable names
* ggml : remove Q4_2 mode
* ggml : minor formatting
* ggml : fix Q5_0 quantization
* scripts : add script for measuring the time per token
* AVX implementations (#1370)
* ggml : uniform 5th bit extraction
* llama : produce error upon loading old model files
* llama : fix model magic/version write
* ggml : speed-up Q5_0 + Q5_1 at 4 threads
* ggml : preserve old Q4 and Q5 formats
* ggml : simplify Q8_1 - no need for low / high sums anymore
* ggml : fix Q8_0 and Q8_1 rounding
* Revert "AVX implementations (#1370)"
This reverts commit 948d124837
.
* ggml : fix AVX2 implementation
* sha : update hashes for 7B and 13B
* readme : update timings + remove warning banner
* llama : update v2 PR number to 1405
* ggml : fix WASM comments
* ggml : back to original bit order
* readme : add note that Q4 and Q5 have been changed
* llama : fix return for unknown version
---------
Co-authored-by: Stephan Walter <stephan@walter.name>
This commit is contained in:
parent
b608b55a3e
commit
b9fd7eee57
12 changed files with 650 additions and 1687 deletions
29
llama.cpp
29
llama.cpp
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@ -402,6 +402,7 @@ enum llama_file_version {
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LLAMA_FILE_VERSION_GGML,
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LLAMA_FILE_VERSION_GGMF_V1, // added version field and scores in vocab
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LLAMA_FILE_VERSION_GGJT_V1, // added padding
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LLAMA_FILE_VERSION_GGJT_V2, // changed quantization format
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};
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struct llama_file_loader {
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@ -432,6 +433,8 @@ struct llama_file_loader {
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file_version = LLAMA_FILE_VERSION_GGMF_V1;
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} else if (magic == 'ggjt' && version == 1) {
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file_version = LLAMA_FILE_VERSION_GGJT_V1;
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} else if (magic == 'ggjt' && version == 2) {
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file_version = LLAMA_FILE_VERSION_GGJT_V2;
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} else {
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throw format("unknown (magic, version) combination: %08x, %08x; is this really a GGML file?",
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magic, version);
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@ -482,7 +485,6 @@ struct llama_file_loader {
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case GGML_TYPE_F16:
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case GGML_TYPE_Q4_0:
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case GGML_TYPE_Q4_1:
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case GGML_TYPE_Q4_2:
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case GGML_TYPE_Q5_0:
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case GGML_TYPE_Q5_1:
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case GGML_TYPE_Q8_0:
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@ -527,8 +529,8 @@ struct llama_file_saver {
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write_vocab();
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}
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void write_magic() {
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file.write_u32('ggjt'); // magic
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file.write_u32(1); // version
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file.write_u32(LLAMA_FILE_MAGIC); // magic
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file.write_u32(LLAMA_FILE_VERSION); // version
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}
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void write_hparams(enum llama_ftype new_ftype) {
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const llama_hparams & hparams = any_file_loader->hparams;
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@ -558,7 +560,6 @@ struct llama_file_saver {
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case GGML_TYPE_F16:
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case GGML_TYPE_Q4_0:
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case GGML_TYPE_Q4_1:
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case GGML_TYPE_Q4_2:
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case GGML_TYPE_Q5_0:
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case GGML_TYPE_Q5_1:
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case GGML_TYPE_Q8_0:
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@ -839,9 +840,11 @@ static const char *llama_file_version_name(llama_file_version version) {
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switch (version) {
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case LLAMA_FILE_VERSION_GGML: return "'ggml' (old version with low tokenizer quality and no mmap support)";
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case LLAMA_FILE_VERSION_GGMF_V1: return "ggmf v1 (old version with no mmap support)";
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case LLAMA_FILE_VERSION_GGJT_V1: return "ggjt v1 (latest)";
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default: LLAMA_ASSERT(false);
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case LLAMA_FILE_VERSION_GGJT_V1: return "ggjt v1 (pre #1405)";
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case LLAMA_FILE_VERSION_GGJT_V2: return "ggjt v2 (latest)";
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}
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return "unknown";
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}
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static const char *llama_ftype_name(enum llama_ftype ftype) {
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@ -852,7 +855,6 @@ static const char *llama_ftype_name(enum llama_ftype ftype) {
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case LLAMA_FTYPE_MOSTLY_Q4_1: return "mostly Q4_1";
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case LLAMA_FTYPE_MOSTLY_Q4_1_SOME_F16:
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return "mostly Q4_1, some F16";
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case LLAMA_FTYPE_MOSTLY_Q4_2: return "mostly Q4_2";
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case LLAMA_FTYPE_MOSTLY_Q5_0: return "mostly Q5_0";
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case LLAMA_FTYPE_MOSTLY_Q5_1: return "mostly Q5_1";
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case LLAMA_FTYPE_MOSTLY_Q8_0: return "mostly Q8_0";
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@ -918,6 +920,14 @@ static void llama_model_load_internal(
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fprintf(stderr, "%s: model size = %s\n", __func__, llama_model_type_name(model.type));
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}
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if (file_version != LLAMA_FILE_VERSION_GGJT_V2) {
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if (hparams.ftype != LLAMA_FTYPE_ALL_F32 &&
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hparams.ftype != LLAMA_FTYPE_MOSTLY_F16 &&
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hparams.ftype != LLAMA_FTYPE_MOSTLY_Q8_0) {
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throw format("this format is no longer supported (see https://github.com/ggerganov/llama.cpp/pull/1305)");
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}
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}
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if (vocab_only) {
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return;
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}
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@ -1905,7 +1915,6 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
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switch (ftype) {
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case LLAMA_FTYPE_MOSTLY_Q4_0: quantized_type = GGML_TYPE_Q4_0; break;
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case LLAMA_FTYPE_MOSTLY_Q4_1: quantized_type = GGML_TYPE_Q4_1; break;
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case LLAMA_FTYPE_MOSTLY_Q4_2: quantized_type = GGML_TYPE_Q4_2; break;
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case LLAMA_FTYPE_MOSTLY_Q5_0: quantized_type = GGML_TYPE_Q5_0; break;
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case LLAMA_FTYPE_MOSTLY_Q5_1: quantized_type = GGML_TYPE_Q5_1; break;
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case LLAMA_FTYPE_MOSTLY_Q8_0: quantized_type = GGML_TYPE_Q8_0; break;
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@ -2813,9 +2822,9 @@ void llama_print_timings(struct llama_context * ctx) {
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fprintf(stderr, "\n");
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fprintf(stderr, "%s: load time = %8.2f ms\n", __func__, ctx->t_load_us / 1000.0);
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fprintf(stderr, "%s: sample time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3 * ctx->t_sample_us, n_sample, 1e-3 * ctx->t_sample_us / n_sample);
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fprintf(stderr, "%s: sample time = %8.2f ms / %5d runs (%8.2f ms per token)\n", __func__, 1e-3 * ctx->t_sample_us, n_sample, 1e-3 * ctx->t_sample_us / n_sample);
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fprintf(stderr, "%s: prompt eval time = %8.2f ms / %5d tokens (%8.2f ms per token)\n", __func__, 1e-3 * ctx->t_p_eval_us, n_p_eval, 1e-3 * ctx->t_p_eval_us / n_p_eval);
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fprintf(stderr, "%s: eval time = %8.2f ms / %5d runs (%8.2f ms per run)\n", __func__, 1e-3 * ctx->t_eval_us, n_eval, 1e-3 * ctx->t_eval_us / n_eval);
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fprintf(stderr, "%s: eval time = %8.2f ms / %5d runs (%8.2f ms per token)\n", __func__, 1e-3 * ctx->t_eval_us, n_eval, 1e-3 * ctx->t_eval_us / n_eval);
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fprintf(stderr, "%s: total time = %8.2f ms\n", __func__, (t_end_us - ctx->t_start_us)/1000.0);
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}
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