diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 909eab283ee6e..a5515f451536b 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -31,17 +31,17 @@ static const std::vector QUANT_OPTIONS = { { "IQ3_XXS",LLAMA_FTYPE_MOSTLY_IQ3_XXS," 3.06 bpw quantization", }, { "IQ3_S", LLAMA_FTYPE_MOSTLY_IQ3_S, " 3.44 bpw quantization", }, { "IQ3_M", LLAMA_FTYPE_MOSTLY_IQ3_M, " 3.66 bpw quantization mix", }, - { "Q3_K", LLAMA_FTYPE_MOSTLY_Q3_K_M, "alias for Q3_K_M" }, + { "Q3_K", LLAMA_FTYPE_MOSTLY_Q3_K_M, "alias for Q3_K_M" }, { "IQ3_XS", LLAMA_FTYPE_MOSTLY_IQ3_XS, " 3.3 bpw quantization" , }, { "Q3_K_S", LLAMA_FTYPE_MOSTLY_Q3_K_S, " 2.75G, +0.5551 ppl @ LLaMA-v1-7B", }, { "Q3_K_M", LLAMA_FTYPE_MOSTLY_Q3_K_M, " 3.07G, +0.2496 ppl @ LLaMA-v1-7B", }, { "Q3_K_L", LLAMA_FTYPE_MOSTLY_Q3_K_L, " 3.35G, +0.1764 ppl @ LLaMA-v1-7B", }, { "IQ4_NL", LLAMA_FTYPE_MOSTLY_IQ4_NL, " 4.50 bpw non-linear quantization", }, { "IQ4_XS", LLAMA_FTYPE_MOSTLY_IQ4_XS, " 4.25 bpw non-linear quantization", }, - { "Q4_K", LLAMA_FTYPE_MOSTLY_Q4_K_M, "alias for Q4_K_M", }, + { "Q4_K", LLAMA_FTYPE_MOSTLY_Q4_K_M, "alias for Q4_K_M", }, { "Q4_K_S", LLAMA_FTYPE_MOSTLY_Q4_K_S, " 3.59G, +0.0992 ppl @ LLaMA-v1-7B", }, { "Q4_K_M", LLAMA_FTYPE_MOSTLY_Q4_K_M, " 3.80G, +0.0532 ppl @ LLaMA-v1-7B", }, - { "Q5_K", LLAMA_FTYPE_MOSTLY_Q5_K_M, "alias for Q5_K_M", }, + { "Q5_K", LLAMA_FTYPE_MOSTLY_Q5_K_M, "alias for Q5_K_M", }, { "Q5_K_S", LLAMA_FTYPE_MOSTLY_Q5_K_S, " 4.33G, +0.0400 ppl @ LLaMA-v1-7B", }, { "Q5_K_M", LLAMA_FTYPE_MOSTLY_Q5_K_M, " 4.45G, +0.0122 ppl @ LLaMA-v1-7B", }, { "Q6_K", LLAMA_FTYPE_MOSTLY_Q6_K, " 5.15G, +0.0008 ppl @ LLaMA-v1-7B", }, @@ -49,8 +49,9 @@ static const std::vector QUANT_OPTIONS = { { "F16", LLAMA_FTYPE_MOSTLY_F16, "14.00G, -0.0020 ppl @ Mistral-7B", }, { "BF16", LLAMA_FTYPE_MOSTLY_BF16, "14.00G, -0.0050 ppl @ Mistral-7B", }, { "F32", LLAMA_FTYPE_ALL_F32, "26.00G @ 7B", }, + { "CUSTOM", LLAMA_FTYPE_CUSTOM, "[:filename] Custom quant config (quant.cfg if not specified", }, // Note: Ensure COPY comes after F32 to avoid ftype 0 from matching. - { "COPY", LLAMA_FTYPE_ALL_F32, "only copy tensors, no quantizing", }, + { "COPY", LLAMA_FTYPE_ALL_F32, "only copy tensors, no quantizing", }, }; static const char * const LLM_KV_QUANTIZE_IMATRIX_FILE = "quantize.imatrix.file"; @@ -58,12 +59,33 @@ 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"; -static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftype, std::string & ftype_str_out) { +static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftype, std::string & ftype_str_out, std::string & custom_cfg_filename_out) { std::string ftype_str; for (auto ch : ftype_str_in) { ftype_str.push_back(std::toupper(ch)); } + + if (ftype_str.find("CUSTOM:") == 0) { + // custom quant mix + ftype = LLAMA_FTYPE_CUSTOM; + ftype_str_out = "CUSTOM"; + if (ftype_str.length() > 7) { + // extract config filename (take from ftype_str_in to get original casing) + std::string custom_cfg = ftype_str_in.substr(7); + custom_cfg_filename_out = custom_cfg; + } else { + return false; + } + return true; + } else if (ftype_str.find("CUSTOM") == 0) { + // custom quant mix with default config + ftype = LLAMA_FTYPE_CUSTOM; + ftype_str_out = "CUSTOM"; + custom_cfg_filename_out = "quant.cfg"; + return true; + } + for (auto & it : QUANT_OPTIONS) { if (it.name == ftype_str) { ftype = it.ftype; @@ -224,13 +246,119 @@ static ggml_type parse_ggml_type(const char * arg) { for (int j = 0; j < GGML_TYPE_COUNT; ++j) { auto type = ggml_type(j); const auto * name = ggml_type_name(type); - if (name && strcmp(arg, name) == 0) { + if (name && strcasecmp(arg, name) == 0) { result = type; break; } } return result; } +static bool parse_kv_override(const char * data, std::vector & overrides) { + const char* sep = strchr(data, '='); + if (sep == nullptr || sep - data >= 128) { + fprintf(stderr, "%s: malformed KV override '%s'\n", __func__, data); + return false; + } + llama_model_kv_override kvo; + std::strncpy(kvo.key, data, sep - data); + kvo.key[sep - data] = 0; + sep++; + if (strncmp(sep, "int:", 4) == 0) { + sep += 4; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; + kvo.int_value = std::atol(sep); + } else if (strncmp(sep, "float:", 6) == 0) { + sep += 6; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT; + kvo.float_value = std::atof(sep); + } else if (strncmp(sep, "bool:", 5) == 0) { + sep += 5; + kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL; + if (std::strcmp(sep, "true") == 0) { + kvo.bool_value = true; + } else if (std::strcmp(sep, "false") == 0) { + kvo.bool_value = false; + } else { + fprintf(stderr, "%s: invalid boolean value for KV override '%s'\n", __func__, data); + return false; + } + } else { + fprintf(stderr, "%s: invalid type for KV override '%s'\n", __func__, data); + return false; + } + overrides.emplace_back(std::move(kvo)); + return true; +} + +static bool read_custom_quant_config(const std::string& filename, llama_model_quantize_ftype_override& override) { + std::ifstream file(filename); + std::string line; + std::vector names; + std::vector types; + + printf("reading custom quantization mix from %s:\n", filename.c_str()); + + if (!file.is_open()) { + fprintf(stderr, "%s: failed to open file: '%s'\n", __func__, filename.c_str()); + return false; + } + + while (getline(file, line)) { + // skip empty lines and comments + if (line.empty() || line[0] == '#') continue; + + // default file type + if (line.find("ftype=") == 0) { + std::string ftype_str = line.substr(6); + std::string ftype_name; + std::string custom_quant_config_filename; + llama_ftype ftype; + if(!try_parse_ftype(ftype_str, ftype, ftype_name, custom_quant_config_filename)) { + fprintf(stderr, "%s: invalid ftype '%s'\n", __func__, ftype_str.c_str()); + file.close(); + return false; + } + + override.default_ftype = static_cast(ftype); + printf(" default ftype = %i (%s)\n", ftype, ftype_name.c_str()); + continue; + } + + // tensor overrides + size_t pos = line.find('='); + if (pos != std::string::npos) { + std::string tensor_name = line.substr(0, pos); + std::string type_name = line.substr(pos + 1); + ggml_type type = parse_ggml_type(type_name.c_str()); + if(type < 0 || type >= GGML_TYPE_COUNT) { + fprintf(stderr, "%s: invalid ggml_type '%s'\n", __func__, type_name.c_str()); + file.close(); + return false; + } + names.push_back(tensor_name); + types.push_back(static_cast(type)); + printf(" %s = %i (%s)\n", tensor_name.c_str(), type, type_name.c_str()); + + } + } + + printf("\n"); + + // allocate memory for names and types + override.names = new const char*[names.size()]; + override.types = new ggml_type[types.size()]; + override.count = names.size(); + + for (size_t i = 0; i < names.size(); ++i) { + override.names[i] = strdup(names[i].c_str()); + override.types[i] = types[i]; + } + + file.close(); + + return true; +} + int main(int argc, char ** argv) { if (argc < 3) { usage(argv[0]); @@ -349,10 +477,11 @@ int main(int argc, char ** argv) { const std::string fname_inp = argv[arg_idx]; arg_idx++; std::string fname_out; + std::string custom_quant_config_filename; std::string ftype_str; std::string suffix = ".gguf"; - if (try_parse_ftype(argv[arg_idx], params.ftype, ftype_str)) { + if (try_parse_ftype(argv[arg_idx], params.ftype, ftype_str, custom_quant_config_filename)) { std::string fpath; const size_t pos = fname_inp.find_last_of("/\\"); if (pos != std::string::npos) { @@ -379,13 +508,23 @@ int main(int argc, char ** argv) { fprintf(stderr, "%s: missing ftype\n", __func__); return 1; } - if (!try_parse_ftype(argv[arg_idx], params.ftype, ftype_str)) { + + if (!try_parse_ftype(argv[arg_idx], params.ftype, ftype_str, custom_quant_config_filename)) { fprintf(stderr, "%s: invalid ftype '%s'\n", __func__, argv[3]); return 1; } + if (ftype_str == "COPY") { params.only_copy = true; } + + if (ftype_str == "CUSTOM") { + params.override_ftype = new llama_model_quantize_ftype_override; + if(!read_custom_quant_config(custom_quant_config_filename, *params.override_ftype)) { + return 1; + } + } + arg_idx++; } diff --git a/llama.cpp b/llama.cpp index 7572f8d56be29..7bccdf80e6cfe 100644 --- a/llama.cpp +++ b/llama.cpp @@ -3700,6 +3700,9 @@ static std::string llama_model_ftype_name(llama_ftype ftype) { case LLAMA_FTYPE_MOSTLY_IQ3_S: return "IQ3_S - 3.4375 bpw"; case LLAMA_FTYPE_MOSTLY_IQ3_M: return "IQ3_S mix - 3.66 bpw"; + // Custom quantization scheme + case LLAMA_FTYPE_CUSTOM: return "CUSTOM"; + default: return "unknown, may not work"; } } @@ -14570,11 +14573,35 @@ static size_t llama_tensor_quantize_internal(enum ggml_type new_type, const floa return new_size; } +static bool match_string(const std::string& str, const std::string& pattern, uint32_t string_index = 0, uint32_t pattern_index = 0) { + // if both index pointers reach the end of str and pattern respectively + if (string_index == str.size() && pattern_index == pattern.size()) { + return true; + } + + // if pattern character is '*', it can match with any sequence of characters. + if (pattern_index < pattern.size() && pattern[pattern_index] == '*') { + // move pattern index by 1 and match rest, or keep string index same and move pattern index + return match_string(str, pattern, string_index, pattern_index + 1) || (string_index < str.size() && match_string(str, pattern, string_index + 1, pattern_index)); + } + + // if current characters match or pattern character is '?' + if (string_index < str.size() && pattern_index < pattern.size() && (str[string_index] == pattern[pattern_index] || pattern[pattern_index] == '?')) { + return match_string(str, pattern, string_index + 1, pattern_index + 1); + } + + return false; +} + static void llama_model_quantize_internal(const std::string & fname_inp, const std::string & fname_out, const llama_model_quantize_params * params) { ggml_type default_type; - llama_ftype ftype = params->ftype; - switch (params->ftype) { + llama_ftype ftype = + params->override_ftype + ? params->override_ftype->default_ftype + : params->ftype; + + switch (ftype) { case LLAMA_FTYPE_MOSTLY_Q4_0: default_type = GGML_TYPE_Q4_0; break; case LLAMA_FTYPE_MOSTLY_Q4_1: default_type = GGML_TYPE_Q4_1; break; case LLAMA_FTYPE_MOSTLY_Q5_0: default_type = GGML_TYPE_Q5_0; break; @@ -14657,7 +14684,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s // copy the KV pairs from the input file gguf_set_kv (ctx_out, ml.meta); gguf_set_val_u32(ctx_out, "general.quantization_version", GGML_QNT_VERSION); - gguf_set_val_u32(ctx_out, "general.file_type", ftype); + gguf_set_val_u32(ctx_out, "general.file_type", params->ftype); // Remove split metadata gguf_remove_key(ctx_out, ml.llm_kv(LLM_KV_SPLIT_NO).c_str()); gguf_remove_key(ctx_out, ml.llm_kv(LLM_KV_SPLIT_COUNT).c_str()); @@ -14845,6 +14872,18 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s new_type = params->output_tensor_type; } + // look up tensor name in type override map, if not found use default + // type as determined by the ftype. + if(params->override_ftype) { + for (uint32_t i = 0; i < params->override_ftype->count; ++i) { + if (match_string(tensor->name, params->override_ftype->names[i])) { + // printf("\n -----> %s, %s\n", params->override_ftype->names[i], tensor->name); + new_type = params->override_ftype->types[i]; + break; + } + } + } + // If we've decided to quantize to the same type the tensor is already // in then there's nothing to do. quantize = tensor->type != new_type; @@ -15309,7 +15348,8 @@ struct llama_model_quantize_params llama_model_quantize_default_params() { /*.pure =*/ false, /*.keep_split =*/ false, /*.imatrix =*/ nullptr, - /*.kv_overrides =*/ nullptr, + /*.kv_overrides =*/ nullptr, + /*.override_ftype =*/ nullptr }; return result; diff --git a/llama.h b/llama.h index 0b2e708d06dea..23a12ff577c80 100644 --- a/llama.h +++ b/llama.h @@ -140,6 +140,7 @@ extern "C" { LLAMA_FTYPE_MOSTLY_IQ4_XS = 30, // except 1d tensors LLAMA_FTYPE_MOSTLY_IQ1_M = 31, // except 1d tensors LLAMA_FTYPE_MOSTLY_BF16 = 32, // except 1d tensors + LLAMA_FTYPE_CUSTOM = 33, // except 1d tensors LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file }; @@ -302,6 +303,13 @@ extern "C" { void * abort_callback_data; }; + typedef struct llama_model_quantize_ftype_override { + enum llama_ftype default_ftype; // default type if not overriden + uint32_t count; // number of overrides + const char ** names; // tensor names + enum ggml_type * types; // tensor type override + } llama_model_quantize_custom_ftype; + // model quantization parameters typedef struct llama_model_quantize_params { int32_t nthread; // number of threads to use for quantizing, if <=0 will use std::thread::hardware_concurrency() @@ -310,11 +318,12 @@ extern "C" { enum ggml_type token_embedding_type; // itoken embeddings tensor type bool allow_requantize; // allow quantizing non-f32/f16 tensors bool quantize_output_tensor; // quantize output.weight - bool only_copy; // only copy tensors - ftype, allow_requantize and quantize_output_tensor are ignored + bool only_copy; // only copy tensors - ftype, override_ftype, allow_requantize and quantize_output_tensor are ignored bool pure; // quantize all tensors to the default type bool keep_split; // quantize to the same number of shards void * imatrix; // pointer to importance matrix data void * kv_overrides; // pointer to vector containing overrides + struct llama_model_quantize_ftype_override * override_ftype; // custom quantization scheme } llama_model_quantize_params; // grammar types diff --git a/quant.cfg b/quant.cfg new file mode 100644 index 0000000000000..282442b4feed4 --- /dev/null +++ b/quant.cfg @@ -0,0 +1,36 @@ +# Defines the default ftype (the quantization mix code, +# that you pass to quantize if you're not using custom mix). +# tensors that are not overriden below will be quantized +# according to this mix. +# +# Must be one of +# Q4_0, Q4_1, Q5_0, Q5_1, IQ2_XXS, IQ2_XS, IQ2_S, IQ2_M, +# IQ1_S, IQ1_M, Q2_K, Q2_K_S, IQ3_XXS, IQ3_S, IQ3_M, Q3_K, +# IQ3_XS, Q3_K_S, Q3_K_M, Q3_K_L, IQ4_NL, IQ4_XS, Q4_K, +# Q4_K_S, Q4_K_M, Q5_K, Q5_K_S, Q5_K_M, Q6_K, Q8_0, F16 + +ftype=Q6_K + +# Defines overrides for tensors with names matching a given +# string. Filters are processed in order given, the first +# matching will be used. +# +# Wildcards are allowed: +# ? single character +# * multiple characters +# +# Type must be one of +# F16, Q4_0, Q4_1, Q5_0, Q5_1, Q8_0, Q8_1, Q2_K, Q3_K, +# Q4_K, Q5_K, Q6_K, Q8_K, IQ2_XXS, IQ2_XS, IQ3_XXS, +# IQ1_S, IQ4_NL, IQ3_S, IQ2_S, IQ4_XS, IQ1_M + +blk.10.ffn_up.weight=Q5_K +blk.1?.ffn_up.weight=Q4_K +blk.23.*=Q2_K +blk.24.*=Q2_K +blk.25.*=Q2_K +blk.2?.ffn_up.weight=Q4_K +*_gate*=Q4_K +*.attn*=IQ4_XS +*_down*=IQ3_S +output.weight=Q5_K