diff --git a/examples/whisper/CMakeLists.txt b/examples/whisper/CMakeLists.txt index c8fa83a..c7f5ff5 100644 --- a/examples/whisper/CMakeLists.txt +++ b/examples/whisper/CMakeLists.txt @@ -13,3 +13,10 @@ set(TEST_TARGET whisper) add_executable(${TEST_TARGET} main.cpp common.cpp) target_link_libraries(${TEST_TARGET} PRIVATE whisper-cpp) target_include_directories(${TEST_TARGET} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/..) + +# +# whisper-quantize + +set(TEST_TARGET whisper-quantize) +add_executable(${TEST_TARGET} quantize.cpp) +target_link_libraries(${TEST_TARGET} PRIVATE ggml ggml_utils) diff --git a/examples/whisper/convert-pt-to-ggml.py b/examples/whisper/convert-pt-to-ggml.py index 9e9b2dc..749f99c 100644 --- a/examples/whisper/convert-pt-to-ggml.py +++ b/examples/whisper/convert-pt-to-ggml.py @@ -303,8 +303,9 @@ for name in list_vars.keys(): data = data.astype(np.float32) ftype = 0 else: - data = data.astype(np.float32) - ftype = 0 + if n_dims < 3 and data.dtype != np.float32: + data = data.astype(np.float32) + ftype = 0 #if name.startswith("encoder"): # if name.endswith("mlp.0.weight") or \ diff --git a/examples/whisper/quantize.cpp b/examples/whisper/quantize.cpp new file mode 100644 index 0000000..3752b67 --- /dev/null +++ b/examples/whisper/quantize.cpp @@ -0,0 +1,455 @@ +#include "ggml/ggml.h" + +#include "utils.h" + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#define QK 32 + +size_t ggml_quantize_q4_0(float * src, void * dst, int n, int k) { + const int nb = k / QK; + const size_t row_size = nb*(sizeof(float) + sizeof(uint8_t)*QK/2); + + assert(k % QK == 0); + + uint8_t pp[QK/2]; + + char * pdst = (char *) dst; + + for (int j = 0; j < n; j += k) { + float * pd = (float *) (pdst + (j/k)*row_size); + uint8_t * pb = (uint8_t *) (pd + nb); + + for (int i = 0; i < nb; i++) { + float amax = 0.0f; // absolute max + + { + for (int l = 0; l < QK; l++) { + const float v = src[j + i*QK + l]; + amax = std::max(amax, fabsf(v)); + } + + const float d = amax / ((1 << 3) - 1); + const float id = d ? 1.0f/d : 0.0f; + + pd[i] = d; + + for (int l = 0; l < QK; l += 2) { + const float v0 = (src[j + i*QK + l + 0])*id; + const float v1 = (src[j + i*QK + l + 1])*id; + + const uint8_t vi0 = ((int8_t) (round(v0))) + 8; + const uint8_t vi1 = ((int8_t) (round(v1))) + 8; + + assert(vi0 >= 0 && vi0 < 16); + assert(vi1 >= 0 && vi1 < 16); + + pp[l/2] = vi0 | (vi1 << 4); + } + + memcpy(pb + i*QK/2, pp, sizeof(pp)); + } + } + } + + return (n/k)*row_size; +} + +size_t ggml_quantize_q4_1(float * src, void * dst, int n, int k) { + const int nb = k / QK; + const size_t row_size = nb*(2*sizeof(float) + sizeof(uint8_t)*QK/2); + + assert(k % QK == 0); + + uint8_t pp[QK/2]; + + char * pdst = (char *) dst; + + for (int j = 0; j < n; j += k) { + float * pm = (float *) (pdst + (j/k)*row_size); + float * pd = (float *) (pm + nb); + uint8_t * pb = (uint8_t *) (pd + nb); + + //printf("n = %d, k = %d, nb = %d, row_size = %d, j = %d, pm = %p, pd = %p, pb = %p\n", n, k, nb, row_size, j, pm, pd, pb); + + for (int i = 0; i < nb; i++) { + float min = std::numeric_limits::max(); + float max = std::numeric_limits::min(); + + { + for (int l = 0; l < QK; l++) { + const float v = src[j + i*QK + l]; + if (v < min) min = v; + if (v > max) max = v; + } + + const float d = (max - min) / ((1 << 4) - 1); + const float id = d ? 1.0f/d : 0.0f; + + pm[i] = min; + pd[i] = d; + + for (int l = 0; l < QK; l += 2) { + const float v0 = (src[j + i*QK + l + 0] - min)*id; + const float v1 = (src[j + i*QK + l + 1] - min)*id; + + const uint8_t vi0 = round(v0); + const uint8_t vi1 = round(v1); + + assert(vi0 >= 0 && vi0 < 16); + assert(vi1 >= 0 && vi1 < 16); + + pp[l/2] = vi0 | (vi1 << 4); + } + + memcpy(pb + i*QK/2, pp, sizeof(pp)); + } + } + } + + return (n/k)*row_size; +} + +// default hparams (Whisper tiny) +struct whisper_hparams { + int32_t n_vocab = 51864; + int32_t n_audio_ctx = 1500; + int32_t n_audio_state = 384; + int32_t n_audio_head = 6; + int32_t n_audio_layer = 4; + int32_t n_text_ctx = 448; + int32_t n_text_state = 384; + int32_t n_text_head = 6; + int32_t n_text_layer = 4; + int32_t n_mels = 80; + int32_t f16 = 1; +}; + +struct whisper_filters { + int32_t n_mel; + int32_t n_fft; + + std::vector data; +}; + +// quantize a model +bool whisper_model_quantize(const std::string & fname_inp, const std::string & fname_out, int itype) { + ggml_type type = GGML_TYPE_Q4_1; + + switch (itype) { + case 2: type = GGML_TYPE_Q4_0; break; + case 3: type = GGML_TYPE_Q4_1; break; + default: fprintf(stderr, "%s: invalid quantization type %d\n", __func__, itype); return 1; + }; + + if (type != GGML_TYPE_Q4_0 && type != GGML_TYPE_Q4_1) { + fprintf(stderr, "%s: invalid quantization type %d\n", __func__, type); + return false; + } + + gpt_vocab vocab; + + printf("%s: loading model from '%s'\n", __func__, fname_inp.c_str()); + + auto finp = std::ifstream(fname_inp, std::ios::binary); + if (!finp) { + fprintf(stderr, "%s: failed to open '%s' for reading\n", __func__, fname_inp.c_str()); + return false; + } + + auto fout = std::ofstream(fname_out, std::ios::binary); + if (!fout) { + fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname_out.c_str()); + return false; + } + + // verify magic + { + uint32_t magic; + finp.read((char *) &magic, sizeof(magic)); + if (magic != 0x67676d6c) { + fprintf(stderr, "%s: invalid model file '%s' (bad magic)\n", __func__, fname_inp.c_str()); + return false; + } + + fout.write((char *) &magic, sizeof(magic)); + } + + whisper_hparams hparams; + + // load hparams + { + finp.read((char *) &hparams.n_vocab, sizeof(hparams.n_vocab)); + finp.read((char *) &hparams.n_audio_ctx, sizeof(hparams.n_audio_ctx)); + finp.read((char *) &hparams.n_audio_state, sizeof(hparams.n_audio_state)); + finp.read((char *) &hparams.n_audio_head, sizeof(hparams.n_audio_head)); + finp.read((char *) &hparams.n_audio_layer, sizeof(hparams.n_audio_layer)); + finp.read((char *) &hparams.n_text_ctx, sizeof(hparams.n_text_ctx)); + finp.read((char *) &hparams.n_text_state, sizeof(hparams.n_text_state)); + finp.read((char *) &hparams.n_text_head, sizeof(hparams.n_text_head)); + finp.read((char *) &hparams.n_text_layer, sizeof(hparams.n_text_layer)); + finp.read((char *) &hparams.n_mels, sizeof(hparams.n_mels)); + finp.read((char *) &hparams.f16, sizeof(hparams.f16)); + + fprintf(stderr, "%s: n_vocab = %d\n", __func__, hparams.n_vocab); + fprintf(stderr, "%s: n_audio_ctx = %d\n", __func__, hparams.n_audio_ctx); + fprintf(stderr, "%s: n_audio_state = %d\n", __func__, hparams.n_audio_state); + fprintf(stderr, "%s: n_audio_head = %d\n", __func__, hparams.n_audio_head); + fprintf(stderr, "%s: n_audio_layer = %d\n", __func__, hparams.n_audio_layer); + fprintf(stderr, "%s: n_text_ctx = %d\n", __func__, hparams.n_text_ctx); + fprintf(stderr, "%s: n_text_state = %d\n", __func__, hparams.n_text_state); + fprintf(stderr, "%s: n_text_head = %d\n", __func__, hparams.n_text_head); + fprintf(stderr, "%s: n_text_layer = %d\n", __func__, hparams.n_text_layer); + fprintf(stderr, "%s: n_mels = %d\n", __func__, hparams.n_mels); + fprintf(stderr, "%s: f16 = %d\n", __func__, hparams.f16); + + fout.write((char *) &hparams.n_vocab, sizeof(hparams.n_vocab)); + fout.write((char *) &hparams.n_audio_ctx, sizeof(hparams.n_audio_ctx)); + fout.write((char *) &hparams.n_audio_state, sizeof(hparams.n_audio_state)); + fout.write((char *) &hparams.n_audio_head, sizeof(hparams.n_audio_head)); + fout.write((char *) &hparams.n_audio_layer, sizeof(hparams.n_audio_layer)); + fout.write((char *) &hparams.n_text_ctx, sizeof(hparams.n_text_ctx)); + fout.write((char *) &hparams.n_text_state, sizeof(hparams.n_text_state)); + fout.write((char *) &hparams.n_text_head, sizeof(hparams.n_text_head)); + fout.write((char *) &hparams.n_text_layer, sizeof(hparams.n_text_layer)); + fout.write((char *) &hparams.n_mels, sizeof(hparams.n_mels)); + fout.write((char *) &itype, sizeof(hparams.f16)); + } + + // load mel filters + { + whisper_filters filters; + + finp.read ((char *) &filters.n_mel, sizeof(filters.n_mel)); + fout.write((char *) &filters.n_mel, sizeof(filters.n_mel)); + finp.read ((char *) &filters.n_fft, sizeof(filters.n_fft)); + fout.write((char *) &filters.n_fft, sizeof(filters.n_fft)); + + filters.data.resize(filters.n_mel * filters.n_fft); + finp.read ((char *) filters.data.data(), filters.data.size() * sizeof(float)); + fout.write((char *) filters.data.data(), filters.data.size() * sizeof(float)); + } + + // load vocab + { + int32_t n_vocab = 0; + finp.read ((char *) &n_vocab, sizeof(n_vocab)); + fout.write((char *) &n_vocab, sizeof(n_vocab)); + + //if (n_vocab != hparams.n_vocab) { + // fprintf(stderr, "%s: invalid model file '%s' (bad vocab size %d != %d)\n", + // __func__, fname_inp.c_str(), n_vocab, hparams.n_vocab); + // return false; + //} + + std::string word; + for (int i = 0; i < n_vocab; i++) { + uint32_t len; + finp.read ((char *) &len, sizeof(len)); + fout.write((char *) &len, sizeof(len)); + + word.resize(len); + finp.read ((char *) word.data(), len); + fout.write((char *) word.data(), len); + + vocab.token_to_id[word] = i; + vocab.id_to_token[i] = word; + } + } + + // load weights + { + size_t total_size_org = 0; + size_t total_size_new = 0; + + std::vector data; + std::vector work; + + std::vector data_u8; + std::vector data_f16; + + while (true) { + int32_t n_dims; + int32_t length; + int32_t ftype; + + finp.read(reinterpret_cast(&n_dims), sizeof(n_dims)); + finp.read(reinterpret_cast(&length), sizeof(length)); + finp.read(reinterpret_cast(&ftype), sizeof(ftype)); + + if (finp.eof()) { + break; + } + + int32_t nelements = 1; + int32_t ne[3] = { 1, 1, 1 }; + for (int i = 0; i < n_dims; ++i) { + finp.read (reinterpret_cast(&ne[i]), sizeof(ne[i])); + nelements *= ne[i]; + } + + std::string name(length, 0); + finp.read (&name[0], length); + + { + static const char * ftype_str[] = { "f32", "f16", "q4_0", "q4_1", }; + printf("%48s - [%5d, %5d, %5d], type = %6s ", name.data(), ne[0], ne[1], ne[2], ftype_str[ftype]); + } + + // regexes of tensor names to not be quantized + const std::vector k_names = { + //"encoder.*", + "encoder.conv1.bias", + "encoder.conv2.bias", + "encoder.positional_embedding", + "decoder.positional_embedding", + }; + + bool quantize = true; + for (const auto & s : k_names) { + if (std::regex_match(name, std::regex(s))) { + quantize = false; + break; + } + } + + // quantize only 2D and 3D tensors + quantize &= (n_dims == 2); + + if (quantize) { + if (ftype != 0 && ftype != 1) { + fprintf(stderr, "%s: unsupported ftype %d for integer quantization\n", __func__, ftype); + return false; + } + + if (ftype == 1) { + data_f16.resize(nelements); + finp.read(reinterpret_cast(data_f16.data()), nelements * sizeof(ggml_fp16_t)); + data.resize(nelements); + for (int i = 0; i < nelements; ++i) { + data[i] = ggml_fp16_to_fp32(data_f16[i]); + } + } else { + data.resize(nelements); + finp.read(reinterpret_cast(data.data()), nelements * sizeof(float)); + } + + ftype = itype; + } else { + const int bpe = (ftype == 0) ? sizeof(float) : sizeof(uint16_t); + + data_u8.resize(nelements*bpe); + finp.read(reinterpret_cast(data_u8.data()), nelements * bpe); + } + + fout.write(reinterpret_cast(&n_dims), sizeof(n_dims)); + fout.write(reinterpret_cast(&length), sizeof(length)); + fout.write(reinterpret_cast(&ftype), sizeof(ftype)); + for (int i = 0; i < n_dims; ++i) { + fout.write(reinterpret_cast(&ne[i]), sizeof(ne[i])); + } + fout.write(&name[0], length); + + if (quantize) { + printf("quantizing .. "); + work.resize(nelements); // for quantization + + size_t cur_size = 0; + + switch (type) { + case GGML_TYPE_Q4_0: + { + cur_size = ggml_quantize_q4_0(data.data(), work.data(), nelements, ne[0]); + } break; + case GGML_TYPE_Q4_1: + { + cur_size = ggml_quantize_q4_1(data.data(), work.data(), nelements, ne[0]); + } break; + default: + { + fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, type); + return false; + } + } + + fout.write(reinterpret_cast(work.data()), cur_size); + total_size_new += cur_size; + + printf("size = %8.3f MB -> %8.3f MB\n", nelements * sizeof(float)/1024.0/1024.0, cur_size/1024.0/1024.0); + } else { + printf("size = %8.3f MB\n", data_u8.size()/1024.0/1024.0); + fout.write(reinterpret_cast(data_u8.data()), data_u8.size()); + total_size_new += data_u8.size(); + } + + total_size_org += nelements * sizeof(float); + } + + printf("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0); + printf("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0); + } + + finp.close(); + fout.close(); + + return true; +} + +// usage: +// ./gpt-2-quantize models/gpt-2-117M/ggml-model.bin models/gpt-2-117M/ggml-model-quant.bin type +// +int main(int argc, char ** argv) { + if (argc != 4) { + fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type\n", argv[0]); + fprintf(stderr, " type = 2 - q4_0\n"); + fprintf(stderr, " type = 3 - q4_1\n"); + return 1; + } + + // needed to initialize f16 tables + { + struct ggml_init_params params = { 0, NULL }; + struct ggml_context * ctx = ggml_init(params); + ggml_free(ctx); + } + + const std::string fname_inp = argv[1]; + const std::string fname_out = argv[2]; + + const int itype = atoi(argv[3]); + + const int64_t t_main_start_us = ggml_time_us(); + + int64_t t_quantize_us = 0; + + // load the model + { + const int64_t t_start_us = ggml_time_us(); + + if (!whisper_model_quantize(fname_inp, fname_out, itype)) { + fprintf(stderr, "%s: failed to quantize model from '%s'\n", __func__, fname_inp.c_str()); + return 1; + } + + t_quantize_us = ggml_time_us() - t_start_us; + } + + // report timing + { + const int64_t t_main_end_us = ggml_time_us(); + + printf("\n"); + printf("%s: quantize time = %8.2f ms\n", __func__, t_quantize_us/1000.0f); + printf("%s: total time = %8.2f ms\n", __func__, (t_main_end_us - t_main_start_us)/1000.0f); + } + + return 0; +}