whisper : reduce memory usage during inference (#431)

* ggml : add "scratch" buffer support

* ggml : support for scratch ring-buffer

* ggml : bug fix in ggml_repeat()

* ggml : error on scratch buffer overflow

* whisper : use scratch buffers during inference (base model only)

* whisper : update memory usage for all models

* whisper : fix encoder memory usage

* whisper : use whisper_context functions instead of macros

* whisper : fix FF + remove it from README

* ggml : reuse ggml_new_i32

* ggml : refactor the scratch buffer storage

* whisper : reorder scratch buffers in the decoder

* main : add option to disable temp fallback

* Update README.md
pull/455/head^2
Georgi Gerganov 2 years ago committed by GitHub
parent c306a7fd89
commit f3ee4a9673
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GPG Key ID: 4AEE18F83AFDEB23

@ -13,7 +13,7 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
- AVX intrinsics support for x86 architectures - AVX intrinsics support for x86 architectures
- VSX intrinsics support for POWER architectures - VSX intrinsics support for POWER architectures
- Mixed F16 / F32 precision - Mixed F16 / F32 precision
- Low memory usage (Flash Attention + Flash Forward) - Low memory usage (Flash Attention)
- Zero memory allocations at runtime - Zero memory allocations at runtime
- Runs on the CPU - Runs on the CPU
- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/whisper.h) - [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/whisper.h)
@ -105,11 +105,13 @@ options:
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy) -su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english -tr, --translate [false ] translate from source language to english
-di, --diarize [false ] stereo audio diarization -di, --diarize [false ] stereo audio diarization
-nf, --no-fallback [false ] do not use temperature fallback while decoding
-otxt, --output-txt [false ] output result in a text file -otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file -ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file -osrt, --output-srt [false ] output result in a srt file
-owts, --output-words [false ] output script for generating karaoke video -owts, --output-words [false ] output script for generating karaoke video
-ocsv, --output-csv [false ] output result in a CSV file -ocsv, --output-csv [false ] output result in a CSV file
-of FNAME, --output-file FNAME [ ] output file path (without file extension)
-ps, --print-special [false ] print special tokens -ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors -pc, --print-colors [false ] print colors
-pp, --print-progress [false ] print progress -pp, --print-progress [false ] print progress
@ -137,7 +139,8 @@ Running base.en on all samples in ./samples ...
[+] Running base.en on samples/jfk.wav ... (run 'ffplay samples/jfk.wav' to listen) [+] Running base.en on samples/jfk.wav ... (run 'ffplay samples/jfk.wav' to listen)
---------------------------------------------- ----------------------------------------------
whisper_model_load: loading model from 'models/ggml-base.en.bin' whisper_init_from_file: loading model from 'models/ggml-base.en.bin'
whisper_model_load: loading model
whisper_model_load: n_vocab = 51864 whisper_model_load: n_vocab = 51864
whisper_model_load: n_audio_ctx = 1500 whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 512 whisper_model_load: n_audio_state = 512
@ -150,13 +153,14 @@ whisper_model_load: n_text_layer = 6
whisper_model_load: n_mels = 80 whisper_model_load: n_mels = 80
whisper_model_load: f16 = 1 whisper_model_load: f16 = 1
whisper_model_load: type = 2 whisper_model_load: type = 2
whisper_model_load: mem required = 215.00 MB (+ 6.00 MB per decoder)
whisper_model_load: kv self size = 5.25 MB
whisper_model_load: kv cross size = 17.58 MB
whisper_model_load: adding 1607 extra tokens whisper_model_load: adding 1607 extra tokens
whisper_model_load: mem_required = 506.00 MB whisper_model_load: model ctx = 140.60 MB
whisper_model_load: ggml ctx size = 140.60 MB
whisper_model_load: memory size = 22.83 MB
whisper_model_load: model size = 140.54 MB whisper_model_load: model size = 140.54 MB
system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ... main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...
@ -164,12 +168,13 @@ main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 proc
[00:00:00.000 --> 00:00:11.000] And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country. [00:00:00.000 --> 00:00:11.000] And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
whisper_print_timings: load time = 105.91 ms whisper_print_timings: fallbacks = 0 p / 0 h
whisper_print_timings: mel time = 24.62 ms whisper_print_timings: load time = 113.81 ms
whisper_print_timings: sample time = 3.63 ms whisper_print_timings: mel time = 15.40 ms
whisper_print_timings: encode time = 324.71 ms / 54.12 ms per layer whisper_print_timings: sample time = 11.58 ms / 27 runs ( 0.43 ms per run)
whisper_print_timings: decode time = 83.58 ms / 13.93 ms per layer whisper_print_timings: encode time = 266.60 ms / 1 runs ( 266.60 ms per run)
whisper_print_timings: total time = 542.81 ms whisper_print_timings: decode time = 66.11 ms / 27 runs ( 2.45 ms per run)
whisper_print_timings: total time = 476.31 ms
``` ```
The command downloads the `base.en` model converted to custom `ggml` format and runs the inference on all `.wav` samples in the folder `samples`. The command downloads the `base.en` model converted to custom `ggml` format and runs the inference on all `.wav` samples in the folder `samples`.
@ -212,11 +217,11 @@ make large
| Model | Disk | Mem | SHA | | Model | Disk | Mem | SHA |
| --- | --- | --- | --- | | --- | --- | --- | --- |
| tiny | 75 MB | ~390 MB | `bd577a113a864445d4c299885e0cb97d4ba92b5f` | | tiny | 75 MB | ~125 MB | `bd577a113a864445d4c299885e0cb97d4ba92b5f` |
| base | 142 MB | ~500 MB | `465707469ff3a37a2b9b8d8f89f2f99de7299dac` | | base | 142 MB | ~210 MB | `465707469ff3a37a2b9b8d8f89f2f99de7299dac` |
| small | 466 MB | ~1.0 GB | `55356645c2b361a969dfd0ef2c5a50d530afd8d5` | | small | 466 MB | ~600 MB | `55356645c2b361a969dfd0ef2c5a50d530afd8d5` |
| medium | 1.5 GB | ~2.6 GB | `fd9727b6e1217c2f614f9b698455c4ffd82463b4` | | medium | 1.5 GB | ~1.7 GB | `fd9727b6e1217c2f614f9b698455c4ffd82463b4` |
| large | 2.9 GB | ~4.7 GB | `0f4c8e34f21cf1a914c59d8b3ce882345ad349d6` | | large | 2.9 GB | ~3.3 GB | `0f4c8e34f21cf1a914c59d8b3ce882345ad349d6` |
## Limitations ## Limitations
@ -234,7 +239,8 @@ in about half a minute on a MacBook M1 Pro, using `medium.en` model:
```java ```java
$ ./main -m models/ggml-medium.en.bin -f samples/gb1.wav -t 8 $ ./main -m models/ggml-medium.en.bin -f samples/gb1.wav -t 8
whisper_model_load: loading model from 'models/ggml-medium.en.bin' whisper_init_from_file: loading model from 'models/ggml-medium.en.bin'
whisper_model_load: loading model
whisper_model_load: n_vocab = 51864 whisper_model_load: n_vocab = 51864
whisper_model_load: n_audio_ctx = 1500 whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 1024 whisper_model_load: n_audio_state = 1024
@ -247,55 +253,60 @@ whisper_model_load: n_text_layer = 24
whisper_model_load: n_mels = 80 whisper_model_load: n_mels = 80
whisper_model_load: f16 = 1 whisper_model_load: f16 = 1
whisper_model_load: type = 4 whisper_model_load: type = 4
whisper_model_load: mem_required = 2610.00 MB whisper_model_load: mem required = 1720.00 MB (+ 43.00 MB per decoder)
whisper_model_load: kv self size = 42.00 MB
whisper_model_load: kv cross size = 140.62 MB
whisper_model_load: adding 1607 extra tokens whisper_model_load: adding 1607 extra tokens
whisper_model_load: ggml ctx size = 1644.97 MB whisper_model_load: model ctx = 1462.35 MB
whisper_model_load: memory size = 182.62 MB
whisper_model_load: model size = 1462.12 MB whisper_model_load: model size = 1462.12 MB
main: processing 'samples/gb1.wav' (3179750 samples, 198.7 sec), 8 threads, lang = en, task = transcribe, timestamps = 1 ... system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
[00:00.000 --> 00:08.000] My fellow Americans, this day has brought terrible news and great sadness to our country. main: processing 'samples/gb1.wav' (3179750 samples, 198.7 sec), 8 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...
[00:08.000 --> 00:17.000] At nine o'clock this morning, Mission Control in Houston lost contact with our Space Shuttle Columbia.
[00:17.000 --> 00:23.000] A short time later, debris was seen falling from the skies above Texas.
[00:23.000 --> 00:29.000] The Columbia's lost. There are no survivors. [00:00:00.000 --> 00:00:08.000] My fellow Americans, this day has brought terrible news and great sadness to our country.
[00:29.000 --> 00:32.000] On board was a crew of seven. [00:00:08.000 --> 00:00:17.000] At nine o'clock this morning, Mission Control in Houston lost contact with our Space Shuttle Columbia.
[00:32.000 --> 00:39.000] Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark, [00:00:17.000 --> 00:00:23.000] A short time later, debris was seen falling from the skies above Texas.
[00:39.000 --> 00:48.000] Captain David Brown, Commander William McCool, Dr. Kultna Shavla, and Ilan Ramon, [00:00:23.000 --> 00:00:29.000] The Columbia's lost. There are no survivors.
[00:48.000 --> 00:52.000] a colonel in the Israeli Air Force. [00:00:29.000 --> 00:00:32.000] On board was a crew of seven.
[00:52.000 --> 00:58.000] These men and women assumed great risk in the service to all humanity. [00:00:32.000 --> 00:00:39.000] Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark,
[00:58.000 --> 01:03.000] In an age when space flight has come to seem almost routine, [00:00:39.000 --> 00:00:48.000] Captain David Brown, Commander William McCool, Dr. Kultna Shavla, and Ilan Ramon,
[01:03.000 --> 01:07.000] it is easy to overlook the dangers of travel by rocket [00:00:48.000 --> 00:00:52.000] a colonel in the Israeli Air Force.
[01:07.000 --> 01:12.000] and the difficulties of navigating the fierce outer atmosphere of the Earth. [00:00:52.000 --> 00:00:58.000] These men and women assumed great risk in the service to all humanity.
[01:12.000 --> 01:18.000] These astronauts knew the dangers, and they faced them willingly, [00:00:58.000 --> 00:01:03.000] In an age when space flight has come to seem almost routine,
[01:18.000 --> 01:23.000] knowing they had a high and noble purpose in life. [00:01:03.000 --> 00:01:07.000] it is easy to overlook the dangers of travel by rocket
[01:23.000 --> 01:31.000] Because of their courage and daring and idealism, we will miss them all the more. [00:01:07.000 --> 00:01:12.000] and the difficulties of navigating the fierce outer atmosphere of the Earth.
[01:31.000 --> 01:36.000] All Americans today are thinking as well of the families of these men and women [00:01:12.000 --> 00:01:18.000] These astronauts knew the dangers, and they faced them willingly,
[01:36.000 --> 01:40.000] who have been given this sudden shock and grief. [00:01:18.000 --> 00:01:23.000] knowing they had a high and noble purpose in life.
[01:40.000 --> 01:45.000] You're not alone. Our entire nation grieves with you, [00:01:23.000 --> 00:01:31.000] Because of their courage and daring and idealism, we will miss them all the more.
[01:45.000 --> 01:52.000] and those you love will always have the respect and gratitude of this country. [00:01:31.000 --> 00:01:36.000] All Americans today are thinking as well of the families of these men and women
[01:52.000 --> 01:56.000] The cause in which they died will continue. [00:01:36.000 --> 00:01:40.000] who have been given this sudden shock and grief.
[01:56.000 --> 02:04.000] Mankind is led into the darkness beyond our world by the inspiration of discovery [00:01:40.000 --> 00:01:45.000] You're not alone. Our entire nation grieves with you,
[02:04.000 --> 02:11.000] and the longing to understand. Our journey into space will go on. [00:01:45.000 --> 00:01:52.000] and those you love will always have the respect and gratitude of this country.
[02:11.000 --> 02:16.000] In the skies today, we saw destruction and tragedy. [00:01:52.000 --> 00:01:56.000] The cause in which they died will continue.
[02:16.000 --> 02:22.000] Yet farther than we can see, there is comfort and hope. [00:01:56.000 --> 00:02:04.000] Mankind is led into the darkness beyond our world by the inspiration of discovery
[02:22.000 --> 02:29.000] In the words of the prophet Isaiah, "Lift your eyes and look to the heavens [00:02:04.000 --> 00:02:11.000] and the longing to understand. Our journey into space will go on.
[02:29.000 --> 02:35.000] who created all these. He who brings out the starry hosts one by one [00:02:11.000 --> 00:02:16.000] In the skies today, we saw destruction and tragedy.
[02:35.000 --> 02:39.000] and calls them each by name." [00:02:16.000 --> 00:02:22.000] Yet farther than we can see, there is comfort and hope.
[02:39.000 --> 02:46.000] Because of His great power and mighty strength, not one of them is missing. [00:02:22.000 --> 00:02:29.000] In the words of the prophet Isaiah, "Lift your eyes and look to the heavens
[02:46.000 --> 02:55.000] The same Creator who names the stars also knows the names of the seven souls we mourn today. [00:02:29.000 --> 00:02:35.000] who created all these. He who brings out the starry hosts one by one
[02:55.000 --> 03:01.000] The crew of the shuttle Columbia did not return safely to earth, [00:02:35.000 --> 00:02:39.000] and calls them each by name."
[03:01.000 --> 03:05.000] yet we can pray that all are safely home. [00:02:39.000 --> 00:02:46.000] Because of His great power and mighty strength, not one of them is missing.
[03:05.000 --> 03:13.000] May God bless the grieving families, and may God continue to bless America. [00:02:46.000 --> 00:02:55.000] The same Creator who names the stars also knows the names of the seven souls we mourn today.
[03:13.000 --> 03:41.000] Audio [00:02:55.000 --> 00:03:01.000] The crew of the shuttle Columbia did not return safely to earth,
[00:03:01.000 --> 00:03:05.000] yet we can pray that all are safely home.
[00:03:05.000 --> 00:03:13.000] May God bless the grieving families, and may God continue to bless America.
whisper_print_timings: load time = 575.92 ms [00:03:13.000 --> 00:03:19.000] [Silence]
whisper_print_timings: mel time = 230.60 ms
whisper_print_timings: sample time = 73.19 ms
whisper_print_timings: encode time = 19552.61 ms / 814.69 ms per layer whisper_print_timings: fallbacks = 1 p / 0 h
whisper_print_timings: decode time = 13249.96 ms / 552.08 ms per layer whisper_print_timings: load time = 569.03 ms
whisper_print_timings: total time = 33686.27 ms whisper_print_timings: mel time = 146.85 ms
whisper_print_timings: sample time = 238.66 ms / 553 runs ( 0.43 ms per run)
whisper_print_timings: encode time = 18665.10 ms / 9 runs ( 2073.90 ms per run)
whisper_print_timings: decode time = 13090.93 ms / 549 runs ( 23.85 ms per run)
whisper_print_timings: total time = 32733.52 ms
``` ```
</details> </details>

File diff suppressed because one or more lines are too long

@ -17,17 +17,27 @@ options:
-d N, --duration N [0 ] duration of audio to process in milliseconds -d N, --duration N [0 ] duration of audio to process in milliseconds
-mc N, --max-context N [-1 ] maximum number of text context tokens to store -mc N, --max-context N [-1 ] maximum number of text context tokens to store
-ml N, --max-len N [0 ] maximum segment length in characters -ml N, --max-len N [0 ] maximum segment length in characters
-bo N, --best-of N [5 ] number of best candidates to keep
-bs N, --beam-size N [-1 ] beam size for beam search
-wt N, --word-thold N [0.01 ] word timestamp probability threshold -wt N, --word-thold N [0.01 ] word timestamp probability threshold
-et N, --entropy-thold N [2.40 ] entropy threshold for decoder fail
-lpt N, --logprob-thold N [-1.00 ] log probability threshold for decoder fail
-su, --speed-up [false ] speed up audio by x2 (reduced accuracy) -su, --speed-up [false ] speed up audio by x2 (reduced accuracy)
-tr, --translate [false ] translate from source language to english -tr, --translate [false ] translate from source language to english
-di, --diarize [false ] stereo audio diarization
-nf, --no-fallback [false ] do not use temperature fallback while decoding
-otxt, --output-txt [false ] output result in a text file -otxt, --output-txt [false ] output result in a text file
-ovtt, --output-vtt [false ] output result in a vtt file -ovtt, --output-vtt [false ] output result in a vtt file
-osrt, --output-srt [false ] output result in a srt file -osrt, --output-srt [false ] output result in a srt file
-owts, --output-words [false ] output script for generating karaoke video -owts, --output-words [false ] output script for generating karaoke video
-ocsv, --output-csv [false ] output result in a CSV file
-of FNAME, --output-file FNAME [ ] output file path (without file extension)
-ps, --print-special [false ] print special tokens -ps, --print-special [false ] print special tokens
-pc, --print-colors [false ] print colors -pc, --print-colors [false ] print colors
-pp, --print-progress [false ] print progress
-nt, --no-timestamps [true ] do not print timestamps -nt, --no-timestamps [true ] do not print timestamps
-l LANG, --language LANG [en ] spoken language -l LANG, --language LANG [en ] spoken language ('auto' for auto-detect)
--prompt PROMPT [ ] initial prompt
-m FNAME, --model FNAME [models/ggml-base.en.bin] model path -m FNAME, --model FNAME [models/ggml-base.en.bin] model path
-f FNAME, --file FNAME [ ] input WAV file path -f FNAME, --file FNAME [ ] input WAV file path
``` ```

@ -63,12 +63,13 @@ struct whisper_params {
int32_t beam_size = -1; int32_t beam_size = -1;
float word_thold = 0.01f; float word_thold = 0.01f;
float entropy_thold = 2.4f; float entropy_thold = 2.40f;
float logprob_thold = -1.0f; float logprob_thold = -1.00f;
bool speed_up = false; bool speed_up = false;
bool translate = false; bool translate = false;
bool diarize = false; bool diarize = false;
bool no_fallback = false;
bool output_txt = false; bool output_txt = false;
bool output_vtt = false; bool output_vtt = false;
bool output_srt = false; bool output_srt = false;
@ -117,6 +118,7 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; } else if (arg == "-su" || arg == "--speed-up") { params.speed_up = true; }
else if (arg == "-tr" || arg == "--translate") { params.translate = true; } else if (arg == "-tr" || arg == "--translate") { params.translate = true; }
else if (arg == "-di" || arg == "--diarize") { params.diarize = true; } else if (arg == "-di" || arg == "--diarize") { params.diarize = true; }
else if (arg == "-nf" || arg == "--no-fallback") { params.no_fallback = true; }
else if (arg == "-otxt" || arg == "--output-txt") { params.output_txt = true; } else if (arg == "-otxt" || arg == "--output-txt") { params.output_txt = true; }
else if (arg == "-ovtt" || arg == "--output-vtt") { params.output_vtt = true; } else if (arg == "-ovtt" || arg == "--output-vtt") { params.output_vtt = true; }
else if (arg == "-osrt" || arg == "--output-srt") { params.output_srt = true; } else if (arg == "-osrt" || arg == "--output-srt") { params.output_srt = true; }
@ -162,6 +164,7 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false"); fprintf(stderr, " -su, --speed-up [%-7s] speed up audio by x2 (reduced accuracy)\n", params.speed_up ? "true" : "false");
fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false"); fprintf(stderr, " -tr, --translate [%-7s] translate from source language to english\n", params.translate ? "true" : "false");
fprintf(stderr, " -di, --diarize [%-7s] stereo audio diarization\n", params.diarize ? "true" : "false"); fprintf(stderr, " -di, --diarize [%-7s] stereo audio diarization\n", params.diarize ? "true" : "false");
fprintf(stderr, " -nf, --no-fallback [%-7s] do not use temperature fallback while decoding\n", params.no_fallback ? "true" : "false");
fprintf(stderr, " -otxt, --output-txt [%-7s] output result in a text file\n", params.output_txt ? "true" : "false"); fprintf(stderr, " -otxt, --output-txt [%-7s] output result in a text file\n", params.output_txt ? "true" : "false");
fprintf(stderr, " -ovtt, --output-vtt [%-7s] output result in a vtt file\n", params.output_vtt ? "true" : "false"); fprintf(stderr, " -ovtt, --output-vtt [%-7s] output result in a vtt file\n", params.output_vtt ? "true" : "false");
fprintf(stderr, " -osrt, --output-srt [%-7s] output result in a srt file\n", params.output_srt ? "true" : "false"); fprintf(stderr, " -osrt, --output-srt [%-7s] output result in a srt file\n", params.output_srt ? "true" : "false");
@ -514,7 +517,7 @@ int main(int argc, char ** argv) {
for (int f = 0; f < (int) params.fname_inp.size(); ++f) { for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
const auto fname_inp = params.fname_inp[f]; const auto fname_inp = params.fname_inp[f];
const auto fname_outp = f < params.fname_outp.size() && !params.fname_outp[f].empty() ? params.fname_outp[f] : params.fname_inp[f]; const auto fname_outp = f < (int) params.fname_outp.size() && !params.fname_outp[f].empty() ? params.fname_outp[f] : params.fname_inp[f];
std::vector<float> pcmf32; // mono-channel F32 PCM std::vector<float> pcmf32; // mono-channel F32 PCM
std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
@ -647,17 +650,19 @@ int main(int argc, char ** argv) {
wparams.token_timestamps = params.output_wts || params.max_len > 0; wparams.token_timestamps = params.output_wts || params.max_len > 0;
wparams.thold_pt = params.word_thold; wparams.thold_pt = params.word_thold;
wparams.entropy_thold = params.entropy_thold;
wparams.logprob_thold = params.logprob_thold;
wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len; wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
wparams.speed_up = params.speed_up; wparams.speed_up = params.speed_up;
wparams.prompt_tokens = prompt_tokens.empty() ? nullptr : prompt_tokens.data();
wparams.prompt_n_tokens = prompt_tokens.empty() ? 0 : prompt_tokens.size();
wparams.greedy.best_of = params.best_of; wparams.greedy.best_of = params.best_of;
wparams.beam_search.beam_size = params.beam_size; wparams.beam_search.beam_size = params.beam_size;
wparams.prompt_tokens = prompt_tokens.empty() ? nullptr : prompt_tokens.data(); wparams.temperature_inc = params.no_fallback ? 0.0f : wparams.temperature_inc;
wparams.prompt_n_tokens = prompt_tokens.empty() ? 0 : prompt_tokens.size(); wparams.entropy_thold = params.entropy_thold;
wparams.logprob_thold = params.logprob_thold;
whisper_print_user_data user_data = { &params, &pcmf32s }; whisper_print_user_data user_data = { &params, &pcmf32s };

103
ggml.c

@ -1258,7 +1258,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
// //
struct ggml_object { struct ggml_object {
size_t offset; size_t offs;
size_t size; size_t size;
struct ggml_object * next; struct ggml_object * next;
@ -1284,6 +1284,9 @@ struct ggml_context {
struct ggml_object * objects_begin; struct ggml_object * objects_begin;
struct ggml_object * objects_end; struct ggml_object * objects_end;
struct ggml_scratch scratch;
struct ggml_scratch scratch_save;
}; };
struct ggml_context_container { struct ggml_context_container {
@ -1346,7 +1349,7 @@ inline static void ggml_critical_section_end(void) {
void ggml_print_object(const struct ggml_object * obj) { void ggml_print_object(const struct ggml_object * obj) {
GGML_PRINT(" - ggml_object: offset = %zu, size = %zu, next = %p\n", GGML_PRINT(" - ggml_object: offset = %zu, size = %zu, next = %p\n",
obj->offset, obj->size, (const void *) obj->next); obj->offs, obj->size, (const void *) obj->next);
} }
void ggml_print_objects(const struct ggml_context * ctx) { void ggml_print_objects(const struct ggml_context * ctx) {
@ -1542,12 +1545,14 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
} }
*ctx = (struct ggml_context) { *ctx = (struct ggml_context) {
.mem_size = params.mem_size, /*.mem_size =*/ params.mem_size,
.mem_buffer = params.mem_buffer ? params.mem_buffer : malloc(params.mem_size), /*.mem_buffer =*/ params.mem_buffer ? params.mem_buffer : malloc(params.mem_size),
.mem_buffer_owned = params.mem_buffer ? false : true, /*.mem_buffer_owned =*/ params.mem_buffer ? false : true,
.n_objects = 0, /*.n_objects =*/ 0,
.objects_begin = NULL, /*.objects_begin =*/ NULL,
.objects_end = NULL, /*.objects_end =*/ NULL,
/*.scratch =*/ { 0, 0, NULL, },
/*.scratch_save =*/ { 0, 0, NULL, },
}; };
ggml_assert_aligned(ctx->mem_buffer); ggml_assert_aligned(ctx->mem_buffer);
@ -1570,7 +1575,7 @@ void ggml_free(struct ggml_context * ctx) {
g_state.contexts[i].used = false; g_state.contexts[i].used = false;
GGML_PRINT_DEBUG("%s: context %d with %d objects has been freed. memory used = %zu\n", GGML_PRINT_DEBUG("%s: context %d with %d objects has been freed. memory used = %zu\n",
__func__, i, ctx->n_objects, ctx->objects_end->offset + ctx->objects_end->size); __func__, i, ctx->n_objects, ctx->objects_end->offs + ctx->objects_end->size);
if (ctx->mem_buffer_owned) { if (ctx->mem_buffer_owned) {
free(ctx->mem_buffer); free(ctx->mem_buffer);
@ -1589,7 +1594,15 @@ void ggml_free(struct ggml_context * ctx) {
} }
size_t ggml_used_mem(const struct ggml_context * ctx) { size_t ggml_used_mem(const struct ggml_context * ctx) {
return ctx->objects_end->offset + ctx->objects_end->size; return ctx->objects_end->offs + ctx->objects_end->size;
}
size_t ggml_set_scratch(struct ggml_context * ctx, struct ggml_scratch scratch) {
const size_t result = ctx->scratch.data ? ctx->scratch.offs : 0;
ctx->scratch = scratch;
return result;
} }
//////////////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////////////
@ -1603,9 +1616,9 @@ struct ggml_tensor * ggml_new_tensor_impl(
// always insert objects at the end of the context's memory pool // always insert objects at the end of the context's memory pool
struct ggml_object * obj_cur = ctx->objects_end; struct ggml_object * obj_cur = ctx->objects_end;
const size_t cur_offset = obj_cur == NULL ? 0 : obj_cur->offset; const size_t cur_offs = obj_cur == NULL ? 0 : obj_cur->offs;
const size_t cur_size = obj_cur == NULL ? 0 : obj_cur->size; const size_t cur_size = obj_cur == NULL ? 0 : obj_cur->size;
const size_t cur_end = cur_offset + cur_size; const size_t cur_end = cur_offs + cur_size;
size_t size_needed = 0; size_t size_needed = 0;
@ -1616,26 +1629,53 @@ struct ggml_tensor * ggml_new_tensor_impl(
} }
// align to GGML_MEM_ALIGN // align to GGML_MEM_ALIGN
size_needed = ((size_needed + GGML_MEM_ALIGN - 1)/GGML_MEM_ALIGN)*GGML_MEM_ALIGN; size_needed = ((size_needed + GGML_MEM_ALIGN - 1)/GGML_MEM_ALIGN)*GGML_MEM_ALIGN;
} }
char * const mem_buffer = ctx->mem_buffer;
struct ggml_object * const obj_new = (struct ggml_object *)(mem_buffer + cur_end);
if (ctx->scratch.data == NULL || data != NULL) {
size_needed += sizeof(struct ggml_tensor); size_needed += sizeof(struct ggml_tensor);
if (cur_end + size_needed + GGML_OBJECT_SIZE > ctx->mem_size) { if (cur_end + size_needed + GGML_OBJECT_SIZE > ctx->mem_size) {
GGML_PRINT("%s: not enough space in the context's memory pool\n", __func__); GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n",
__func__, cur_end + size_needed + GGML_OBJECT_SIZE, ctx->mem_size);
assert(false); assert(false);
return NULL; return NULL;
} }
char * const mem_buffer = ctx->mem_buffer; *obj_new = (struct ggml_object) {
.offs = cur_end + GGML_OBJECT_SIZE,
.size = size_needed,
.next = NULL,
};
} else {
if (ctx->scratch.offs + size_needed > ctx->scratch.size) {
GGML_PRINT("%s: not enough space in the scratch memory\n", __func__);
assert(false);
return NULL;
}
struct ggml_object * const obj_new = (struct ggml_object *)(mem_buffer + cur_end); if (cur_end + sizeof(struct ggml_tensor) + GGML_OBJECT_SIZE > ctx->mem_size) {
GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n",
__func__, cur_end + sizeof(struct ggml_tensor) + GGML_OBJECT_SIZE, ctx->mem_size);
assert(false);
return NULL;
}
data = (char * const) ctx->scratch.data + ctx->scratch.offs;
*obj_new = (struct ggml_object) { *obj_new = (struct ggml_object) {
.offset = cur_end + GGML_OBJECT_SIZE, .offs = cur_end + GGML_OBJECT_SIZE,
.size = size_needed, .size = sizeof(struct ggml_tensor),
.next = NULL, .next = NULL,
}; };
//printf("scratch offs = %zu, size_needed = %zu\n", ctx->scratch.offs, size_needed);
ctx->scratch.offs += size_needed;
}
if (obj_cur != NULL) { if (obj_cur != NULL) {
obj_cur->next = obj_new; obj_cur->next = obj_new;
} else { } else {
@ -1645,9 +1685,9 @@ struct ggml_tensor * ggml_new_tensor_impl(
ctx->objects_end = obj_new; ctx->objects_end = obj_new;
//GGML_PRINT_DEBUG("%s: inserted new object at %zu\n", __func__, cur_end); //printf("%s: inserted new object at %zu, size = %zu\n", __func__, cur_end, obj_new->size);
struct ggml_tensor * const result = (struct ggml_tensor *)(mem_buffer + obj_new->offset); struct ggml_tensor * const result = (struct ggml_tensor *)(mem_buffer + obj_new->offs);
ggml_assert_aligned(result); ggml_assert_aligned(result);
@ -1732,16 +1772,26 @@ struct ggml_tensor * ggml_new_tensor_4d(
} }
struct ggml_tensor * ggml_new_i32(struct ggml_context * ctx, int32_t value) { struct ggml_tensor * ggml_new_i32(struct ggml_context * ctx, int32_t value) {
ctx->scratch_save = ctx->scratch;
ctx->scratch.data = NULL;
struct ggml_tensor * result = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 1); struct ggml_tensor * result = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 1);
ctx->scratch = ctx->scratch_save;
ggml_set_i32(result, value); ggml_set_i32(result, value);
return result; return result;
} }
struct ggml_tensor * ggml_new_f32(struct ggml_context * ctx, float value) { struct ggml_tensor * ggml_new_f32(struct ggml_context * ctx, float value) {
ctx->scratch_save = ctx->scratch;
ctx->scratch.data = NULL;
struct ggml_tensor * result = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, 1); struct ggml_tensor * result = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, 1);
ctx->scratch = ctx->scratch_save;
ggml_set_f32(result, value); ggml_set_f32(result, value);
return result; return result;
@ -2350,7 +2400,7 @@ struct ggml_tensor * ggml_repeat(
result->op = GGML_OP_REPEAT; result->op = GGML_OP_REPEAT;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL; result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
result->src0 = a; result->src0 = a;
result->src1 = NULL; result->src1 = b;
return result; return result;
} }
@ -2966,9 +3016,7 @@ struct ggml_tensor * ggml_diag_mask_inf(
// TODO: when implement backward, fix this: // TODO: when implement backward, fix this:
//struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); //struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
struct ggml_tensor * result = ggml_view_tensor(ctx, a); struct ggml_tensor * result = ggml_view_tensor(ctx, a);
struct ggml_tensor * b = ggml_new_i32(ctx, n_past);
struct ggml_tensor * b = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 1);
((int32_t *) b->data)[0] = n_past;
result->op = GGML_OP_DIAG_MASK_INF; result->op = GGML_OP_DIAG_MASK_INF;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL; result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
@ -4300,7 +4348,9 @@ static bool ggml_compute_forward_mul_mat_use_blas(
const int ne1 = dst->ne[1]; const int ne1 = dst->ne[1];
// TODO: find the optimal values for these // TODO: find the optimal values for these
if (ggml_is_contiguous(src0) && ggml_is_contiguous(src1) && ne0 >= 32 && ne1 >= 32 && ne10 >= 32) { if (ggml_is_contiguous(src0) && ggml_is_contiguous(src1) && (
(ne0 >= 32 && ne1 >= 32 && ne10 >= 32)
)) {
//printf("BLAS: %d %d %d\n", ne0, ne1, ne10); //printf("BLAS: %d %d %d\n", ne0, ne1, ne10);
return true; return true;
} }
@ -7289,6 +7339,9 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
node->n_tasks = 1; // TODO: this actually is doing nothing node->n_tasks = 1; // TODO: this actually is doing nothing
// the threads are still spinning // the threads are still spinning
cur = sizeof(float)*(node->src0->ne[0]*node->src0->ne[1]); cur = sizeof(float)*(node->src0->ne[0]*node->src0->ne[1]);
//printf("src0: ne0 = %d, ne1 = %d, ne = %d\n", node->src0->ne[0], node->src0->ne[1], node->src0->ne[0]*node->src0->ne[1]);
//printf("src1: ne0 = %d, ne1 = %d, ne = %d\n", node->src1->ne[0], node->src1->ne[1], node->src1->ne[0]*node->src1->ne[1]);
//printf("cur = %zu\n", cur);
} else { } else {
cur = sizeof(ggml_fp16_t)*ggml_nelements(node->src1); cur = sizeof(ggml_fp16_t)*ggml_nelements(node->src1);
} }

@ -301,6 +301,13 @@ struct ggml_cgraph {
int64_t perf_time_us; int64_t perf_time_us;
}; };
// scratch buffer
struct ggml_scratch {
size_t offs;
size_t size;
void * data;
};
struct ggml_init_params { struct ggml_init_params {
// memory pool // memory pool
size_t mem_size; // bytes size_t mem_size; // bytes
@ -327,6 +334,8 @@ void ggml_free(struct ggml_context * ctx);
size_t ggml_used_mem(const struct ggml_context * ctx); size_t ggml_used_mem(const struct ggml_context * ctx);
size_t ggml_set_scratch(struct ggml_context * ctx, struct ggml_scratch scratch);
struct ggml_tensor * ggml_new_tensor( struct ggml_tensor * ggml_new_tensor(
struct ggml_context * ctx, struct ggml_context * ctx,
enum ggml_type type, enum ggml_type type,

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