Commit graph

14 commits

Author SHA1 Message Date
Stephan Walter
3e6e70d8e8
Add enum llama_ftype, sync ggml_type to model files (#709) 2023-04-11 15:03:51 +00:00
Georgi Gerganov
c3ac702e5e
ggml : add ggml_cont() + optimize ggml_cpy() for contiguous dst 2023-04-10 22:42:28 +03:00
comex
f963b63afa Rewrite loading code to try to satisfy everyone:
- Support all three formats (ggml, ggmf, ggjt).  (However, I didn't
  include the hack needed to support GPT4All files without conversion.
  Those can still be used after converting them with convert.py from my
  other PR.)

- Support both mmap and read (mmap is used by default, but can be
  disabled with `--no-mmap`, and is automatically disabled for pre-ggjt
  files or on platforms where mmap is not supported).

- Support multi-file models like before, but automatically determine the
  number of parts rather than requiring `--n_parts`.

- Improve validation and error checking.

- Stop using the per-file type field (f16) entirely in favor of just
  relying on the per-tensor type/size fields.  This has no immediate
  benefit, but makes it easier to experiment with different formats, and
  should make it easier to support the new GPTQ-for-LLaMa models in the
  future (I have some work in progress on that front).

- Support VirtualLock on Windows (using the same `--mlock` option as on
  Unix).

    - Indicate loading progress when using mmap + mlock.  (Which led me
      to the interesting observation that on my Linux machine, with a
      warm file cache, mlock actually takes some time, whereas mmap
      without mlock starts almost instantly...)

      - To help implement this, move mlock support from ggml to the
        loading code.

- madvise/PrefetchVirtualMemory support (based on #740)

- Switch from ifstream to the `fopen` family of functions to avoid
  unnecessary copying and, when mmap is enabled, allow reusing the same
  file descriptor for both metadata reads and mmap (whereas the existing
  implementation opens the file a second time to mmap).

- Quantization now produces a single-file output even with multi-file
  inputs (not really a feature as much as 'it was easier this way').

Implementation notes:

I tried to factor the code into more discrete pieces than before.

Regarding code style: I tried to follow the code style, but I'm naughty
and used a few advanced C++ features repeatedly:

- Destructors to make it easier to ensure everything gets cleaned up.

- Exceptions.  I don't even usually use exceptions when writing C++, and
  I can remove them if desired... but here they make the loading code
  much more succinct while still properly handling a variety of errors,
  ranging from API calls failing to integer overflow and allocation
  failure.  The exceptions are converted to error codes at the
  API boundary.)

Co-authored-by: Pavol Rusnak <pavol@rusnak.io> (for the bit I copied from #740)
2023-04-10 01:10:46 +02:00
unbounded
62cfc54f77
Add quantize-stats command for testing quantization (#728)
Command that calculates some statistics over the errors introduced by
quantization, like mean square error, max error and some percentile errors for layer
weights. Should be useful for testing quantization improvements.

Exposes some internal state from ggml and llama for testing
2023-04-08 00:09:18 +02:00
Georgi Gerganov
986b6ce9f9
ggml, llama : avoid heavy V transpose + improvements (#775)
ggml :

- added ggml_view_3d()
- ggml_view_tensor() now inherits the stride too
- reimplement ggml_cpy() to account for dst stride
- no longer require tensor->data to be memory aligned

llama :

- compute RoPE on 32-bit tensors (should be more accurate)
- store RoPE-ed K in the KV cache
- store transposed V in the KV cache (significant speed-up)
- avoid unnecessary Q copy
2023-04-05 22:07:33 +03:00
Marian Cepok
c0bb1d3ce2
ggml : change ne to int64_t (#626) 2023-04-02 13:21:31 +03:00
Justine Tunney
6f23ba5ee2 Ensure --mlock works properly with mmap() support 2023-03-30 12:28:25 -07:00
Slaren
c03ae8dca1 Add mmap support for model files 2023-03-30 12:28:25 -07:00
Stephan Walter
c1f885067c
ggml : introduce structs for the q4 data blocks (#356)
* Introduce structs for the q4 data blocks

* ggml : rename quant struct variables + fix ARM_NEON

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-03-28 18:56:03 +03:00
comex
563cdc391d
Support calling mlock() on loaded model data on Linux and macOS (#453)
* Support calling mlock() on loaded model data on Linux and macOS

This is enabled by a new --mlock command line option.

Using mlock() disables swapping and memory compression for the model
data.  Doing so can be useful on systems where the model takes up a
large fraction of system RAM.  In my experience, macOS is quite eager to
start compressing llama.cpp's memory, which then makes it halt for a few
seconds while it decompresses, even with a model that uses "only" 25GB
out of 32GB.

Of course, this comes at the cost of forcing the system to swap or
compress other processes' memory instead, so it needs to be used with
care and shouldn't be enabled by default.

In theory it should be possible to support this on Windows as well using
VirtualLock(), but I'm not much of a Windows user.

* Update llama.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-03-24 17:19:05 +02:00
Stephan Walter
69c92298a9
Deduplicate q4 quantization functions (#383)
* Deduplicate q4 quantization functions

* Use const; add basic test

* Re-enable quantization test

* Disable AVX2 flags in CI

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-03-22 19:29:06 +02:00
Georgi Gerganov
f5a77a629b
Introduce C-style API (#370)
* Major refactoring - introduce C-style API

* Clean up

* Add <cassert>

* Add <iterator>

* Add <algorithm> ....

* Fix timing reporting and accumulation

* Measure eval time only for single-token calls

* Change llama_tokenize return meaning
2023-03-22 07:32:36 +02:00
hoangmit
6eac39ba95
Add RMS norm and use it (#187)
* add ggml_rms_norm

* update op num
2023-03-16 00:41:38 +02:00
Georgi Gerganov
26c0846629
Initial release 2023-03-10 20:56:40 +02:00