* llama/ggml: add LLM training support
more compact progress bar
llama_save_model_to_file
llama_opt_param_filter
ggml_graph_dup force_grads
refactor ggml_opt, fix test-opt
* remove logits_all
* refactor CUDA implementation for ACC
* reset graph at beginning of opt period
* vulkan: scalar flash attention implementation
* vulkan: always use fp32 for scalar flash attention
* vulkan: use vector loads in scalar flash attention shader
* vulkan: remove PV matrix, helps with register usage
* vulkan: reduce register usage in scalar FA, but perf may be slightly worse
* vulkan: load each Q value once. optimize O reduction. more tuning
* vulkan: support q4_0/q8_0 KV in scalar FA
* CI: increase timeout to accommodate newly-supported tests
* vulkan: for scalar FA, select between 1 and 8 rows
* vulkan: avoid using Float16 capability in scalar FA
* sycl : Implemented reorder Q4_0 mmvq
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
* sycl : Fixed mmvq being called when reorder is disabled
* sycl : Improved comments in the quants header
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
* Use static_assert
* safe_div -> ceil_div
* Clarify qi comment
* change the reorder tensor from init to execute OP
* dbg
* Undo changes to test-backend-ops
* Refactor changes on top of q4_0 reorder fix
* Missing Reverts
* Refactored opt_for_reorder logic to simplify code path
* Explicit inlining and unroll
* Renamed mul_mat_algo enum for consistency
---------
Signed-off-by: Alberto Cabrera <alberto.cabrera@codeplay.com>
Co-authored-by: romain.biessy <romain.biessy@codeplay.com>
This assert fired running Qwen_Qwen3-30B-A3B-Q2_K.gguf:
GGML_ASSERT(nei0 * nei1 <= 3072);
The tensor is 8 x 512. Increase this array size to accommodate.
* vad : add initial Voice Activity Detection (VAD) support
This commit add support for Voice Activity Detection (VAD). When enabled
this feature will process the audio input and detect speech segments.
This information is then used to reduce the number of samples that need
to be processed by whisper_full.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3003
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit adds a description of the color scheme used in the CLI
when the --print-colors option is enabled.
The motivation for this is that it is not immediately clear what the
color scheme is when using the CLI with the --print-colors option.
Example output:
```console
$ ./build/bin/whisper-cli -f samples/jfk.wav --print-colors
...
main: color scheme: red (low confidence), yellow (medium), green (high confidence)
[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.
```
The description will not be dispayed if the `--no-prints` options is
set.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3135
This commit updates the link to Paul Tol's color scheme in the
`examples/common.h` file. The previous link was outdated and
pointed to a non-existent page.
* Test Ruby bindings' extra options only when commanded
* ruby : test extra build options only when env var specified
* Fix extra_options
* Update gem date
This commit omits the test for `test_build_options` when run locally as
it currently fails on Linux and MacOS platforms.
`
The motivation for this change is that currently when running the tests
locally on a non-macOS platform the test fails with the following error:
```console
.F
========================================================================
Failure: test_build_options(TestPackage):
<["ACCELERATE_FRAMEWORK",
"CMAKE_OSX_ARCHITECTURES",
"CMAKE_OSX_SYSROOT",
"FOUNDATION_LIBRARY",
"METALKIT_FRAMEWORK",
"METAL_FRAMEWORK"]> was expected to be empty.
/home/danbev/work/ai/whisper.cpp/bindings/ruby/tests/test_package.rb:43:in `test_build_options'
40: options = BuildOptions::Options.new
41: assert_empty options.missing_options
42: unless ENV["CI"]
=> 43: assert_empty options.extra_options
44: end
45: end
46: end
========================================================================
```
This commit adds HEAPU8 to the list of exported methods.
The motivation for this commit is that currently this is causing an error on Window systems where HEAPU8 in undefined, which results in the following error message in the web console:
main.js:1 Uncaught TypeError:
Cannot read properties of undefined (reading 'buffer') at __emval_get_property
(main.js:1:1363125) at 003a453a:0xc4a47 at 003a453a:0xc51cd at
Object.full_default (eval at craftInvokerFunction (main.js:1:1347011),
<anonymous>:9:10) at whisper.cpp/:647:42
danbev originally fixed this for whisper.wasm, stream.wasm, and command.stream, but the issue still exists on the other examples which I patch in this code.
Resolves: #3059
This commit updates the documentation for the WASM examples to include a
note about the generation of the `worker.js` file. As of Emscripten
3.1.58 (April 2024), separate worker.js files are no longer generated
and the worker is embedded in the main JS file.
The motivation for this change is to inform users about the new behavior
of Emscripten and why the `worker.js` file may not be present.
Refs: https://github.com/ggml-org/whisper.cpp/issues/3123
* whisper : deprecate WHISPER_CCACHE CMake option
This commit deprecates the WHISPER_CCACHE CMake option in favor of
the GGML_CCACHE option.
The motivation for this change is that currently when setting, or not
setting WHISPER_CCACHE, the outut message from ggml will be that to
enable ccache you need to set GGML_CCACHE which can be confusing.
This also seems to be inline with what llama.cpp does which does not
have a LLAMA_CCACHE option as far as I know.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3063
* ruby : change "WHISPER_CCACHE" to "GGML_CCACHE"
* ruby : move GGML_CCACHE to sorted position
* stream.wasm : add HEAPU8 to exported runtime methods
This commit adds HEAPU8 to the list of exported methods for stream.wasm.
The motivation for this is that without it HEAPUD8 will be undefined
and when its 'buffer' attribute is accessed this will cause error as
reported in the referenced issue.
Note that to test this make sure that the web browsers caches is cleared
first.
Resolves: https://github.com/ggml-org/whisper.cpp/issues/3123
* command.wasm : add HEAPU8 to exported runtime methods
This patch upstreams llamafile's cpu matrix multiplication kernels for ppc64le using MMA builtins for BF16 data type.
This change results in 9x - 40x gains
in total speed S t/s (ie all tokens/total time), across various batch sizes tested using llama-batched-bench benchmark.
The patch is tested with Meta-Lllama-3-8B,
and Mistral-7B models (BF16 models generated by using llama-quantize from corresponding FP32 models) on an IBM POWER10 machine.
Signed-off-by: Shalini Salomi Bodapati <Shalini.Salomi.Bodapati@ibm.com>
The following scenario will cause an assertion failure in the graph
allocator:
- Build and allocate a graph containing a tensor with a non-NULL data
pointer
- Build and allocate a new graph where that data is NULL
Result:
ggml-alloc.c:819: GGML_ASSERT(talloc->buffer_id >= 0) failed
This happens during revalidation because we think that memory should
have been previously allocated based on the current graph but in
reality the previous graph was different. In this situation, we
should do a full reallocation pass.
