* support smallthinker
* support 20b softmax, 4b no sliding window
* new build_moe_ffn_from_probs, and can run 4b
* fix 4b rope bug
* fix python type check
* remove is_moe judge
* remove set_dense_start_swa_pattern function and modify set_swa_pattern function
* trim trailing whitespace
* remove get_vocab_base of SmallThinkerModel in convert_hf_to_gguf.py
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* better whitespace
Apply suggestions from code review
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* use GGML_ASSERT for expert count validation
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Improve null pointer check for probs
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* use template parameter for SWA attention logic
* better whitespace
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* move the creation of inp_out_ids before the layer loop
* remove redundant judge for probs
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama : clarify comment about pp and tg graphs [no ci]
This commit clarifies the comment in `llama-context.cpp` regarding the
prefill prompt (pp), and token generation (tg) graphs.
The motivation for this is that I've struggled to remember these and had
to look them up more than once, so I thought it would be helpful to add
a comment that makes it clear what these stand for.
* squash! llama : clarify comment about pp and tg graphs [no ci]
Change "pp" to "prompt processing".
This commit adds support for MFMA instructions to MMQ. CDNA1/GFX908 CDNA2/GFX90a and CDNA3/GFX942 are supported by the MFMA-enabled code path added by this commit. The code path and stream-k is only enabled on CDNA3 for now as it fails to outperform blas in all cases on the other devices.
Blas is currently only consistently outperformed on CDNA3 due to issues in the amd-provided blas libraries.
This commit also improves the awareness of MMQ towards different warp sizes and as a side effect improves the performance of all quant formats besides q4_0 and q4_1, which regress slightly, on GCN gpus.
* feat: Add s_off as a parameter in the args struct
This may not be necessary, but it more closely mirrors the CUDA kernel
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* perf: Parallelize mamba2 SSM_SCAN metal kernel over d_state
This is a first attempt at optimizing the metal kernel. The changes here
are:
- Launch the kernel with a thread group of size d_state
- Use simd groups and shared memory to do the summation for the y
computation
When tested with G4 tiny preview, this shows roughly a 3x speedup on
prefill and 15% speedup on decode.
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Update logic to correctly do the multi-layer parallel sum
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* fix: Correctly size the shared memory bufer and assert expected size relationships
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* refactor: Compute block offsets once rather than once per token
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Use local variable for state recursion
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Use a secondary simd_sum instead of a for loop
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Add assertion and comment about relationship between simd size and num simd groups
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Parallelize of d_state for mamba-1
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat: Parallel sum in SSM_CONV
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* Revert "feat: Parallel sum in SSM_CONV"
After discussion with @compilade, the size of the parallelism here is
not worth the cost in complexity or overhead of the parallel for.
https://github.com/ggml-org/llama.cpp/pull/14743#discussion_r2223395357
This reverts commit 16bc059660.
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* refactor: Simplify shared memory sizing
Branch: GraniteFourPerf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-Authored-By: Georgi Gerganov <ggerganov@gmail.com>
---------
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This patch updates the example in docs/development/HOWTO-add-model.md to
reflect recent changes after `TextModel` and `MmprojModel` were introduced.
It replaces the outdated `Model` base class with `TextModel` or `MmprojModel`
and updates the registration example accordingly.
Signed-off-by: Wook Song <wook16.song@samsung.com>
Neither "g" nor "x" are valid portPos specifiers per the official
[graphviz documents](https://graphviz.org/docs/attr-types/portPos/):
> If a compass point is used, it must have the form "n","ne","e","se","s","sw","w","nw","c","_".
I tested locally for it to fall back to default portPos specifier if an
invalid portPos is specified. As a consequence, we can remove associated
code.
* CMake config: Create target only once
Fix error on repeated find_package(ggml).
For simplicity, check only for the top-level ggml::ggml.
* CMake config: Add CUDA link libs
* CMake config: Add OpenCL link libs
* CMake config: Use canonical find_dependency
Use set and append to control link lib variables.
Apply more $<LINK_ONLY...>.
* CMake config: Wire OpenMP dependency
This commit removes the inclusion of `<cstdlib>`.
The motivation for this change is that this source file does not seem to
use any functions from this header and the comment about `qsort` is a
little misleading/confusing.
MiniCPM models use the llm_build_granite constructor which was changed
in the Granite Four PR to use hparams.rope_finetuned instead of a
use_rope parameter. MiniCPM models need rope enabled by default.
Fixes inference from gibberish to correct responses.
* weight format to nz for 310p
* remove quant weight format to nz
* clean code
* fix
* make the conditions for converting weights to NZ format consistent
* clean code
