* bench : cache llama_context state at depth
* cont : handle failures to restore the old state
* cont : print information when the state is being reused
* kv-cache : pad the size of the small SWA cache for performance
* context : pad the total context to 256
* cont : future-proof the swa pad
* server : adjust test params to new logic
When using GCC 9 and GCC 12 on the arm64 platform of ubuntu 2004,
the command "gcc -mcpu=native -E -v -" fails to detect the correct CPU flags,
which results in compilation failures for certain extended instructions,
but the correct CPU flags can be obtained by using gcc -march.
Signed-off-by: lizhenneng <lizhenneng@kylinos.cn>
Co-authored-by: lizhenneng <lizhenneng@kylinos.cn>
* common: move download functions to download.(cpp|h)
* rm unused includes
* minor cleanup
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Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* metal : rework mat-mat multiplication
* metal : initial Metal4 support
* cont
* metal : detect tensor support
* cont : better ifdefs
* metal : support tensors in mul_mm_id
* metal : add env for disabling tensor API
* tests : restore
* metal : remove unused constants
* metal : fix check for bfloat tensor support
* cont : handle API incompatibilities
* cont : handle even more incompatibilities
* metal : use tensor API only on M5 and later
* support older socs where FASTRPC_GET_URI is unsupported
* added graceful fallback when FASTRPC_GET_URI call fails
* use weak symbols instead of loading libcdsprpc.so dynamically
* Add weak pragma for rpcmem_alloc2
* Remove weak declaration for rpcmem_alloc2 in ggml-hexagon.cpp
Removed weak declaration for rpcmem_alloc2.
* Enforce ndev to 1 for archs below v75
Force ndev to 1 for SoCs architectures lower than v75.
* WIP
* added a cpy kernel specific to transposed tensor which uses smem to avoid uncoalesced access; test cases also added shwoing improved memory bandwidth
* added BF16 support
* more strict check to make sure src0 is a transpose
* reformulated to handle more complicated transpose cases
* bring back 2D transpose for higher performance
* allow build on windows
* tranpose copy more shapes
* minor tweak
* final clean up
* restore some test cases
* keep only the kernel for true tranposed case; updated with review suggestions
* make CI happy
* remove headers not needed
* reduced bank conflicts for fp16 and bf16
* add missing const*
* now bank conflicts free
* use padding instead of swizzling
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Co-authored-by: bssrdf <bssrdf@gmail.com>
* feat(llama-gguf): Print out the tensor type in llama-gguf r
Branch: Mamba2Perf
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* feat(off-topic): print the number of elements in tensors with llama-gguf
Branch: Mamba2SSD
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* style: valign
Branch: GGUFToolOutputs
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
* Update examples/gguf/gguf.cpp
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Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Add buffer label and enable dawn-specific toggles to turn off some checks
* Minor set_rows optimization (#4)
* updated optimization, fixed errors
* non vectorized version now dispatches one thread per element
* Simplify
* Change logic for set_rows pipelines
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Co-authored-by: Neha Abbas <nehaabbas@macbookpro.lan>
Co-authored-by: Neha Abbas <nehaabbas@ReeseLevines-MacBook-Pro.local>
Co-authored-by: Reese Levine <reeselevine1@gmail.com>
* Comment on dawn toggles
* Remove some comments
* Implement overlap binary operators
* Revert "Implement overlap binary operators"
This reverts commit ed710b36f5.
* Disable support for non-contiguous binary_op tensors and leave note for future support
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Co-authored-by: neha-ha <137219201+neha-ha@users.noreply.github.com>
Co-authored-by: Neha Abbas <nehaabbas@macbookpro.lan>
Co-authored-by: Neha Abbas <nehaabbas@ReeseLevines-MacBook-Pro.local>
* Fix test-conv2d-dw failure on ARM SVE by using runtime vector length
The ggml_compute_forward_conv_2d_dw_cwhn function was using a hardcoded GGML_F32_EPR (8) for SIMD vectorization, but on ARM SVE the actual vector length varies by hardware. This caused incorrect computation when processing CWHN layout tensors on ARM machines.
Fix by using svcntw() to get the runtime SVE vector length instead of the compile-time constant.
Co-authored-by: ggerganov <1991296+ggerganov@users.noreply.github.com>
* ci : reduce sam score threshold
* ci : update bbox checks for sam test
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Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: ggerganov <1991296+ggerganov@users.noreply.github.com>
* vulkan: remove the need for the dryrun
Allocate pipelines and descriptor sets when requested.
Reallocate the prealloc buffers when needed, and flush any pending work
before reallocating.
For rms_partials and total_mul_mat_bytes, use the sizes computed the last time
the graph was executed.
* remove dryrun parameters
* Fix garbled output with REPACK at high thread counts
Fixed a race condition in the REPACK matrix multiplication code that caused garbled output when using 26+ threads (model-dependent threshold). The issue occurred because with high thread counts, the code forced chunk count to equal thread count, creating many small chunks. After aligning these chunks to NB_COLS boundaries, adjacent chunks could overlap, causing data corruption and race conditions. The fix enforces minimum chunk sizes based on NB_COLS and caps maximum chunk count to prevent creating too many tiny chunks, ensuring proper alignment without overlaps.
* Update ggml/src/ggml-cpu/repack.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Update ggml/src/ggml-cpu/repack.cpp
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit modifies the script `run-org-model.py` to ensure that the
model configuration is explicitly passed to the `from_pretrained` method
when loading the model. It also removes a duplicate configuration
loading which was a mistake.
The motivation for this change is that enables the config object to be
modified and then passed to the model loading function, which can be
useful when testing new models.
