* llama : deprecate softmax sampler + fix dist sampler
ggml-ci
* tests : replace macros with functions
ggml-ci
* sampling : change temperature sampler logic
For t <= 0.0f, keep the max logit intact and set the rest to -inf
* cont : no need for special "greedy" logic
top-k == 1 is the same
* tests : init prob correctly
* llama : handle temp <= 0.0 in the temp_ext sampler too
ggml-ci
* cont : avoid extra loop in temperature sampler for sub-zero temp
ggml-ci
llama_cpp_canister allows you to run llama.cpp as a Smart Contract on the Internet Computer. The smart contract runs as WebAssembly in a so-called 'canister'.
add intel amx isa detection
add vnni kernel for gemv cases
add vnni and amx kernel support for block_q8_0
code cleanup
fix packing B issue
enable openmp
fine tune amx kernel
switch to aten parallel pattern
add error message for nested parallelism
code cleanup
add f16 support in ggml-amx
add amx kernels for QK_K quant formats: Q4_K, Q5_K, Q6_K and IQ4_XS
update CMakeList
update README
fix some compilation warning
fix compiler warning when amx is not enabled
minor change
ggml-ci
move ggml_amx_init from ggml.c to ggml-amx/mmq.cpp
ggml-ci
update CMakeLists with -mamx-tile, -mamx-int8 and -mamx-bf16
ggml-ci
add amx as an ggml-backend
update header file, the old path for immintrin.h has changed to ggml-cpu-impl.h
minor change
update CMakeLists.txt
minor change
apply weight prepacking in set_tensor method in ggml-backend
fix compile error
ggml-ci
minor change
ggml-ci
update CMakeLists.txt
ggml-ci
add march dependency
minor change
ggml-ci
change ggml_backend_buffer_is_host to return false for amx backend
ggml-ci
fix supports_op
use device reg for AMX backend
ggml-ci
minor change
ggml-ci
minor change
fix rebase
set .buffer_from_host_ptr to be false for AMX backend
* fix: use `vm_allocate` to allocate CPU backend buffer on macOS
* fix: switch to `posix_memalign` to keep existing `free()` usages work
* feat: move `GGML_ALIGNED_MALLOC` to `ggml-backend-impl.h`, add support for `vm_allocate` on macOS
* style: formatting
* fix: move const outside of `#ifndef`
* style: formatting
* fix: unused var
* fix: transform `GGML_ALIGNED_MALLOC` and `GGML_ALIGNED_FREE` into functions and add them to `ggml-impl.h`
* fix: unused var
* fix: page align to `GGUF_DEFAULT_ALIGNMENT`
* fix: page align to `TENSOR_ALIGNMENT`
* fix: convert `TENSOR_ALIGNMENT` to a macro
* fix: increase page size to `32` on iOS
* fix: iOS page size
* fix: `hbw_posix_memalign` alignment
* llama : suppress conversion from 'size_t' to 'int'
This commit updates llm_tokenizer_spm.tokenize to suppress/remove the
following warnings that are generated on Windows when using MSVC:
```console
src\llama-vocab.cpp(211,1): warning C4267: 'argument':
conversion from 'size_t' to 'int', possible loss of data
src\llama-vocab.cpp(517,1): warning C4267: 'argument':
conversion from 'size_t' to 'int', possible loss of data
```
This is done by adding a cast for the size_t returned from
symbols.size(). I believe this is safe as it seems unlikely that
symbols, which stores an entry for each UTF8 character, would become
larger than INT_MAX.
The motivation for this change is to reduce the number of warnings that
are currently generated when building on Windows.
* squash! llama : suppress conversion from 'size_t' to 'int'
Move cast into for loop.
Prior to this commit, using a JSON Schema containing a string
with `pattern` regular expression that uses top-level alternation
(e.g. `"pattern": "^A|B|C|D$"`) would result in invalid JSON
output from the constrained sampling grammar, because it
ended up creating a grammar rule like this for the string:
```
thing ::= "\"" "A" | "B" | "C" | "D" "\"" space
```
Note that this rule will only match a starting quote for the "A" case,
and will only match an ending quote for the "D" case,
so this rule will always produce invalid JSON when used for sampling
(that is, the JSON will always be lacking the starting quote,
the ending quote, or both).
This was fixed in a simple way by adding parentheses to the
generated rule (for all string pattern rules, to keep it simple),
such that the new generated rule looks like this (correct):
```
thing ::= "\"" ("A" | "B" | "C" | "D") "\"" space
```
This commit removes the buffer_id field from the leaf_alloc struct.
The motivation for is that this field is only written to and never
read/used as far as I can tell. Each tensor_alloc has a buffer_id field
and this is what caused me to look into this more closely, to
understand what the buffer_id in leaf_alloc was used for.
* Initial XTC commit
Adds XTC sampler, not activated by default, but recommended settings by default.
* Cleanup
* Simplified chances calculation
To be more inline with the original implementation, chance is calculated once at the beginning.
* First fixes by comments
Still need to look into sorting
* Fixed trailing backspaces
* Fixed RNG to be reproduceable
Thanks to @slaren for directions
* Fixed forgotten header
* Moved `min_keep`
Moved from conditions to a simple check at the end.
* Fixed broken randomization
Thanks to @slaren for explanation
* Swapped sorting for a custom algorithm
Shifts tokens to remove the penalized ones, then puts the penalized at the back. Should make `min_keep` still viable.
* Algorithm rework
1. Scan token from top till the first non-penalizable
2. Remove the last captured token (the least probable above threshold)
3. Shift all tokens to override the remaining penalizable
4. Penalize and put them at the the bottom.
* Added XTC to `test-sampling`
* Simplified algorithm and more tests
* Updated info in common and args
* Merged back lost commits in common and arg
* Update dump info in common
* Fixed incorrect min_keep check
* Added XTC to README
* Renamed parameters, fixed info and defaults
* probability is at 0 by default, but XTC is included in sampling queue
* threshold higher than 0.5 switches XTC off
* Initial server support
* Added XTC to server UIs
* Fixed labels in old server UI
* Made algorithm safer and more readable
* Removed xtc_threshold_max
* Fixed arg after update
* Quick fixes by comments
* Simplified algorithm since threshold_max is removed
* Renamed random distribution
* Fixed tests and outdated README
* Small fixes
* Vectorize load instructions in dmmv f16 CUDA kernel
Replaces scalar with vector load instructions, which substantially
improves performance on NVIDIA HBM GPUs, e.g. gives a 1.27X overall
speedup for Meta-Llama-3-8B-Instruct-F16 BS1 inference evaluation on
H100 SXM 80GB HBM3. On GDDR GPUs, there is a slight (1.01X) speedup.
* addressed comment
* Update ggml/src/ggml-cuda/dmmv.cu
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* server : accept extra_context for the infill endpoint
ggml-ci
* server : update readme [no ci]
* server : use repo-level FIM pattern if possible
ggml-ci
* llama : improve infill support
ggml-ci
* llama : add more FIM token strings
ggml-ci
* server : update prompt on slot restore (#9800)
* gguf : deprecate old FIM token KVs
* ggml : do not use BLAS with types without to_float
* ggml : return pointer from ggml_internal_get_type_traits to avoid unnecessary copies
* ggml : rename ggml_internal_get_type_traits -> ggml_get_type_traits
it's not really internal if everybody uses it
