Update llama.cpp

This commit is contained in:
Andrei Betlen 2023-07-13 23:24:55 -04:00
parent 7bb0024cd0
commit 896ab7b88a
2 changed files with 50 additions and 7 deletions

View file

@ -326,13 +326,23 @@ _lib.llama_mlock_supported.restype = c_bool
# // Initialize the llama + ggml backend # // Initialize the llama + ggml backend
# // If numa is true, use NUMA optimizations # // If numa is true, use NUMA optimizations
# // Call once at the start of the program # // Call once at the start of the program
# LLAMA_API void llama_init_backend(bool numa); # LLAMA_API void llama_backend_init(bool numa);
def llama_init_backend(numa: c_bool): def llama_backend_init(numa: c_bool):
return _lib.llama_init_backend(numa) return _lib.llama_backend_init(numa)
_lib.llama_init_backend.argtypes = [c_bool] _lib.llama_backend_init.argtypes = [c_bool]
_lib.llama_init_backend.restype = None _lib.llama_backend_init.restype = None
# // Call once at the end of the program - currently only used for MPI
# LLAMA_API void llama_backend_free();
def llama_backend_free():
return _lib.llama_backend_free()
_lib.llama_backend_free.argtypes = []
_lib.llama_backend_free.restype = None
# LLAMA_API struct llama_model * llama_load_model_from_file( # LLAMA_API struct llama_model * llama_load_model_from_file(
@ -819,6 +829,39 @@ _lib.llama_sample_frequency_and_presence_penalties.argtypes = [
_lib.llama_sample_frequency_and_presence_penalties.restype = None _lib.llama_sample_frequency_and_presence_penalties.restype = None
# /// @details Apply classifier-free guidance to the logits as described in academic paper "Stay on topic with Classifier-Free Guidance" https://arxiv.org/abs/2306.17806
# /// @param candidates A vector of `llama_token_data` containing the candidate tokens, the logits must be directly extracted from the original generation context without being sorted.
# /// @params guidance_ctx A separate context from the same model. Other than a negative prompt at the beginning, it should have all generated and user input tokens copied from the main context.
# /// @params scale Guidance strength. 1.0f means no guidance. Higher values mean stronger guidance.
# /// @params smooth_factor Smooth factor between guidance logits and original logits. 1.0f means only use guidance logits. 0.0f means only original logits.
# LLAMA_API void llama_sample_classifier_free_guidance(
# struct llama_context * ctx,
# llama_token_data_array * candidates,
# struct llama_context * guidance_ctx,
# float scale,
# float smooth_factor);
def llama_sample_classifier_free_guidance(
ctx: llama_context_p,
candidates, # type: _Pointer[llama_token_data_array]
guidance_ctx: llama_context_p,
scale: c_float,
smooth_factor: c_float,
):
return _lib.llama_sample_classifier_free_guidance(
ctx, candidates, guidance_ctx, scale, smooth_factor
)
_lib.llama_sample_classifier_free_guidance.argtypes = [
llama_context_p,
llama_token_data_array_p,
llama_context_p,
c_float,
c_float,
]
_lib.llama_sample_classifier_free_guidance.restype = None
# @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits. # @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.
# LLAMA_API void llama_sample_softmax(struct llama_context * ctx, llama_token_data_array * candidates); # LLAMA_API void llama_sample_softmax(struct llama_context * ctx, llama_token_data_array * candidates);
def llama_sample_softmax( def llama_sample_softmax(
@ -1063,5 +1106,5 @@ _lib.llama_print_system_info.restype = c_char_p
_llama_initialized = False _llama_initialized = False
if not _llama_initialized: if not _llama_initialized:
llama_init_backend(c_bool(False)) llama_backend_init(c_bool(False))
_llama_initialized = True _llama_initialized = True

2
vendor/llama.cpp vendored

@ -1 +1 @@
Subproject commit 1d1630996920f889cdc08de26cebf2415958540e Subproject commit 32c54116318929c90fd7ae814cf9b5232cd44c36