baalajimaestro/llama.cpp
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feat: Update llama.cpp

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This commit is contained in:
Andrei Betlen 2024-02-28 14:27:16 -05:00
parent ffcd4b2636
commit 0d37ce52b1
3 changed files with 5 additions and 145 deletions
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144
llama_cpp/llama_cpp.py
View file

@ -111,6 +111,7 @@ if TYPE_CHECKING:
F = TypeVar("F", bound=Callable[..., Any]) F = TypeVar("F", bound=Callable[..., Any])
def ctypes_function_for_shared_library(lib: ctypes.CDLL): def ctypes_function_for_shared_library(lib: ctypes.CDLL):
def ctypes_function( def ctypes_function(
name: str, argtypes: List[Any], restype: Any, enabled: bool = True name: str, argtypes: List[Any], restype: Any, enabled: bool = True
@ -938,18 +939,6 @@ def llama_supports_gpu_offload() -> bool:
... ...
# LLAMA_API DEPRECATED(bool llama_mmap_supported (void), "use llama_supports_mmap() instead");
@ctypes_function("llama_mmap_supported", [], ctypes.c_bool)
def llama_mmap_supported() -> bool:
...
# LLAMA_API DEPRECATED(bool llama_mlock_supported(void), "use llama_supports_mlock() instead");
@ctypes_function("llama_mlock_supported", [], ctypes.c_bool)
def llama_mlock_supported() -> bool:
...
# LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx); # LLAMA_API const struct llama_model * llama_get_model(const struct llama_context * ctx);
@ctypes_function("llama_get_model", [llama_context_p_ctypes], llama_model_p_ctypes) @ctypes_function("llama_get_model", [llama_context_p_ctypes], llama_model_p_ctypes)
def llama_get_model(ctx: llama_context_p, /) -> Optional[llama_model_p]: def llama_get_model(ctx: llama_context_p, /) -> Optional[llama_model_p]:
@ -1158,47 +1147,6 @@ def llama_model_quantize(
... ...
# // Apply a LoRA adapter to a loaded model
# // path_base_model is the path to a higher quality model to use as a base for
# // the layers modified by the adapter. Can be NULL to use the current loaded model.
# // The model needs to be reloaded before applying a new adapter, otherwise the adapter
# // will be applied on top of the previous one
# // Returns 0 on success
# LLAMA_API DEPRECATED(int32_t llama_apply_lora_from_file(
# struct llama_context * ctx,
# const char * path_lora,
# float scale,
# const char * path_base_model,
# int32_t n_threads),
# "use llama_model_apply_lora_from_file instead");
@ctypes_function(
"llama_apply_lora_from_file",
[
llama_context_p_ctypes,
ctypes.c_char_p,
ctypes.c_float,
ctypes.c_char_p,
ctypes.c_int32,
],
ctypes.c_int32,
)
def llama_apply_lora_from_file(
ctx: llama_context_p,
path_lora: Union[ctypes.c_char_p, bytes],
scale: Union[ctypes.c_float, float],
path_base_model: Union[ctypes.c_char_p, bytes],
n_threads: Union[ctypes.c_int32, int],
/,
) -> int:
"""Apply a LoRA adapter to a loaded model
path_base_model is the path to a higher quality model to use as a base for
the layers modified by the adapter. Can be NULL to use the current loaded model.
The model needs to be reloaded before applying a new adapter, otherwise the adapter
will be applied on top of the previous one
Returns 0 on success"""
...
# LLAMA_API int32_t llama_model_apply_lora_from_file( # LLAMA_API int32_t llama_model_apply_lora_from_file(
# const struct llama_model * model, # const struct llama_model * model,
# const char * path_lora, # const char * path_lora,
@ -1220,7 +1168,7 @@ def llama_model_apply_lora_from_file(
model: llama_model_p, model: llama_model_p,
path_lora: Union[ctypes.c_char_p, bytes], path_lora: Union[ctypes.c_char_p, bytes],
scale: Union[ctypes.c_float, float], scale: Union[ctypes.c_float, float],
path_base_model: Union[ctypes.c_char_p, bytes], path_base_model: Union[ctypes.c_char_p, bytes, None],
n_threads: Union[ctypes.c_int32, int], n_threads: Union[ctypes.c_int32, int],
/, /,
) -> int: ) -> int:
@ -1647,72 +1595,6 @@ def llama_save_session_file(
# // # //
# // Run the llama inference to obtain the logits and probabilities for the next token(s).
# // tokens + n_tokens is the provided batch of new tokens to process
# // n_past is the number of tokens to use from previous eval calls
# // Returns 0 on success
# // DEPRECATED: use llama_decode() instead
# LLAMA_API DEPRECATED(int llama_eval(
# struct llama_context * ctx,
# llama_token * tokens,
# int32_t n_tokens,
# int32_t n_past),
# "use llama_decode() instead");
@ctypes_function(
"llama_eval",
[
llama_context_p_ctypes,
llama_token_p,
ctypes.c_int32,
ctypes.c_int32,
],
ctypes.c_int,
)
def llama_eval(
ctx: llama_context_p,
tokens: CtypesArray[llama_token],
n_tokens: Union[ctypes.c_int, int],
n_past: Union[ctypes.c_int, int],
/,
) -> int:
"""Run the llama inference to obtain the logits and probabilities for the next token(s).
tokens + n_tokens is the provided batch of new tokens to process
n_past is the number of tokens to use from previous eval calls
Returns 0 on success
DEPRECATED: use llama_decode() instead"""
...
# // Same as llama_eval, but use float matrix input directly.
# // DEPRECATED: use llama_decode() instead
# LLAMA_API DEPRECATED(int llama_eval_embd(
# struct llama_context * ctx,
# float * embd,
# int32_t n_tokens,
# int32_t n_past),
# "use llama_decode() instead");
@ctypes_function(
"llama_eval_embd",
[
llama_context_p_ctypes,
ctypes.POINTER(ctypes.c_float),
ctypes.c_int32,
ctypes.c_int32,
],
ctypes.c_int,
)
def llama_eval_embd(
ctx: llama_context_p,
embd: CtypesArray[ctypes.c_float],
n_tokens: Union[ctypes.c_int, int],
n_past: Union[ctypes.c_int, int],
/,
) -> int:
"""Same as llama_eval, but use float matrix input directly.
DEPRECATED: use llama_decode() instead"""
...
# // Return batch for single sequence of tokens starting at pos_0 # // Return batch for single sequence of tokens starting at pos_0
# // # //
# // NOTE: this is a helper function to facilitate transition to the new batch API - avoid using it # // NOTE: this is a helper function to facilitate transition to the new batch API - avoid using it
@ -2474,28 +2356,6 @@ def llama_sample_temp(
... ...
# LLAMA_API DEPRECATED(void llama_sample_temperature(
# struct llama_context * ctx,
# llama_token_data_array * candidates,
# float temp),
# "use llama_sample_temp instead");
@ctypes_function(
"llama_sample_temperature",
[llama_context_p_ctypes, llama_token_data_array_p, ctypes.c_float],
None,
)
def llama_sample_temperature(
ctx: llama_context_p,
candidates: Union[
CtypesArray[llama_token_data_array], CtypesPointerOrRef[llama_token_data_array]
],
temp: Union[ctypes.c_float, float],
/,
):
"""use llama_sample_temp instead"""
...
# /// @details Apply constraints from grammar # /// @details Apply constraints from grammar
# LLAMA_API void llama_sample_grammar( # LLAMA_API void llama_sample_grammar(
# struct llama_context * ctx, # struct llama_context * ctx,

4
llama_cpp/server/settings.py
View file

@ -45,11 +45,11 @@ class ModelSettings(BaseSettings):
default=False, description="Whether to only return the vocabulary." default=False, description="Whether to only return the vocabulary."
) )
use_mmap: bool = Field( use_mmap: bool = Field(
default=llama_cpp.llama_mmap_supported(), default=llama_cpp.llama_supports_mmap(),
description="Use mmap.", description="Use mmap.",
) )
use_mlock: bool = Field( use_mlock: bool = Field(
default=llama_cpp.llama_mlock_supported(), default=llama_cpp.llama_supports_mlock(),
description="Use mlock.", description="Use mlock.",
) )
kv_overrides: Optional[List[str]] = Field( kv_overrides: Optional[List[str]] = Field(

2
vendor/llama.cpp vendored

@ -1 +1 @@
Subproject commit cb49e0f8c906e5da49e9f6d64a57742a9a241c6a Subproject commit 08c5ee87e4cceb603ecceac90734fcdade57311b