vbatts/llama.cpp
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Update llama.cpp

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This commit is contained in:
Andrei Betlen 2023-04-11 11:59:03 -04:00 • committed by Don Mahurin
parent ce0ca60b56
commit d595f330e2
1 changed files with 27 additions and 5 deletions
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32
examples/llama_cpp.py
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@ -11,10 +11,11 @@ from ctypes import (
Structure,
Array,
c_uint8,
c_size_t
c_size_t,
)
import pathlib
# Load the library
def _load_shared_library(lib_base_name):
# Determine the file extension based on the platform
@ -33,10 +34,10 @@ def _load_shared_library(lib_base_name):
# for llamacpp) and "llama" (default name for this repo)
_lib_paths = [
_base_path / f"lib{lib_base_name}{lib_ext}",
_base_path / f"{lib_base_name}{lib_ext}"
_base_path / f"{lib_base_name}{lib_ext}",
]
if ("LLAMA_CPP_LIB" in os.environ):
if "LLAMA_CPP_LIB" in os.environ:
lib_base_name = os.environ["LLAMA_CPP_LIB"]
_lib = pathlib.Path(lib_base_name)
_base_path = _lib.parent.resolve()
@ -54,7 +55,10 @@ def _load_shared_library(lib_base_name):
except Exception as e:
raise RuntimeError(f"Failed to load shared library '{_lib_path}': {e}")
raise FileNotFoundError(f"Shared library with base name '{lib_base_name}' not found")
raise FileNotFoundError(
f"Shared library with base name '{lib_base_name}' not found"
)
# Specify the base name of the shared library to load
_lib_base_name = "llama"
@ -106,6 +110,10 @@ class llama_context_params(Structure):
llama_context_params_p = POINTER(llama_context_params)
LLAMA_FTYPE_ALL_F32 = ctypes.c_int(0)
LLAMA_FTYPE_MOSTLY_F16 = ctypes.c_int(1) # except 1d tensors
LLAMA_FTYPE_MOSTLY_Q4_0 = ctypes.c_int(2) # except 1d tensors
LLAMA_FTYPE_MOSTLY_Q4_1 = ctypes.c_int(3) # except 1d tensors
# Functions
@ -117,18 +125,23 @@ def llama_context_default_params() -> llama_context_params:
_lib.llama_context_default_params.argtypes = []
_lib.llama_context_default_params.restype = llama_context_params
def llama_mmap_supported() -> c_bool:
return _lib.llama_mmap_supported()
_lib.llama_mmap_supported.argtypes = []
_lib.llama_mmap_supported.restype = c_bool
def llama_mlock_supported() -> c_bool:
return _lib.llama_mlock_supported()
_lib.llama_mlock_supported.argtypes = []
_lib.llama_mlock_supported.restype = c_bool
# Various functions for loading a ggml llama model.
# Allocate (almost) all memory needed for the model.
# Return NULL on failure
@ -162,33 +175,42 @@ def llama_model_quantize(
_lib.llama_model_quantize.argtypes = [c_char_p, c_char_p, c_int]
_lib.llama_model_quantize.restype = c_int
# Returns the KV cache that will contain the context for the
# ongoing prediction with the model.
def llama_get_kv_cache(ctx: llama_context_p):
return _lib.llama_get_kv_cache(ctx)
_lib.llama_get_kv_cache.argtypes = [llama_context_p]
_lib.llama_get_kv_cache.restype = POINTER(c_uint8)
# Returns the size of the KV cache
def llama_get_kv_cache_size(ctx: llama_context_p) -> c_size_t:
return _lib.llama_get_kv_cache_size(ctx)
_lib.llama_get_kv_cache_size.argtypes = [llama_context_p]
_lib.llama_get_kv_cache_size.restype = c_size_t
# Returns the number of tokens in the KV cache
def llama_get_kv_cache_token_count(ctx: llama_context_p) -> c_int:
return _lib.llama_get_kv_cache_token_count(ctx)
_lib.llama_get_kv_cache_token_count.argtypes = [llama_context_p]
_lib.llama_get_kv_cache_token_count.restype = c_int
# Sets the KV cache containing the current context for the model
def llama_set_kv_cache(ctx: llama_context_p, kv_cache, n_size: c_size_t, n_token_count: c_int):
def llama_set_kv_cache(
ctx: llama_context_p, kv_cache, n_size: c_size_t, n_token_count: c_int
):
return _lib.llama_set_kv_cache(ctx, kv_cache, n_size, n_token_count)
_lib.llama_set_kv_cache.argtypes = [llama_context_p, POINTER(c_uint8), c_size_t, c_int]
_lib.llama_set_kv_cache.restype = None