mirror of
https://git.adityakumar.xyz/llama.cpp.git
synced 2024-11-09 15:29:43 +00:00
cfa0750bc9
* add interface for float input * fixed inpL shape and type * add examples of input floats * add test example for embd input * fixed sampling * add free for context * fixed add end condition for generating * add examples for llava.py * add READMD for llava.py * add READMD for llava.py * add example of PandaGPT * refactor the interface and fixed the styles * add cmake build for embd-input * add cmake build for embd-input * Add MiniGPT-4 example * change the order of the args of llama_eval_internal * fix ci error
71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
import ctypes
|
|
from ctypes import cdll, c_char_p, c_void_p, POINTER, c_float, c_int
|
|
import numpy as np
|
|
import os
|
|
|
|
libc = cdll.LoadLibrary("./libembdinput.so")
|
|
libc.sampling.restype=c_char_p
|
|
libc.create_mymodel.restype=c_void_p
|
|
libc.eval_string.argtypes=[c_void_p, c_char_p]
|
|
libc.sampling.argtypes=[c_void_p]
|
|
libc.eval_float.argtypes=[c_void_p, POINTER(c_float), c_int]
|
|
|
|
|
|
class MyModel:
|
|
def __init__(self, args):
|
|
argc = len(args)
|
|
c_str = [c_char_p(i.encode()) for i in args]
|
|
args_c = (c_char_p * argc)(*c_str)
|
|
self.model = c_void_p(libc.create_mymodel(argc, args_c))
|
|
self.max_tgt_len = 512
|
|
self.print_string_eval = True
|
|
|
|
def __del__(self):
|
|
libc.free_mymodel(self.model)
|
|
|
|
def eval_float(self, x):
|
|
libc.eval_float(self.model, x.astype(np.float32).ctypes.data_as(POINTER(c_float)), x.shape[1])
|
|
|
|
def eval_string(self, x):
|
|
libc.eval_string(self.model, x.encode()) # c_char_p(x.encode()))
|
|
if self.print_string_eval:
|
|
print(x)
|
|
|
|
def eval_token(self, x):
|
|
libc.eval_id(self.model, x)
|
|
|
|
def sampling(self):
|
|
s = libc.sampling(self.model)
|
|
return s
|
|
|
|
def stream_generate(self, end="</s>"):
|
|
ret = b""
|
|
end = end.encode()
|
|
for _ in range(self.max_tgt_len):
|
|
tmp = self.sampling()
|
|
ret += tmp
|
|
yield tmp
|
|
if ret.endswith(end):
|
|
break
|
|
|
|
def generate_with_print(self, end="</s>"):
|
|
ret = b""
|
|
for i in self.stream_generate(end=end):
|
|
ret += i
|
|
print(i.decode(errors="replace"), end="", flush=True)
|
|
print("")
|
|
return ret.decode(errors="replace")
|
|
|
|
|
|
def generate(self, end="</s>"):
|
|
text = b"".join(self.stream_generate(end=end))
|
|
return text.decode(errors="replace")
|
|
|
|
if __name__ == "__main__":
|
|
model = MyModel(["main", "--model", "../llama.cpp/models/ggml-vic13b-q4_1.bin", "-c", "2048"])
|
|
model.eval_string("""user: what is the color of the flag of UN?""")
|
|
x = np.random.random((5120,10))# , dtype=np.float32)
|
|
model.eval_float(x)
|
|
model.eval_string("""assistant:""")
|
|
for i in model.generate():
|
|
print(i.decode(errors="replace"), end="", flush=True)
|