mlx-examples/llms/mlx_lm/generate.py
Baptiste Canton 42672f5446
add an option to apply the tokenizer chat template (#338)
* add an option to apply the tokenizer chat template

* fix the option to apply the tokenizer chat template

* better error messages for chat template issues

* apply the chat template by default when possible

* nit in comment'

* rebase

---------

Co-authored-by: Awni Hannun <awni@apple.com>
2024-01-22 19:52:42 -08:00

113 lines
3.2 KiB
Python

import argparse
import time
import mlx.core as mx
from .utils import generate_step, load
DEFAULT_MODEL_PATH = "mlx_model"
DEFAULT_PROMPT = "hello"
DEFAULT_MAX_TOKENS = 100
DEFAULT_TEMP = 0.6
DEFAULT_SEED = 0
def setup_arg_parser():
"""Set up and return the argument parser."""
parser = argparse.ArgumentParser(description="LLM inference script")
parser.add_argument(
"--model",
type=str,
default="mlx_model",
help="The path to the local model directory or Hugging Face repo.",
)
parser.add_argument(
"--trust-remote-code",
action="store_true",
help="Enable trusting remote code for tokenizer",
)
parser.add_argument(
"--eos-token",
type=str,
default=None,
help="End of sequence token for tokenizer",
)
parser.add_argument(
"--prompt", default=DEFAULT_PROMPT, help="Message to be processed by the model"
)
parser.add_argument(
"--max-tokens",
"-m",
type=int,
default=DEFAULT_MAX_TOKENS,
help="Maximum number of tokens to generate",
)
parser.add_argument(
"--temp", type=float, default=DEFAULT_TEMP, help="Sampling temperature"
)
parser.add_argument("--seed", type=int, default=DEFAULT_SEED, help="PRNG seed")
parser.add_argument(
"--ignore-chat-template",
action="store_true",
help="Use the raw prompt without the tokenizer's chat template.",
)
return parser
def main(args):
mx.random.seed(args.seed)
# Building tokenizer_config
tokenizer_config = {"trust_remote_code": True if args.trust_remote_code else None}
if args.eos_token is not None:
tokenizer_config["eos_token"] = args.eos_token
model, tokenizer = load(args.model, tokenizer_config=tokenizer_config)
if not args.ignore_chat_template and (
hasattr(tokenizer, "apply_chat_template")
and tokenizer.chat_template is not None
):
messages = [{"role": "user", "content": args.prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
else:
prompt = args.prompt
print("=" * 10)
print("Prompt:", prompt)
prompt = tokenizer.encode(prompt)
prompt = mx.array(prompt)
tic = time.time()
tokens = []
skip = 0
for token, n in zip(
generate_step(prompt, model, args.temp), range(args.max_tokens)
):
if token == tokenizer.eos_token_id:
break
if n == 0:
prompt_time = time.time() - tic
tic = time.time()
tokens.append(token.item())
s = tokenizer.decode(tokens)
print(s[skip:], end="", flush=True)
skip = len(s)
print(tokenizer.decode(tokens)[skip:], flush=True)
gen_time = time.time() - tic
print("=" * 10)
if len(tokens) == 0:
print("No tokens generated for this prompt")
return
prompt_tps = prompt.size / prompt_time
gen_tps = (len(tokens) - 1) / gen_time
print(f"Prompt: {prompt_tps:.3f} tokens-per-sec")
print(f"Generation: {gen_tps:.3f} tokens-per-sec")
if __name__ == "__main__":
parser = setup_arg_parser()
args = parser.parse_args()
main(args)