mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-03 19:57:35 +00:00
80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
import argparse
|
|
import os
|
|
import textwrap
|
|
|
|
from pathlib import Path
|
|
|
|
from toolchain.cli.subcommand import Subcommand
|
|
|
|
|
|
CONFIGS_BASE_DIR = f"{os.path.expanduser('~')}/.llama/configs/"
|
|
|
|
class InferenceConfigure(Subcommand):
|
|
"""Llama cli for configuring llama toolchain configs"""
|
|
|
|
def __init__(self, subparsers: argparse._SubParsersAction):
|
|
super().__init__()
|
|
self.parser = subparsers.add_parser(
|
|
"configure",
|
|
prog="llama inference configure",
|
|
description="Configure llama toolchain inference configs",
|
|
epilog=textwrap.dedent(
|
|
"""
|
|
Example:
|
|
llama inference configure
|
|
"""
|
|
),
|
|
formatter_class=argparse.RawTextHelpFormatter,
|
|
)
|
|
self._add_arguments()
|
|
self.parser.set_defaults(func=self._run_inference_configure_cmd)
|
|
|
|
def _add_arguments(self):
|
|
pass
|
|
|
|
def read_user_inputs(self):
|
|
checkpoint_dir = input("Enter the checkpoint directory for the model (e.g., ~/.llama/checkpoints/Meta-Llama-3-8B/): ")
|
|
model_parallel_size = input("Enter model parallel size (e.g., 1 for 8B / 8 for 70B and 405B): ")
|
|
|
|
return checkpoint_dir, model_parallel_size
|
|
|
|
def write_output_yaml(
|
|
self,
|
|
checkpoint_dir,
|
|
model_parallel_size,
|
|
yaml_output_path
|
|
):
|
|
yaml_content = textwrap.dedent(f"""
|
|
model_inference_config:
|
|
impl_type: "inline"
|
|
inline_config:
|
|
checkpoint_type: "pytorch"
|
|
checkpoint_dir: {checkpoint_dir}/
|
|
tokenizer_path: {checkpoint_dir}/tokenizer.model
|
|
model_parallel_size: {model_parallel_size}
|
|
max_seq_len: 2048
|
|
max_batch_size: 1
|
|
""")
|
|
with open(yaml_output_path, 'w') as yaml_file:
|
|
yaml_file.write(yaml_content.strip())
|
|
|
|
print(f"YAML configuration has been written to {yaml_output_path}")
|
|
|
|
def _run_inference_configure_cmd(self, args: argparse.Namespace) -> None:
|
|
checkpoint_dir, model_parallel_size = self.read_user_inputs()
|
|
checkpoint_dir = os.path.expanduser(checkpoint_dir)
|
|
|
|
if not (
|
|
checkpoint_dir.endswith("original") or
|
|
checkpoint_dir.endswith("original/")
|
|
):
|
|
checkpoint_dir = os.path.join(checkpoint_dir, "original")
|
|
|
|
os.makedirs(CONFIGS_BASE_DIR, exist_ok=True)
|
|
yaml_output_path = Path(CONFIGS_BASE_DIR) / "inference.yaml"
|
|
|
|
self.write_output_yaml(
|
|
checkpoint_dir,
|
|
model_parallel_size,
|
|
yaml_output_path,
|
|
)
|