mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-28 10:54:19 +00:00
258 lines
9.6 KiB
Python
258 lines
9.6 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
|
# All rights reserved.
|
|
#
|
|
# This source code is licensed under the terms described in the LICENSE file in
|
|
# the root directory of this source tree.
|
|
|
|
import argparse
|
|
import asyncio
|
|
import os
|
|
import shutil
|
|
import time
|
|
from pathlib import Path
|
|
|
|
import httpx
|
|
|
|
from huggingface_hub import snapshot_download
|
|
from huggingface_hub.utils import GatedRepoError, RepositoryNotFoundError
|
|
|
|
from llama_models.datatypes import Model
|
|
from llama_models.sku_list import (
|
|
all_registered_models,
|
|
llama_meta_net_info,
|
|
resolve_model,
|
|
)
|
|
from termcolor import cprint
|
|
|
|
from llama_toolchain.cli.subcommand import Subcommand
|
|
from llama_toolchain.utils import DEFAULT_DUMP_DIR
|
|
|
|
|
|
DEFAULT_CHECKPOINT_DIR = os.path.join(DEFAULT_DUMP_DIR, "checkpoints")
|
|
|
|
|
|
class Download(Subcommand):
|
|
"""Llama cli for downloading llama toolchain assets"""
|
|
|
|
def __init__(self, subparsers: argparse._SubParsersAction):
|
|
super().__init__()
|
|
self.parser = subparsers.add_parser(
|
|
"download",
|
|
prog="llama download",
|
|
description="Download a model from llama.meta.comf or HuggingFace hub",
|
|
formatter_class=argparse.RawTextHelpFormatter,
|
|
)
|
|
self._add_arguments()
|
|
self.parser.set_defaults(func=self._run_download_cmd)
|
|
|
|
def _add_arguments(self):
|
|
models = all_registered_models()
|
|
self.parser.add_argument(
|
|
"--source",
|
|
choices=["meta", "huggingface"],
|
|
required=True,
|
|
)
|
|
self.parser.add_argument(
|
|
"--model-id",
|
|
choices=[x.descriptor() for x in models],
|
|
required=True,
|
|
)
|
|
self.parser.add_argument(
|
|
"--hf-token",
|
|
type=str,
|
|
required=False,
|
|
default=None,
|
|
help="Hugging Face API token. Needed for gated models like llama2/3. Will also try to read environment variable `HF_TOKEN` as default.",
|
|
)
|
|
self.parser.add_argument(
|
|
"--meta-url",
|
|
type=str,
|
|
required=False,
|
|
help="For source=meta, URL obtained from llama.meta.com after accepting license terms",
|
|
)
|
|
self.parser.add_argument(
|
|
"--ignore-patterns",
|
|
type=str,
|
|
required=False,
|
|
default="*.safetensors",
|
|
help="""
|
|
For source=huggingface, files matching any of the patterns are not downloaded. Defaults to ignoring
|
|
safetensors files to avoid downloading duplicate weights.
|
|
""",
|
|
)
|
|
|
|
def _hf_download(self, model: Model, hf_token: str, ignore_patterns: str):
|
|
repo_id = model.huggingface_repo
|
|
if repo_id is None:
|
|
raise ValueError(f"No repo id found for model {model.descriptor()}")
|
|
|
|
output_dir = Path(DEFAULT_CHECKPOINT_DIR) / model.descriptor()
|
|
os.makedirs(output_dir, exist_ok=True)
|
|
try:
|
|
true_output_dir = snapshot_download(
|
|
repo_id,
|
|
local_dir=output_dir,
|
|
ignore_patterns=ignore_patterns,
|
|
token=hf_token,
|
|
library_name="llama-toolchain",
|
|
)
|
|
except GatedRepoError:
|
|
self.parser.error(
|
|
"It looks like you are trying to access a gated repository. Please ensure you "
|
|
"have access to the repository and have provided the proper Hugging Face API token "
|
|
"using the option `--hf-token` or by running `huggingface-cli login`."
|
|
"You can find your token by visiting https://huggingface.co/settings/tokens"
|
|
)
|
|
except RepositoryNotFoundError:
|
|
self.parser.error(
|
|
f"Repository '{args.repo_id}' not found on the Hugging Face Hub."
|
|
)
|
|
except Exception as e:
|
|
self.parser.error(e)
|
|
|
|
print(f"Successfully downloaded model to {true_output_dir}")
|
|
|
|
def _meta_download(self, model: Model, meta_url: str):
|
|
output_dir = Path(DEFAULT_CHECKPOINT_DIR) / model.descriptor()
|
|
os.makedirs(output_dir, exist_ok=True)
|
|
|
|
info = llama_meta_net_info(model)
|
|
|
|
# I believe we can use some concurrency here if needed but not sure it is worth it
|
|
for f in info.files:
|
|
output_file = str(output_dir / f)
|
|
url = meta_url.replace("*", f"{info.folder}/{f}")
|
|
total_size = info.pth_size if "consolidated" in f else 0
|
|
cprint(f"Downloading `{f}`...", "white")
|
|
downloader = ResumableDownloader(url, output_file, total_size)
|
|
asyncio.run(downloader.download())
|
|
|
|
def _run_download_cmd(self, args: argparse.Namespace):
|
|
model = resolve_model(args.model_id)
|
|
if model is None:
|
|
self.parser.error(f"Model {args.model_id} not found")
|
|
return
|
|
|
|
if args.source == "huggingface":
|
|
self._hf_download(model, args.hf_token, args.ignore_patterns)
|
|
else:
|
|
meta_url = args.meta_url
|
|
if not meta_url:
|
|
meta_url = input(
|
|
"Please provide the signed URL you received via email (e.g., https://llama3-1.llamameta.net/*?Policy...): "
|
|
)
|
|
assert meta_url is not None and "llama3-1.llamameta.net" in meta_url
|
|
self._meta_download(model, meta_url)
|
|
|
|
|
|
class ResumableDownloader:
|
|
def __init__(
|
|
self,
|
|
url: str,
|
|
output_file: str,
|
|
total_size: int = 0,
|
|
buffer_size: int = 32 * 1024,
|
|
):
|
|
self.url = url
|
|
self.output_file = output_file
|
|
self.buffer_size = buffer_size
|
|
self.total_size = total_size
|
|
self.downloaded_size = 0
|
|
self.start_size = 0
|
|
self.start_time = 0
|
|
|
|
async def get_file_info(self, client: httpx.AsyncClient) -> None:
|
|
if self.total_size > 0:
|
|
return
|
|
|
|
# Force disable compression when trying to retrieve file size
|
|
response = await client.head(
|
|
self.url, follow_redirects=True, headers={"Accept-Encoding": "identity"}
|
|
)
|
|
response.raise_for_status()
|
|
self.url = str(response.url) # Update URL in case of redirects
|
|
self.total_size = int(response.headers.get("Content-Length", 0))
|
|
if self.total_size == 0:
|
|
raise ValueError(
|
|
"Unable to determine file size. The server might not support range requests."
|
|
)
|
|
|
|
async def download(self) -> None:
|
|
self.start_time = time.time()
|
|
async with httpx.AsyncClient() as client:
|
|
await self.get_file_info(client)
|
|
|
|
if os.path.exists(self.output_file):
|
|
self.downloaded_size = os.path.getsize(self.output_file)
|
|
self.start_size = self.downloaded_size
|
|
if self.downloaded_size >= self.total_size:
|
|
print(f"Already downloaded `{self.output_file}`, skipping...")
|
|
return
|
|
|
|
additional_size = self.total_size - self.downloaded_size
|
|
if not self.has_disk_space(additional_size):
|
|
print(
|
|
f"Not enough disk space to download `{self.output_file}`. "
|
|
f"Required: {(additional_size / M):.2f} MB"
|
|
)
|
|
raise ValueError(
|
|
f"Not enough disk space to download `{self.output_file}`"
|
|
)
|
|
|
|
while True:
|
|
if self.downloaded_size >= self.total_size:
|
|
break
|
|
|
|
# Cloudfront has a max-size limit
|
|
max_chunk_size = 27_000_000_000
|
|
request_size = min(
|
|
self.total_size - self.downloaded_size, max_chunk_size
|
|
)
|
|
headers = {
|
|
"Range": f"bytes={self.downloaded_size}-{self.downloaded_size + request_size}"
|
|
}
|
|
# print(f"Downloading `{self.output_file}`....{headers}")
|
|
try:
|
|
async with client.stream(
|
|
"GET", self.url, headers=headers
|
|
) as response:
|
|
response.raise_for_status()
|
|
with open(self.output_file, "ab") as file:
|
|
async for chunk in response.aiter_bytes(self.buffer_size):
|
|
file.write(chunk)
|
|
self.downloaded_size += len(chunk)
|
|
self.print_progress()
|
|
except httpx.HTTPError as e:
|
|
print(f"\nDownload interrupted: {e}")
|
|
print("You can resume the download by running the script again.")
|
|
except Exception as e:
|
|
print(f"\nAn error occurred: {e}")
|
|
|
|
print(f"\nFinished downloading `{self.output_file}`....")
|
|
|
|
def print_progress(self) -> None:
|
|
percent = (self.downloaded_size / self.total_size) * 100
|
|
bar_length = 50
|
|
filled_length = int(bar_length * self.downloaded_size // self.total_size)
|
|
bar = "█" * filled_length + "-" * (bar_length - filled_length)
|
|
|
|
elapsed_time = time.time() - self.start_time
|
|
M = 1024 * 1024 # noqa
|
|
|
|
speed = (
|
|
(self.downloaded_size - self.start_size) / (elapsed_time * M)
|
|
if elapsed_time > 0
|
|
else 0
|
|
)
|
|
print(
|
|
f"\rProgress: |{bar}| {percent:.2f}% "
|
|
f"({self.downloaded_size // M}/{self.total_size // M} MB) "
|
|
f"Speed: {speed:.2f} MiB/s",
|
|
end="",
|
|
flush=True,
|
|
)
|
|
|
|
def has_disk_space(self, file_size: int) -> bool:
|
|
dir_path = os.path.dirname(os.path.abspath(self.output_file))
|
|
free_space = shutil.disk_usage(dir_path).free
|
|
return free_space > file_size
|