109 lines
2.9 KiB
Python
109 lines
2.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import json
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import struct
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from functools import cache
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from os import PathLike
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from pathlib import Path
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from typing import Any, Optional, Union
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from vllm.envs import VLLM_MODEL_REDIRECT_PATH
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from vllm.logger import init_logger
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logger = init_logger(__name__)
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def is_s3(model_or_path: str) -> bool:
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return model_or_path.lower().startswith('s3://')
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def check_gguf_file(model: Union[str, PathLike]) -> bool:
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"""Check if the file is a GGUF model."""
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model = Path(model)
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if not model.is_file():
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return False
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elif model.suffix == ".gguf":
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return True
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try:
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with model.open("rb") as f:
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header = f.read(4)
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return header == b"GGUF"
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except Exception as e:
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logger.debug("Error reading file %s: %s", model, e)
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return False
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def modelscope_list_repo_files(
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repo_id: str,
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revision: Optional[str] = None,
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token: Union[str, bool, None] = None,
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) -> list[str]:
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"""List files in a modelscope repo."""
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from modelscope.hub.api import HubApi
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api = HubApi()
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api.login(token)
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# same as huggingface_hub.list_repo_files
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files = [
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file['Path'] for file in api.get_model_files(
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model_id=repo_id, revision=revision, recursive=True)
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if file['Type'] == 'blob'
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]
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return files
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def _maybe_json_dict(path: Union[str, PathLike]) -> dict[str, str]:
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with open(path) as f:
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try:
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return json.loads(f.read())
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except Exception:
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return dict[str, str]()
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def _maybe_space_split_dict(path: Union[str, PathLike]) -> dict[str, str]:
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parsed_dict = dict[str, str]()
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with open(path) as f:
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for line in f.readlines():
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try:
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model_name, redirect_name = line.strip().split()
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parsed_dict[model_name] = redirect_name
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except Exception:
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pass
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return parsed_dict
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@cache
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def maybe_model_redirect(model: str) -> str:
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"""
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Use model_redirect to redirect the model name to a local folder.
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:param model: hf model name
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:return: maybe redirect to a local folder
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"""
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model_redirect_path = VLLM_MODEL_REDIRECT_PATH
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if not model_redirect_path:
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return model
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if not Path(model_redirect_path).exists():
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return model
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redirect_dict = (_maybe_json_dict(model_redirect_path)
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or _maybe_space_split_dict(model_redirect_path))
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if (redirect_model := redirect_dict.get(model)):
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logger.info("model redirect: [ %s ] -> [ %s ]", model, redirect_model)
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return redirect_model
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return model
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def parse_safetensors_file_metadata(
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path: Union[str, PathLike]) -> dict[str, Any]:
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with open(path, "rb") as f:
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length_of_metadata = struct.unpack('<Q', f.read(8))[0]
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metadata = json.loads(f.read(length_of_metadata).decode('utf-8'))
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return metadata
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