Mirrors/modelscope
1
0
Fork 0
mirror of https://github.com/modelscope/modelscope.git synced 2025-12-16 08:17:45 +01:00
Code Issues Packages Projects Releases Wiki Activity
Files
2fc6d8e82229e6bd4af9cefc362a0cad95c43227
modelscope/modelscope/hub/api.py
Gongsheng Li 2fc6d8e822 Feat/support repo info (#1483)
2025-08-29 17:23:46 +08:00

2996 lines
124 KiB
Python
Raw Blame History

# Copyright (c) Alibaba, Inc. and its affiliates.
# yapf: disable
import datetime
import fnmatch
import functools
import io
import os
import pickle
import platform
import re
import shutil
import tempfile
import time
import uuid
import warnings
from collections import defaultdict
from http import HTTPStatus
from http.cookiejar import CookieJar
from os.path import expanduser
from pathlib import Path
from typing import Any, BinaryIO, Dict, Iterable, List, Optional, Tuple, Union
from urllib.parse import urlencode
import json
import requests
from requests import Session
from requests.adapters import HTTPAdapter, Retry
from requests.exceptions import HTTPError
from tqdm.auto import tqdm
from modelscope.hub.constants import (API_HTTP_CLIENT_MAX_RETRIES,
API_HTTP_CLIENT_TIMEOUT,
API_RESPONSE_FIELD_DATA,
API_RESPONSE_FIELD_EMAIL,
API_RESPONSE_FIELD_GIT_ACCESS_TOKEN,
API_RESPONSE_FIELD_MESSAGE,
API_RESPONSE_FIELD_USERNAME,
DEFAULT_MAX_WORKERS,
MODELSCOPE_CLOUD_ENVIRONMENT,
MODELSCOPE_CLOUD_USERNAME,
MODELSCOPE_CREDENTIALS_PATH,
MODELSCOPE_DOMAIN,
MODELSCOPE_PREFER_AI_SITE,
MODELSCOPE_REQUEST_ID,
MODELSCOPE_URL_SCHEME, ONE_YEAR_SECONDS,
REQUESTS_API_HTTP_METHOD,
TEMPORARY_FOLDER_NAME,
UPLOAD_BLOB_TQDM_DISABLE_THRESHOLD,
UPLOAD_COMMIT_BATCH_SIZE,
UPLOAD_MAX_FILE_COUNT,
UPLOAD_MAX_FILE_COUNT_IN_DIR,
UPLOAD_MAX_FILE_SIZE,
UPLOAD_NORMAL_FILE_SIZE_TOTAL_LIMIT,
UPLOAD_SIZE_THRESHOLD_TO_ENFORCE_LFS,
DatasetVisibility, Licenses,
ModelVisibility, Visibility,
VisibilityMap)
from modelscope.hub.errors import (InvalidParameter, NotExistError,
NotLoginException, RequestError,
datahub_raise_on_error,
handle_http_post_error,
handle_http_response, is_ok,
raise_for_http_status, raise_on_error)
from modelscope.hub.git import GitCommandWrapper
from modelscope.hub.info import DatasetInfo, ModelInfo
from modelscope.hub.repository import Repository
from modelscope.hub.utils.aigc import AigcModel
from modelscope.hub.utils.utils import (add_content_to_file, get_domain,
get_endpoint, get_readable_folder_size,
get_release_datetime, is_env_true,
model_id_to_group_owner_name)
from modelscope.utils.constant import (DEFAULT_DATASET_REVISION,
DEFAULT_MODEL_REVISION,
DEFAULT_REPOSITORY_REVISION,
MASTER_MODEL_BRANCH, META_FILES_FORMAT,
REPO_TYPE_DATASET, REPO_TYPE_MODEL,
REPO_TYPE_SUPPORT, ConfigFields,
DatasetFormations, DatasetMetaFormats,
DownloadChannel, DownloadMode,
Frameworks, ModelFile, Tasks,
VirgoDatasetConfig)
from modelscope.utils.file_utils import get_file_hash, get_file_size
from modelscope.utils.logger import get_logger
from modelscope.utils.repo_utils import (DATASET_LFS_SUFFIX,
DEFAULT_IGNORE_PATTERNS,
MODEL_LFS_SUFFIX,
CommitHistoryResponse, CommitInfo,
CommitOperation, CommitOperationAdd,
RepoUtils)
from modelscope.utils.thread_utils import thread_executor
logger = get_logger()
class HubApi:
"""Model hub api interface.
"""
def __init__(self,
endpoint: Optional[str] = None,
timeout=API_HTTP_CLIENT_TIMEOUT,
max_retries=API_HTTP_CLIENT_MAX_RETRIES):
"""The ModelScope HubApi。
Args:
endpoint (str, optional): The modelscope server http|https address. Defaults to None.
"""
self.endpoint = endpoint if endpoint is not None else get_endpoint()
self.headers = {'user-agent': ModelScopeConfig.get_user_agent()}
self.session = Session()
retry = Retry(
total=max_retries,
read=2,
connect=2,
backoff_factor=1,
status_forcelist=(500, 502, 503, 504),
respect_retry_after_header=False,
)
adapter = HTTPAdapter(max_retries=retry)
self.session.mount('http://', adapter)
self.session.mount('https://', adapter)
# set http timeout
for method in REQUESTS_API_HTTP_METHOD:
setattr(
self.session, method,
functools.partial(
getattr(self.session, method),
timeout=timeout))
self.upload_checker = UploadingCheck()
@staticmethod
def _get_cookies(access_token: str):
"""
Get jar cookies for authentication from access_token.
Args:
access_token (str): user access token on ModelScope.
Returns:
jar (CookieJar): cookies for authentication.
"""
from requests.cookies import RequestsCookieJar
jar = RequestsCookieJar()
jar.set('m_session_id',
access_token,
domain=get_domain(),
path='/')
return jar
def get_cookies(self, access_token, cookies_required: Optional[bool] = False):
"""
Get cookies for authentication from local cache or access_token.
Args:
access_token (str): user access token on ModelScope
cookies_required (bool): whether to raise error if no cookies found, defaults to `False`.
Returns:
cookies (CookieJar): cookies for authentication.
Raises:
ValueError: If no credentials found and cookies_required is True.
"""
if access_token:
cookies = self._get_cookies(access_token=access_token)
else:
cookies = ModelScopeConfig.get_cookies()
if cookies is None and cookies_required:
raise ValueError(
'No credentials found.'
'You can pass the `--token` argument, '
'or use HubApi().login(access_token=`your_sdk_token`). '
'Your token is available at https://modelscope.cn/my/myaccesstoken'
)
return cookies
def login(
self,
access_token: Optional[str] = None,
endpoint: Optional[str] = None
):
"""Login with your SDK access token, which can be obtained from
https://www.modelscope.cn user center.
Args:
access_token (str): user access token on modelscope, set this argument or set `MODELSCOPE_API_TOKEN`.
If neither of the tokens exist, login will directly return.
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Returns:
cookies: to authenticate yourself to ModelScope open-api
git_token: token to access your git repository.
Note:
You only have to login once within 30 days.
"""
if access_token is None:
access_token = os.environ.get('MODELSCOPE_API_TOKEN')
if not access_token:
return None, None
if not endpoint:
endpoint = self.endpoint
path = f'{endpoint}/api/v1/login'
r = self.session.post(
path,
json={'AccessToken': access_token},
headers=self.builder_headers(self.headers))
raise_for_http_status(r)
d = r.json()
raise_on_error(d)
token = d[API_RESPONSE_FIELD_DATA][API_RESPONSE_FIELD_GIT_ACCESS_TOKEN]
cookies = r.cookies
# save token and cookie
ModelScopeConfig.save_token(token)
ModelScopeConfig.save_cookies(cookies)
ModelScopeConfig.save_user_info(
d[API_RESPONSE_FIELD_DATA][API_RESPONSE_FIELD_USERNAME],
d[API_RESPONSE_FIELD_DATA][API_RESPONSE_FIELD_EMAIL])
return d[API_RESPONSE_FIELD_DATA][
API_RESPONSE_FIELD_GIT_ACCESS_TOKEN], cookies
def create_model(self,
model_id: str,
visibility: Optional[int] = ModelVisibility.PUBLIC,
license: Optional[str] = Licenses.APACHE_V2,
chinese_name: Optional[str] = None,
original_model_id: Optional[str] = '',
endpoint: Optional[str] = None,
token: Optional[str] = None,
aigc_model: Optional['AigcModel'] = None) -> str:
"""Create model repo at ModelScope Hub.
Args:
model_id (str): The model id in format {owner}/{name}
visibility (int, optional): visibility of the model(1-private, 5-public), default 5.
license (str, optional): license of the model, default apache-2.0.
chinese_name (str, optional): chinese name of the model.
original_model_id (str, optional): the base model id which this model is trained from
endpoint: the endpoint to use, default to None to use endpoint specified in the class
token (str, optional): access token for authentication
aigc_model (AigcModel, optional): AigcModel instance for AIGC model creation.
If provided, will create an AIGC model with automatic file upload.
Refer to modelscope.hub.utils.aigc.AigcModel for details.
Returns:
str: URL of the created model repository
Raises:
InvalidParameter: If model_id is invalid or required AIGC parameters are missing.
ValueError: If not login.
Note:
model_id = {owner}/{name}
"""
if model_id is None:
raise InvalidParameter('model_id is required!')
# Get cookies for authentication.
cookies = self.get_cookies(access_token=token, cookies_required=True)
if not endpoint:
endpoint = self.endpoint
owner_or_group, name = model_id_to_group_owner_name(model_id)
# Base body configuration
body = {
'Path': owner_or_group,
'Name': name,
'ChineseName': chinese_name,
'Visibility': visibility,
'License': license,
'OriginalModelId': original_model_id,
'TrainId': os.environ.get('MODELSCOPE_TRAIN_ID', '')
}
# Set path based on model type
if aigc_model is not None:
# Use AIGC model endpoint
path = f'{endpoint}/api/v1/models/aigc'
# Best-effort pre-upload weights so server recognizes sha256 (use existing cookies)
aigc_model.preupload_weights(cookies=cookies, headers=self.builder_headers(self.headers))
# Add AIGC-specific fields to body
body.update({
'TagShowName': aigc_model.revision,
'CoverImages': aigc_model.cover_images,
'AigcType': aigc_model.aigc_type,
'TagDescription': aigc_model.description,
'VisionFoundation': aigc_model.base_model_type,
'BaseModel': aigc_model.base_model_id or original_model_id,
'WeightsName': aigc_model.weight_filename,
'WeightsSha256': aigc_model.weight_sha256,
'WeightsSize': aigc_model.weight_size,
'ModelPath': aigc_model.model_path
})
else:
# Use regular model endpoint
path = f'{endpoint}/api/v1/models'
r = self.session.post(
path,
json=body,
cookies=cookies,
headers=self.builder_headers(self.headers))
handle_http_post_error(r, path, body)
raise_on_error(r.json())
model_repo_url = f'{endpoint}/models/{model_id}'
# TODO: to be aligned with the new api
# Upload model files for AIGC models
# if aigc_model is not None:
# aigc_model.upload_to_repo(self, model_id, token)
return model_repo_url
def delete_model(self, model_id: str, endpoint: Optional[str] = None):
"""Delete model_id from ModelScope.
Args:
model_id (str): The model id.
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Raises:
ValueError: If not login.
Note:
model_id = {owner}/{name}
"""
cookies = ModelScopeConfig.get_cookies()
if not endpoint:
endpoint = self.endpoint
if cookies is None:
raise ValueError('Token does not exist, please login first.')
path = f'{endpoint}/api/v1/models/{model_id}'
r = self.session.delete(path,
cookies=cookies,
headers=self.builder_headers(self.headers))
raise_for_http_status(r)
raise_on_error(r.json())
def get_model_url(self, model_id: str, endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
return f'{endpoint}/api/v1/models/{model_id}.git'
def get_model(
self,
model_id: str,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
endpoint: Optional[str] = None
) -> str:
"""Get model information at ModelScope
Args:
model_id (str): The model id.
revision (str optional): revision of model.
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Returns:
The model detail information.
Raises:
NotExistError: If the model is not exist, will throw NotExistError
Note:
model_id = {owner}/{name}
"""
cookies = ModelScopeConfig.get_cookies()
owner_or_group, name = model_id_to_group_owner_name(model_id)
if not endpoint:
endpoint = self.endpoint
if revision:
path = f'{endpoint}/api/v1/models/{owner_or_group}/{name}?Revision={revision}'
else:
path = f'{endpoint}/api/v1/models/{owner_or_group}/{name}'
r = self.session.get(path, cookies=cookies,
headers=self.builder_headers(self.headers))
handle_http_response(r, logger, cookies, model_id)
if r.status_code == HTTPStatus.OK:
if is_ok(r.json()):
return r.json()[API_RESPONSE_FIELD_DATA]
else:
raise NotExistError(r.json()[API_RESPONSE_FIELD_MESSAGE])
else:
raise_for_http_status(r)
def get_endpoint_for_read(self,
repo_id: str,
*,
repo_type: Optional[str] = None) -> str:
"""Get proper endpoint for read operation (such as download, list etc.)
1. If user has set MODELSCOPE_DOMAIN, construct endpoint with user-specified domain.
If the repo does not exist on that endpoint, throw 404 error, otherwise return the endpoint.
2. If domain is not set, check existence of repo in cn-site and ai-site (intl version) respectively.
Checking order is determined by MODELSCOPE_PREFER_AI_SITE.
a. if MODELSCOPE_PREFER_AI_SITE is not set ,check cn-site first before ai-site (intl version)
b. otherwise check ai-site before cn-site
return the endpoint with which the given repo_id exists.
if neither exists, throw 404 error
"""
s = os.environ.get(MODELSCOPE_DOMAIN)
if s is not None and s.strip() != '':
endpoint = MODELSCOPE_URL_SCHEME + s
try:
self.repo_exists(repo_id=repo_id, repo_type=repo_type, endpoint=endpoint, re_raise=True)
except Exception:
logger.error(f'Repo {repo_id} does not exist on {endpoint}.')
raise
return endpoint
check_cn_first = not is_env_true(MODELSCOPE_PREFER_AI_SITE)
prefer_endpoint = get_endpoint(cn_site=check_cn_first)
if not self.repo_exists(
repo_id, repo_type=repo_type, endpoint=prefer_endpoint):
alternative_endpoint = get_endpoint(cn_site=(not check_cn_first))
logger.warning(f'Repo {repo_id} not exists on {prefer_endpoint}, '
f'will try on alternative endpoint {alternative_endpoint}.')
try:
self.repo_exists(
repo_id, repo_type=repo_type, endpoint=alternative_endpoint, re_raise=True)
except Exception:
logger.error(f'Repo {repo_id} not exists on either {prefer_endpoint} or {alternative_endpoint}')
raise
else:
return alternative_endpoint
else:
return prefer_endpoint
def model_info(self,
repo_id: str,
*,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
endpoint: Optional[str] = None) -> ModelInfo:
"""Get model information including commit history.
Args:
repo_id (str): The model id in the format of
``namespace/model_name``.
revision (str, optional): Specific revision of the model.
Defaults to ``DEFAULT_MODEL_REVISION``.
endpoint (str, optional): Hub endpoint to use. When ``None``,
use the endpoint specified when initializing :class:`HubApi`.
Returns:
ModelInfo: The model detailed information returned by
ModelScope Hub with commit history.
"""
owner_or_group, _ = model_id_to_group_owner_name(repo_id)
model_data = self.get_model(
model_id=repo_id, revision=revision, endpoint=endpoint)
commits = self.list_repo_commits(
repo_id=repo_id, repo_type=REPO_TYPE_MODEL, revision=revision, endpoint=endpoint)
# Create ModelInfo from API response data
model_info = ModelInfo(**model_data, commits=commits, author=owner_or_group)
return model_info
def dataset_info(self,
repo_id: str,
*,
revision: Optional[str] = None,
endpoint: Optional[str] = None) -> DatasetInfo:
"""Get dataset information including commit history.
Args:
repo_id (str): The dataset id in the format of
``namespace/dataset_name``.
revision (str, optional): Specific revision of the dataset.
Defaults to ``None``.
endpoint (str, optional): Hub endpoint to use. When ``None``,
use the endpoint specified when initializing :class:`HubApi`.
Returns:
DatasetInfo: The dataset detailed information returned by
ModelScope Hub with commit history.
"""
owner_or_group, _ = model_id_to_group_owner_name(repo_id)
dataset_data = self.get_dataset(
dataset_id=repo_id, revision=revision, endpoint=endpoint)
commits = self.list_repo_commits(
repo_id=repo_id, repo_type=REPO_TYPE_DATASET, revision=revision, endpoint=endpoint)
# Create DatasetInfo from API response data
dataset_info = DatasetInfo(**dataset_data, commits=commits, author=owner_or_group)
return dataset_info
def repo_info(
self,
repo_id: str,
*,
repo_type: Optional[str] = REPO_TYPE_MODEL,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
endpoint: Optional[str] = None
) -> Union[ModelInfo, DatasetInfo]:
"""Get repository information for models or datasets.
Args:
repo_id (str): The repository id in the format of
``namespace/repo_name``.
revision (str, optional): Specific revision of the repository.
Currently only effective for model repositories. Defaults to
``DEFAULT_MODEL_REVISION``.
repo_type (str, optional): Type of the repository. Supported
values are ``"model"`` and ``"dataset"``. If not provided,
``"model"`` is assumed.
endpoint (str, optional): Hub endpoint to use. When ``None``,
use the endpoint specified when initializing :class:`HubApi`.
Returns:
Union[ModelInfo, DatasetInfo]: The repository detailed information
returned by ModelScope Hub.
"""
if repo_type is None or repo_type == REPO_TYPE_MODEL:
return self.model_info(repo_id=repo_id, revision=revision, endpoint=endpoint)
if repo_type == REPO_TYPE_DATASET:
return self.dataset_info(repo_id=repo_id, revision=revision, endpoint=endpoint)
raise InvalidParameter(
f'Arg repo_type {repo_type} not supported. Please choose from {REPO_TYPE_SUPPORT}.')
def repo_exists(
self,
repo_id: str,
*,
repo_type: Optional[str] = None,
endpoint: Optional[str] = None,
re_raise: Optional[bool] = False,
token: Optional[str] = None
) -> bool:
"""
Checks if a repository exists on ModelScope
Args:
repo_id (`str`):
A namespace (user or an organization) and a repo name separated
by a `/`.
repo_type (`str`, *optional*):
`None` or `"model"` if getting repository info from a model. Default is `None`.
TODO: support studio
endpoint(`str`):
None or specific endpoint to use, when None, use the default endpoint
set in HubApi class (self.endpoint)
re_raise(`bool`):
raise exception when error
token (`str`, *optional*): access token to use for checking existence.
Returns:
True if the repository exists, False otherwise.
"""
if endpoint is None:
endpoint = self.endpoint
if (repo_type is not None) and repo_type.lower() not in REPO_TYPE_SUPPORT:
raise Exception('Not support repo-type: %s' % repo_type)
if (repo_id is None) or repo_id.count('/') != 1:
raise Exception('Invalid repo_id: %s, must be of format namespace/name' % repo_type)
cookies = self.get_cookies(access_token=token, cookies_required=False)
owner_or_group, name = model_id_to_group_owner_name(repo_id)
if (repo_type is not None) and repo_type.lower() == REPO_TYPE_DATASET:
path = f'{endpoint}/api/v1/datasets/{owner_or_group}/{name}'
else:
path = f'{endpoint}/api/v1/models/{owner_or_group}/{name}'
r = self.session.get(path, cookies=cookies,
headers=self.builder_headers(self.headers))
code = handle_http_response(r, logger, cookies, repo_id, False)
if code == 200:
return True
elif code == 404:
if re_raise:
raise HTTPError(r)
else:
return False
else:
logger.warn(f'Check repo_exists return status code {code}.')
raise Exception(
'Failed to check existence of repo: %s, make sure you have access authorization.'
% repo_type)
def delete_repo(self, repo_id: str, repo_type: str, endpoint: Optional[str] = None):
"""
Delete a repository from ModelScope.
Args:
repo_id (`str`):
A namespace (user or an organization) and a repo name separated
by a `/`.
repo_type (`str`):
The type of the repository. Supported types are `model` and `dataset`.
endpoint(`str`):
The endpoint to use. If not provided, the default endpoint is `https://www.modelscope.cn`
Could be set to `https://ai.modelscope.ai` for international version.
"""
if not endpoint:
endpoint = self.endpoint
if repo_type == REPO_TYPE_DATASET:
self.delete_dataset(repo_id, endpoint)
elif repo_type == REPO_TYPE_MODEL:
self.delete_model(repo_id, endpoint)
else:
raise Exception(f'Arg repo_type {repo_type} not supported.')
logger.info(f'Repo {repo_id} deleted successfully.')
@staticmethod
def _create_default_config(model_dir):
cfg_file = os.path.join(model_dir, ModelFile.CONFIGURATION)
cfg = {
ConfigFields.framework: Frameworks.torch,
ConfigFields.task: Tasks.other,
}
with open(cfg_file, 'w') as file:
json.dump(cfg, file)
def push_model(self,
model_id: str,
model_dir: str,
visibility: Optional[int] = ModelVisibility.PUBLIC,
license: Optional[str] = Licenses.APACHE_V2,
chinese_name: Optional[str] = None,
commit_message: Optional[str] = 'upload model',
tag: Optional[str] = None,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION,
original_model_id: Optional[str] = None,
ignore_file_pattern: Optional[Union[List[str], str]] = None,
lfs_suffix: Optional[Union[str, List[str]]] = None):
warnings.warn(
'This function is deprecated and will be removed in future versions. '
'Please use git command directly or use HubApi().upload_folder instead',
DeprecationWarning,
stacklevel=2
)
"""Upload model from a given directory to given repository. A valid model directory
must contain a configuration.json file.
This function upload the files in given directory to given repository. If the
given repository is not exists in remote, it will automatically create it with
given visibility, license and chinese_name parameters. If the revision is also
not exists in remote repository, it will create a new branch for it.
This function must be called before calling HubApi's login with a valid token
which can be obtained from ModelScope's website.
If any error, please upload via git commands.
Args:
model_id (str):
The model id to be uploaded, caller must have write permission for it.
model_dir(str):
The Absolute Path of the finetune result.
visibility(int, optional):
Visibility of the new created model(1-private, 5-public). If the model is
not exists in ModelScope, this function will create a new model with this
visibility and this parameter is required. You can ignore this parameter
if you make sure the model's existence.
license(`str`, defaults to `None`):
License of the new created model(see License). If the model is not exists
in ModelScope, this function will create a new model with this license
and this parameter is required. You can ignore this parameter if you
make sure the model's existence.
chinese_name(`str`, *optional*, defaults to `None`):
chinese name of the new created model.
commit_message(`str`, *optional*, defaults to `None`):
commit message of the push request.
tag(`str`, *optional*, defaults to `None`):
The tag on this commit
revision (`str`, *optional*, default to DEFAULT_MODEL_REVISION):
which branch to push. If the branch is not exists, It will create a new
branch and push to it.
original_model_id (str, optional): The base model id which this model is trained from
ignore_file_pattern (`Union[List[str], str]`, optional): The file pattern to ignore uploading
lfs_suffix (`List[str]`, optional): File types to use LFS to manage. examples: '*.safetensors'.
Raises:
InvalidParameter: Parameter invalid.
NotLoginException: Not login
ValueError: No configuration.json
Exception: Create failed.
"""
if model_id is None:
raise InvalidParameter('model_id cannot be empty!')
if model_dir is None:
raise InvalidParameter('model_dir cannot be empty!')
if not os.path.exists(model_dir) or os.path.isfile(model_dir):
raise InvalidParameter('model_dir must be a valid directory.')
cfg_file = os.path.join(model_dir, ModelFile.CONFIGURATION)
if not os.path.exists(cfg_file):
logger.warning(
f'No {ModelFile.CONFIGURATION} file found in {model_dir}, creating a default one.')
HubApi._create_default_config(model_dir)
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise NotLoginException('Must login before upload!')
files_to_save = os.listdir(model_dir)
folder_size = get_readable_folder_size(model_dir)
if ignore_file_pattern is None:
ignore_file_pattern = []
if isinstance(ignore_file_pattern, str):
ignore_file_pattern = [ignore_file_pattern]
if visibility is None or license is None:
raise InvalidParameter('Visibility and License cannot be empty for new model.')
if not self.repo_exists(model_id):
logger.info('Creating new model [%s]' % model_id)
self.create_model(
model_id=model_id,
visibility=visibility,
license=license,
chinese_name=chinese_name,
original_model_id=original_model_id)
tmp_dir = os.path.join(model_dir, TEMPORARY_FOLDER_NAME) # make temporary folder
git_wrapper = GitCommandWrapper()
logger.info(f'Pushing folder {model_dir} as model {model_id}.')
logger.info(f'Total folder size {folder_size}, this may take a while depending on actual pushing size...')
try:
repo = Repository(model_dir=tmp_dir, clone_from=model_id)
branches = git_wrapper.get_remote_branches(tmp_dir)
if revision not in branches:
logger.info('Creating new branch %s' % revision)
git_wrapper.new_branch(tmp_dir, revision)
git_wrapper.checkout(tmp_dir, revision)
files_in_repo = os.listdir(tmp_dir)
for f in files_in_repo:
if f[0] != '.':
src = os.path.join(tmp_dir, f)
if os.path.isfile(src):
os.remove(src)
else:
shutil.rmtree(src, ignore_errors=True)
for f in files_to_save:
if f[0] != '.':
if any([re.search(pattern, f) is not None for pattern in ignore_file_pattern]):
continue
src = os.path.join(model_dir, f)
if os.path.isdir(src):
shutil.copytree(src, os.path.join(tmp_dir, f))
else:
shutil.copy(src, tmp_dir)
if not commit_message:
date = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S')
commit_message = '[automsg] push model %s to hub at %s' % (
model_id, date)
if lfs_suffix is not None:
lfs_suffix_list = [lfs_suffix] if isinstance(lfs_suffix, str) else lfs_suffix
for suffix in lfs_suffix_list:
repo.add_lfs_type(suffix)
repo.push(
commit_message=commit_message,
local_branch=revision,
remote_branch=revision)
if tag is not None:
repo.tag_and_push(tag, tag)
logger.info(f'Successfully push folder {model_dir} to remote repo [{model_id}].')
except Exception:
raise
finally:
shutil.rmtree(tmp_dir, ignore_errors=True)
def list_models(self,
owner_or_group: str,
page_number: Optional[int] = 1,
page_size: Optional[int] = 10,
endpoint: Optional[str] = None) -> dict:
"""List models in owner or group.
Args:
owner_or_group(str): owner or group.
page_number(int, optional): The page number, default: 1
page_size(int, optional): The page size, default: 10
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Raises:
RequestError: The request error.
Returns:
dict: {"models": "list of models", "TotalCount": total_number_of_models_in_owner_or_group}
"""
cookies = ModelScopeConfig.get_cookies()
if not endpoint:
endpoint = self.endpoint
path = f'{endpoint}/api/v1/models/'
r = self.session.put(
path,
data='{"Path":"%s", "PageNumber":%s, "PageSize": %s}' %
(owner_or_group, page_number, page_size),
cookies=cookies,
headers=self.builder_headers(self.headers))
handle_http_response(r, logger, cookies, owner_or_group)
if r.status_code == HTTPStatus.OK:
if is_ok(r.json()):
data = r.json()[API_RESPONSE_FIELD_DATA]
return data
else:
raise RequestError(r.json()[API_RESPONSE_FIELD_MESSAGE])
else:
raise_for_http_status(r)
return None
def _check_cookie(self, use_cookies: Union[bool, CookieJar] = False) -> CookieJar: # noqa
cookies = None
if isinstance(use_cookies, CookieJar):
cookies = use_cookies
elif use_cookies:
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise ValueError('Token does not exist, please login first.')
return cookies
def list_model_revisions(
self,
model_id: str,
cutoff_timestamp: Optional[int] = None,
use_cookies: Union[bool, CookieJar] = False) -> List[str]:
"""Get model branch and tags.
Args:
model_id (str): The model id
cutoff_timestamp (int): Tags created before the cutoff will be included.
The timestamp is represented by the seconds elapsed from the epoch time.
use_cookies (Union[bool, CookieJar], optional): If is cookieJar, we will use this cookie, if True,
will load cookie from local. Defaults to False.
Returns:
Tuple[List[str], List[str]]: Return list of branch name and tags
"""
tags_details = self.list_model_revisions_detail(model_id=model_id,
cutoff_timestamp=cutoff_timestamp,
use_cookies=use_cookies)
tags = [x['Revision'] for x in tags_details
] if tags_details else []
return tags
def list_model_revisions_detail(
self,
model_id: str,
cutoff_timestamp: Optional[int] = None,
use_cookies: Union[bool, CookieJar] = False,
endpoint: Optional[str] = None) -> List[str]:
"""Get model branch and tags.
Args:
model_id (str): The model id
cutoff_timestamp (int): Tags created before the cutoff will be included.
The timestamp is represented by the seconds elapsed from the epoch time.
use_cookies (Union[bool, CookieJar], optional): If is cookieJar, we will use this cookie, if True,
will load cookie from local. Defaults to False.
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Returns:
Tuple[List[str], List[str]]: Return list of branch name and tags
"""
cookies = self._check_cookie(use_cookies)
if cutoff_timestamp is None:
cutoff_timestamp = get_release_datetime()
if not endpoint:
endpoint = self.endpoint
path = f'{endpoint}/api/v1/models/{model_id}/revisions?EndTime=%s' % cutoff_timestamp
r = self.session.get(path, cookies=cookies,
headers=self.builder_headers(self.headers))
handle_http_response(r, logger, cookies, model_id)
d = r.json()
raise_on_error(d)
info = d[API_RESPONSE_FIELD_DATA]
# tags returned from backend are guaranteed to be ordered by create-time
return info['RevisionMap']['Tags']
def get_branch_tag_detail(self, details, name):
for item in details:
if item['Revision'] == name:
return item
return None
def get_valid_revision_detail(self,
model_id: str,
revision=None,
cookies: Optional[CookieJar] = None,
endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
release_timestamp = get_release_datetime()
current_timestamp = int(round(datetime.datetime.now().timestamp()))
# for active development in library codes (non-release-branches), release_timestamp
# is set to be a far-away-time-in-the-future, to ensure that we shall
# get the master-HEAD version from model repo by default (when no revision is provided)
all_branches_detail, all_tags_detail = self.get_model_branches_and_tags_details(
model_id, use_cookies=False if cookies is None else cookies, endpoint=endpoint)
all_branches = [x['Revision'] for x in all_branches_detail] if all_branches_detail else []
all_tags = [x['Revision'] for x in all_tags_detail] if all_tags_detail else []
if release_timestamp > current_timestamp + ONE_YEAR_SECONDS:
if revision is None:
revision = MASTER_MODEL_BRANCH
logger.info(
'Model revision not specified, using default [%s] version.'
% revision)
if revision not in all_branches and revision not in all_tags:
raise NotExistError('The model: %s has no revision : %s .' % (model_id, revision))
revision_detail = self.get_branch_tag_detail(all_tags_detail, revision)
if revision_detail is None:
revision_detail = self.get_branch_tag_detail(all_branches_detail, revision)
logger.debug('Development mode use revision: %s' % revision)
else:
if revision is not None and revision in all_branches:
revision_detail = self.get_branch_tag_detail(all_branches_detail, revision)
return revision_detail
if len(all_tags_detail) == 0: # use no revision use master as default.
if revision is None or revision == MASTER_MODEL_BRANCH:
revision = MASTER_MODEL_BRANCH
else:
raise NotExistError('The model: %s has no revision: %s !' % (model_id, revision))
revision_detail = self.get_branch_tag_detail(all_branches_detail, revision)
else:
if revision is None: # user not specified revision, use latest revision before release time
revisions_detail = [x for x in
all_tags_detail if
x['CreatedAt'] <= release_timestamp] if all_tags_detail else [] # noqa E501
if len(revisions_detail) > 0:
revision = revisions_detail[0]['Revision'] # use latest revision before release time.
revision_detail = revisions_detail[0]
else:
revision = MASTER_MODEL_BRANCH
revision_detail = self.get_branch_tag_detail(all_branches_detail, revision)
vl = '[%s]' % ','.join(all_tags)
logger.warning('Model revision should be specified from revisions: %s' % (vl))
logger.warning('Model revision not specified, use revision: %s' % revision)
else:
# use user-specified revision
if revision not in all_tags:
if revision == MASTER_MODEL_BRANCH:
logger.warning('Using the master branch is fragile, please use it with caution!')
revision_detail = self.get_branch_tag_detail(all_branches_detail, revision)
else:
vl = '[%s]' % ','.join(all_tags)
raise NotExistError('The model: %s has no revision: %s valid are: %s!' %
(model_id, revision, vl))
else:
revision_detail = self.get_branch_tag_detail(all_tags_detail, revision)
logger.info('Use user-specified model revision: %s' % revision)
return revision_detail
def get_valid_revision(self,
model_id: str,
revision=None,
cookies: Optional[CookieJar] = None,
endpoint: Optional[str] = None):
return self.get_valid_revision_detail(model_id=model_id,
revision=revision,
cookies=cookies,
endpoint=endpoint)['Revision']
def get_model_branches_and_tags_details(
self,
model_id: str,
use_cookies: Union[bool, CookieJar] = False,
endpoint: Optional[str] = None
) -> Tuple[List[str], List[str]]:
"""Get model branch and tags.
Args:
model_id (str): The model id
use_cookies (Union[bool, CookieJar], optional): If is cookieJar, we will use this cookie, if True,
will load cookie from local. Defaults to False.
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Returns:
Tuple[List[str], List[str]]: Return list of branch name and tags
"""
cookies = self._check_cookie(use_cookies)
if not endpoint:
endpoint = self.endpoint
path = f'{endpoint}/api/v1/models/{model_id}/revisions'
r = self.session.get(path, cookies=cookies,
headers=self.builder_headers(self.headers))
handle_http_response(r, logger, cookies, model_id)
d = r.json()
raise_on_error(d)
info = d[API_RESPONSE_FIELD_DATA]
return info['RevisionMap']['Branches'], info['RevisionMap']['Tags']
def get_model_branches_and_tags(
self,
model_id: str,
use_cookies: Union[bool, CookieJar] = False,
) -> Tuple[List[str], List[str]]:
"""Get model branch and tags.
Args:
model_id (str): The model id
use_cookies (Union[bool, CookieJar], optional): If is cookieJar, we will use this cookie, if True,
will load cookie from local. Defaults to False.
Returns:
Tuple[List[str], List[str]]: Return list of branch name and tags
"""
branches_detail, tags_detail = self.get_model_branches_and_tags_details(model_id=model_id,
use_cookies=use_cookies)
branches = [x['Revision'] for x in branches_detail
] if branches_detail else []
tags = [x['Revision'] for x in tags_detail
] if tags_detail else []
return branches, tags
def get_model_files(self,
model_id: str,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
root: Optional[str] = None,
recursive: Optional[bool] = False,
use_cookies: Union[bool, CookieJar] = False,
headers: Optional[dict] = {},
endpoint: Optional[str] = None) -> List[dict]:
"""List the models files.
Args:
model_id (str): The model id
revision (Optional[str], optional): The branch or tag name.
root (Optional[str], optional): The root path. Defaults to None.
recursive (Optional[bool], optional): Is recursive list files. Defaults to False.
use_cookies (Union[bool, CookieJar], optional): If is cookieJar, we will use this cookie, if True,
will load cookie from local. Defaults to False.
headers: request headers
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Returns:
List[dict]: Model file list.
"""
if not endpoint:
endpoint = self.endpoint
if revision:
path = '%s/api/v1/models/%s/repo/files?Revision=%s&Recursive=%s' % (
endpoint, model_id, revision, recursive)
else:
path = '%s/api/v1/models/%s/repo/files?Recursive=%s' % (
endpoint, model_id, recursive)
cookies = self._check_cookie(use_cookies)
if root is not None:
path = path + f'&Root={root}'
headers = self.headers if headers is None else headers
headers['X-Request-ID'] = str(uuid.uuid4().hex)
r = self.session.get(
path, cookies=cookies, headers=headers)
handle_http_response(r, logger, cookies, model_id)
d = r.json()
raise_on_error(d)
files = []
if not d[API_RESPONSE_FIELD_DATA]['Files']:
logger.warning(f'No files found in model {model_id} at revision {revision}.')
return files
for file in d[API_RESPONSE_FIELD_DATA]['Files']:
if file['Name'] == '.gitignore' or file['Name'] == '.gitattributes':
continue
files.append(file)
return files
def file_exists(
self,
repo_id: str,
filename: str,
*,
revision: Optional[str] = None,
):
"""Get if the specified file exists
Args:
repo_id (`str`): The repo id to use
filename (`str`): The queried filename, if the file exists in a sub folder,
please pass <sub-folder-name>/<file-name>
revision (`Optional[str]`): The repo revision
Returns:
The query result in bool value
"""
cookies = ModelScopeConfig.get_cookies()
files = self.get_model_files(
repo_id,
recursive=True,
revision=revision,
use_cookies=False if cookies is None else cookies,
)
files = [file['Path'] for file in files]
return filename in files
def create_dataset(self,
dataset_name: str,
namespace: str,
chinese_name: Optional[str] = '',
license: Optional[str] = Licenses.APACHE_V2,
visibility: Optional[int] = DatasetVisibility.PUBLIC,
description: Optional[str] = '',
endpoint: Optional[str] = None, ) -> str:
if dataset_name is None or namespace is None:
raise InvalidParameter('dataset_name and namespace are required!')
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise ValueError('Token does not exist, please login first.')
if not endpoint:
endpoint = self.endpoint
path = f'{endpoint}/api/v1/datasets'
files = {
'Name': (None, dataset_name),
'ChineseName': (None, chinese_name),
'Owner': (None, namespace),
'License': (None, license),
'Visibility': (None, visibility),
'Description': (None, description)
}
r = self.session.post(
path,
files=files,
cookies=cookies,
headers=self.builder_headers(self.headers),
)
handle_http_post_error(r, path, files)
raise_on_error(r.json())
dataset_repo_url = f'{endpoint}/datasets/{namespace}/{dataset_name}'
logger.info(f'Create dataset success: {dataset_repo_url}')
return dataset_repo_url
def list_datasets(self, endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
path = f'{endpoint}/api/v1/datasets'
params = {}
r = self.session.get(path, params=params,
headers=self.builder_headers(self.headers))
raise_for_http_status(r)
dataset_list = r.json()[API_RESPONSE_FIELD_DATA]
return [x['Name'] for x in dataset_list]
def delete_dataset(self, dataset_id: str, endpoint: Optional[str] = None):
cookies = ModelScopeConfig.get_cookies()
if not endpoint:
endpoint = self.endpoint
if cookies is None:
raise ValueError('Token does not exist, please login first.')
path = f'{endpoint}/api/v1/datasets/{dataset_id}'
r = self.session.delete(path,
cookies=cookies,
headers=self.builder_headers(self.headers))
raise_for_http_status(r)
raise_on_error(r.json())
def get_dataset_id_and_type(self, dataset_name: str, namespace: str, endpoint: Optional[str] = None):
""" Get the dataset id and type. """
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}'
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(datahub_url, cookies=cookies)
resp = r.json()
datahub_raise_on_error(datahub_url, resp, r)
dataset_id = resp['Data']['Id']
dataset_type = resp['Data']['Type']
return dataset_id, dataset_type
def list_repo_tree(self,
dataset_name: str,
namespace: str,
revision: str,
root_path: str,
recursive: bool = True,
page_number: int = 1,
page_size: int = 100,
endpoint: Optional[str] = None):
"""
@deprecated: Use `get_dataset_files` instead.
"""
warnings.warn('The function `list_repo_tree` is deprecated, use `get_dataset_files` instead.',
DeprecationWarning)
dataset_hub_id, dataset_type = self.get_dataset_id_and_type(
dataset_name=dataset_name, namespace=namespace, endpoint=endpoint)
recursive = 'True' if recursive else 'False'
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{dataset_hub_id}/repo/tree'
params = {'Revision': revision if revision else 'master',
'Root': root_path if root_path else '/', 'Recursive': recursive,
'PageNumber': page_number, 'PageSize': page_size}
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(datahub_url, params=params, cookies=cookies)
resp = r.json()
datahub_raise_on_error(datahub_url, resp, r)
return resp
def list_repo_commits(self,
repo_id: str,
*,
repo_type: Optional[str] = REPO_TYPE_MODEL,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION,
page_number: int = 1,
page_size: int = 50,
endpoint: Optional[str] = None):
"""
Get the commit history for a repository.
Args:
repo_id (str): The repository id, in the format of `namespace/repo_name`.
repo_type (Optional[str]): The type of the repository. Supported types are `model` and `dataset`.
revision (str): The branch or tag name. Defaults to `DEFAULT_REPOSITORY_REVISION`.
page_number (int): The page number for pagination. Defaults to 1.
page_size (int): The number of commits per page. Defaults to 50.
endpoint (Optional[str]): The endpoint to use, defaults to None to use the endpoint specified in the class.
Returns:
CommitHistoryResponse: The commit history response.
Examples:
>>> from modelscope.hub.api import HubApi
>>> api = HubApi()
>>> commit_history = api.list_repo_commits('meituan/Meeseeks')
>>> print(f"Total commits: {commit_history.total_count}")
>>> for commit in commit_history.commits:
... print(f"{commit.short_id}: {commit.title}")
"""
from datasets.utils.file_utils import is_relative_path
if is_relative_path(repo_id) and repo_id.count('/') == 1:
_owner, _dataset_name = repo_id.split('/')
else:
raise ValueError(f'Invalid repo_id: {repo_id} !')
if not endpoint:
endpoint = self.endpoint
commits_url = f'{endpoint}/api/v1/{repo_type}s/{repo_id}/commits' if repo_type else \
f'{endpoint}/api/v1/models/{repo_id}/commits'
params = {
'Ref': revision or DEFAULT_MODEL_REVISION or DEFAULT_REPOSITORY_REVISION,
'PageNumber': page_number,
'PageSize': page_size
}
cookies = ModelScopeConfig.get_cookies()
try:
r = self.session.get(commits_url, params=params,
cookies=cookies, headers=self.builder_headers(self.headers))
raise_for_http_status(r)
resp = r.json()
raise_on_error(resp)
if resp.get('Code') == HTTPStatus.OK:
return CommitHistoryResponse.from_api_response(resp)
except requests.exceptions.RequestException as e:
raise Exception(f'Failed to get repository commits for {repo_id}: {str(e)}')
def get_dataset_files(self,
repo_id: str,
*,
revision: str = DEFAULT_REPOSITORY_REVISION,
root_path: str = '/',
recursive: bool = True,
page_number: int = 1,
page_size: int = 100,
endpoint: Optional[str] = None):
"""
Get the dataset files.
Args:
repo_id (str): The repository id, in the format of `namespace/dataset_name`.
revision (str): The branch or tag name. Defaults to `DEFAULT_REPOSITORY_REVISION`.
root_path (str): The root path to list. Defaults to '/'.
recursive (bool): Whether to list recursively. Defaults to True.
page_number (int): The page number for pagination. Defaults to 1.
page_size (int): The number of items per page. Defaults to 100.
endpoint (Optional[str]): The endpoint to use, defaults to None to use the endpoint specified in the class.
Returns:
List: The response containing the dataset repository tree information.
e.g. [{'CommitId': None, 'CommitMessage': '...', 'Size': 0, 'Type': 'tree'}, ...]
"""
from datasets.utils.file_utils import is_relative_path
if is_relative_path(repo_id) and repo_id.count('/') == 1:
_owner, _dataset_name = repo_id.split('/')
else:
raise ValueError(f'Invalid repo_id: {repo_id} !')
dataset_hub_id, dataset_type = self.get_dataset_id_and_type(
dataset_name=_dataset_name, namespace=_owner, endpoint=endpoint)
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{dataset_hub_id}/repo/tree'
params = {
'Revision': revision,
'Root': root_path,
'Recursive': 'True' if recursive else 'False',
'PageNumber': page_number,
'PageSize': page_size
}
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(datahub_url, params=params, cookies=cookies)
resp = r.json()
datahub_raise_on_error(datahub_url, resp, r)
return resp['Data']['Files']
def get_dataset(
self,
dataset_id: str,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION,
endpoint: Optional[str] = None
):
"""
Get the dataset information.
Args:
dataset_id (str): The dataset id.
revision (Optional[str]): The revision of the dataset.
endpoint (Optional[str]): The endpoint to use, defaults to None to use the endpoint specified in the class.
Returns:
dict: The dataset information.
"""
cookies = ModelScopeConfig.get_cookies()
if not endpoint:
endpoint = self.endpoint
if revision:
path = f'{endpoint}/api/v1/datasets/{dataset_id}?Revision={revision}'
else:
path = f'{endpoint}/api/v1/datasets/{dataset_id}'
r = self.session.get(
path, cookies=cookies, headers=self.builder_headers(self.headers))
raise_for_http_status(r)
resp = r.json()
datahub_raise_on_error(path, resp, r)
return resp[API_RESPONSE_FIELD_DATA]
def get_dataset_meta_file_list(self, dataset_name: str, namespace: str,
dataset_id: str, revision: str, endpoint: Optional[str] = None):
""" Get the meta file-list of the dataset. """
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{dataset_id}/repo/tree?Revision={revision}'
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(datahub_url,
cookies=cookies,
headers=self.builder_headers(self.headers))
resp = r.json()
datahub_raise_on_error(datahub_url, resp, r)
file_list = resp['Data']
if file_list is None:
raise NotExistError(
f'The modelscope dataset [dataset_name = {dataset_name}, namespace = {namespace}, '
f'version = {revision}] dose not exist')
file_list = file_list['Files']
return file_list
@staticmethod
def dump_datatype_file(dataset_type: int, meta_cache_dir: str):
"""
Dump the data_type as a local file, in order to get the dataset
formation without calling the datahub.
More details, please refer to the class
`modelscope.utils.constant.DatasetFormations`.
"""
dataset_type_file_path = os.path.join(meta_cache_dir,
f'{str(dataset_type)}{DatasetFormations.formation_mark_ext.value}')
with open(dataset_type_file_path, 'w') as fp:
fp.write('*** Automatically-generated file, do not modify ***')
def get_dataset_meta_files_local_paths(self, dataset_name: str,
namespace: str,
revision: str,
meta_cache_dir: str, dataset_type: int, file_list: list,
endpoint: Optional[str] = None):
local_paths = defaultdict(list)
dataset_formation = DatasetFormations(dataset_type)
dataset_meta_format = DatasetMetaFormats[dataset_formation]
cookies = ModelScopeConfig.get_cookies()
# Dump the data_type as a local file
HubApi.dump_datatype_file(dataset_type=dataset_type, meta_cache_dir=meta_cache_dir)
if not endpoint:
endpoint = self.endpoint
for file_info in file_list:
file_path = file_info['Path']
extension = os.path.splitext(file_path)[-1]
if extension in dataset_meta_format:
datahub_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/repo?' \
f'Revision={revision}&FilePath={file_path}'
r = self.session.get(datahub_url, cookies=cookies)
raise_for_http_status(r)
local_path = os.path.join(meta_cache_dir, file_path)
if os.path.exists(local_path):
logger.warning(
f"Reusing dataset {dataset_name}'s python file ({local_path})"
)
local_paths[extension].append(local_path)
continue
with open(local_path, 'wb') as f:
f.write(r.content)
local_paths[extension].append(local_path)
return local_paths, dataset_formation
@staticmethod
def fetch_meta_files_from_url(url, out_path, chunk_size=1024, mode=DownloadMode.REUSE_DATASET_IF_EXISTS):
"""
Fetch the meta-data files from the url, e.g. csv/jsonl files.
"""
import hashlib
from tqdm.auto import tqdm
import pandas as pd
out_path = os.path.join(out_path, hashlib.md5(url.encode(encoding='UTF-8')).hexdigest())
if mode == DownloadMode.FORCE_REDOWNLOAD and os.path.exists(out_path):
os.remove(out_path)
if os.path.exists(out_path):
logger.info(f'Reusing cached meta-data file: {out_path}')
return out_path
cookies = ModelScopeConfig.get_cookies()
# Make the request and get the response content as TextIO
logger.info('Loading meta-data file ...')
response = requests.get(url, cookies=cookies, stream=True)
total_size = int(response.headers.get('content-length', 0))
progress = tqdm(total=total_size, dynamic_ncols=True)
def get_chunk(resp):
chunk_data = []
for data in resp.iter_lines():
data = data.decode('utf-8')
chunk_data.append(data)
if len(chunk_data) >= chunk_size:
yield chunk_data
chunk_data = []
yield chunk_data
iter_num = 0
with open(out_path, 'a') as f:
for chunk in get_chunk(response):
progress.update(len(chunk))
if url.endswith('jsonl'):
chunk = [json.loads(line) for line in chunk if line.strip()]
if len(chunk) == 0:
continue
if iter_num == 0:
with_header = True
else:
with_header = False
chunk_df = pd.DataFrame(chunk)
chunk_df.to_csv(f, index=False, header=with_header, escapechar='\\')
iter_num += 1
else:
# csv or others
for line in chunk:
f.write(line + '\n')
progress.close()
return out_path
def get_dataset_file_url(
self,
file_name: str,
dataset_name: str,
namespace: str,
revision: Optional[str] = DEFAULT_DATASET_REVISION,
view: Optional[bool] = False,
extension_filter: Optional[bool] = True,
endpoint: Optional[str] = None):
if not file_name or not dataset_name or not namespace:
raise ValueError('Args (file_name, dataset_name, namespace) cannot be empty!')
# Note: make sure the FilePath is the last parameter in the url
params: dict = {'Source': 'SDK', 'Revision': revision, 'FilePath': file_name, 'View': view}
params: str = urlencode(params)
if not endpoint:
endpoint = self.endpoint
file_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/repo?{params}'
return file_url
# if extension_filter:
# if os.path.splitext(file_name)[-1] in META_FILES_FORMAT:
# file_url = f'{self.endpoint}/api/v1/datasets/{namespace}/{dataset_name}/repo?'\
# f'Revision={revision}&FilePath={file_name}'
# else:
# file_url = file_name
# return file_url
# else:
# return file_url
def get_dataset_file_url_origin(
self,
file_name: str,
dataset_name: str,
namespace: str,
revision: Optional[str] = DEFAULT_DATASET_REVISION,
endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
if file_name and os.path.splitext(file_name)[-1] in META_FILES_FORMAT:
file_name = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/repo?' \
f'Revision={revision}&FilePath={file_name}'
return file_name
def get_dataset_access_config(
self,
dataset_name: str,
namespace: str,
revision: Optional[str] = DEFAULT_DATASET_REVISION,
endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/' \
f'ststoken?Revision={revision}'
return self.datahub_remote_call(datahub_url)
def get_dataset_access_config_session(
self,
dataset_name: str,
namespace: str,
check_cookie: bool,
revision: Optional[str] = DEFAULT_DATASET_REVISION,
endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/' \
f'ststoken?Revision={revision}'
if check_cookie:
cookies = self._check_cookie(use_cookies=True)
else:
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(
url=datahub_url,
cookies=cookies,
headers=self.builder_headers(self.headers))
resp = r.json()
raise_on_error(resp)
return resp['Data']
def get_virgo_meta(self, dataset_id: str, version: int = 1) -> dict:
"""
Get virgo dataset meta info.
"""
virgo_endpoint = os.environ.get(VirgoDatasetConfig.env_virgo_endpoint, '')
if not virgo_endpoint:
raise RuntimeError(f'Virgo endpoint is not set in env: {VirgoDatasetConfig.env_virgo_endpoint}')
virgo_dataset_url = f'{virgo_endpoint}/data/set/download'
cookies = requests.utils.dict_from_cookiejar(ModelScopeConfig.get_cookies())
dataset_info = dict(
dataSetId=dataset_id,
dataSetVersion=version
)
data = dict(
data=dataset_info,
)
r = self.session.post(url=virgo_dataset_url,
json=data,
cookies=cookies,
headers=self.builder_headers(self.headers),
timeout=900)
resp = r.json()
if resp['code'] != 0:
raise RuntimeError(f'Failed to get virgo dataset: {resp}')
return resp['data']
def get_dataset_access_config_for_unzipped(self,
dataset_name: str,
namespace: str,
revision: str,
zip_file_name: str,
endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
datahub_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}'
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(url=datahub_url, cookies=cookies,
headers=self.builder_headers(self.headers))
resp = r.json()
# get visibility of the dataset
raise_on_error(resp)
data = resp['Data']
visibility = VisibilityMap.get(data['Visibility'])
datahub_sts_url = f'{datahub_url}/ststoken?Revision={revision}'
r_sts = self.session.get(url=datahub_sts_url, cookies=cookies,
headers=self.builder_headers(self.headers))
resp_sts = r_sts.json()
raise_on_error(resp_sts)
data_sts = resp_sts['Data']
file_dir = visibility + '-unzipped' + '/' + namespace + '_' + dataset_name + '_' + zip_file_name
data_sts['Dir'] = file_dir
return data_sts
def list_oss_dataset_objects(self, dataset_name, namespace, max_limit,
is_recursive, is_filter_dir, revision, endpoint: Optional[str] = None):
if not endpoint:
endpoint = self.endpoint
url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/oss/tree/?' \
f'MaxLimit={max_limit}&Revision={revision}&Recursive={is_recursive}&FilterDir={is_filter_dir}'
cookies = ModelScopeConfig.get_cookies()
resp = self.session.get(url=url, cookies=cookies, timeout=1800)
resp = resp.json()
raise_on_error(resp)
resp = resp['Data']
return resp
def delete_oss_dataset_object(self, object_name: str, dataset_name: str,
namespace: str, revision: str, endpoint: Optional[str] = None) -> str:
if not object_name or not dataset_name or not namespace or not revision:
raise ValueError('Args cannot be empty!')
if not endpoint:
endpoint = self.endpoint
url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/oss?Path={object_name}&Revision={revision}'
cookies = ModelScopeConfig.get_cookies()
resp = self.session.delete(url=url, cookies=cookies)
resp = resp.json()
raise_on_error(resp)
resp = resp['Message']
return resp
def delete_oss_dataset_dir(self, object_name: str, dataset_name: str,
namespace: str, revision: str, endpoint: Optional[str] = None) -> str:
if not object_name or not dataset_name or not namespace or not revision:
raise ValueError('Args cannot be empty!')
if not endpoint:
endpoint = self.endpoint
url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/oss/prefix?Prefix={object_name}/' \
f'&Revision={revision}'
cookies = ModelScopeConfig.get_cookies()
resp = self.session.delete(url=url, cookies=cookies)
resp = resp.json()
raise_on_error(resp)
resp = resp['Message']
return resp
def datahub_remote_call(self, url):
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(
url,
cookies=cookies,
headers={'user-agent': ModelScopeConfig.get_user_agent()})
resp = r.json()
datahub_raise_on_error(url, resp, r)
return resp['Data']
def dataset_download_statistics(self, dataset_name: str, namespace: str,
use_streaming: bool = False, endpoint: Optional[str] = None) -> None:
is_ci_test = os.getenv('CI_TEST') == 'True'
if not endpoint:
endpoint = self.endpoint
if dataset_name and namespace and not is_ci_test and not use_streaming:
try:
cookies = ModelScopeConfig.get_cookies()
# Download count
download_count_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/download/increase'
download_count_resp = self.session.post(download_count_url, cookies=cookies,
headers=self.builder_headers(self.headers))
raise_for_http_status(download_count_resp)
# Download uv
channel = DownloadChannel.LOCAL.value
user_name = ''
if MODELSCOPE_CLOUD_ENVIRONMENT in os.environ:
channel = os.environ[MODELSCOPE_CLOUD_ENVIRONMENT]
if MODELSCOPE_CLOUD_USERNAME in os.environ:
user_name = os.environ[MODELSCOPE_CLOUD_USERNAME]
download_uv_url = f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/download/uv/' \
f'{channel}?user={user_name}'
download_uv_resp = self.session.post(download_uv_url, cookies=cookies,
headers=self.builder_headers(self.headers))
download_uv_resp = download_uv_resp.json()
raise_on_error(download_uv_resp)
except Exception as e:
logger.error(e)
def builder_headers(self, headers):
return {MODELSCOPE_REQUEST_ID: str(uuid.uuid4().hex),
**headers}
def get_file_base_path(self, repo_id: str, endpoint: Optional[str] = None) -> str:
_namespace, _dataset_name = repo_id.split('/')
if not endpoint:
endpoint = self.endpoint
return f'{endpoint}/api/v1/datasets/{_namespace}/{_dataset_name}/repo?'
# return f'{endpoint}/api/v1/datasets/{namespace}/{dataset_name}/repo?Revision={revision}&FilePath='
def create_repo(
self,
repo_id: str,
*,
token: Union[str, bool, None] = None,
visibility: Optional[str] = Visibility.PUBLIC,
repo_type: Optional[str] = REPO_TYPE_MODEL,
chinese_name: Optional[str] = None,
license: Optional[str] = Licenses.APACHE_V2,
endpoint: Optional[str] = None,
exist_ok: Optional[bool] = False,
create_default_config: Optional[bool] = True,
aigc_model: Optional[AigcModel] = None,
**kwargs,
) -> str:
"""
Create a repository on the ModelScope Hub.
Args:
repo_id (str): The repo id in the format of `owner_name/repo_name`.
token (Union[str, bool, None]): The access token.
visibility (Optional[str]): The visibility of the repo,
could be `public`, `private`, `internal`, default to `public`.
repo_type (Optional[str]): The repo type, default to `model`.
chinese_name (Optional[str]): The Chinese name of the repo.
license (Optional[str]): The license of the repo, default to `apache-2.0`.
endpoint (Optional[str]): The endpoint to use.
In the format of `https://www.modelscope.cn` or 'https://www.modelscope.ai'
exist_ok (Optional[bool]): If the repo exists, whether to return the repo url directly.
create_default_config (Optional[bool]): If True, create a default configuration file in the model repo.
**kwargs: The additional arguments.
Returns:
str: The repo url.
"""
if not repo_id:
raise ValueError('Repo id cannot be empty!')
if not endpoint:
endpoint = self.endpoint
self.login(access_token=token, endpoint=endpoint)
repo_exists: bool = self.repo_exists(repo_id, repo_type=repo_type, endpoint=endpoint, token=token)
if repo_exists:
if exist_ok:
repo_url: str = f'{endpoint}/{repo_type}s/{repo_id}'
logger.warning(f'Repo {repo_id} already exists, got repo url: {repo_url}')
return repo_url
else:
raise ValueError(f'Repo {repo_id} already exists!')
repo_id_list = repo_id.split('/')
if len(repo_id_list) != 2:
raise ValueError('Invalid repo id, should be in the format of `owner_name/repo_name`')
namespace, repo_name = repo_id_list
if repo_type == REPO_TYPE_MODEL:
visibilities = {k: v for k, v in ModelVisibility.__dict__.items() if not k.startswith('__')}
visibility: int = visibilities.get(visibility.upper())
if visibility is None:
raise ValueError(f'Invalid visibility: {visibility}, '
f'supported visibilities: `public`, `private`, `internal`')
repo_url: str = self.create_model(
model_id=repo_id,
visibility=visibility,
license=license,
chinese_name=chinese_name,
aigc_model=aigc_model
)
if create_default_config:
with tempfile.TemporaryDirectory() as temp_cache_dir:
from modelscope.hub.repository import Repository
repo = Repository(temp_cache_dir, repo_id)
default_config = {
'framework': 'pytorch',
'task': 'text-generation',
'allow_remote': True
}
config_json = kwargs.get('config_json')
if not config_json:
config_json = {}
config = {**default_config, **config_json}
add_content_to_file(
repo,
'configuration.json', [json.dumps(config)],
ignore_push_error=True)
print(f'New model created successfully at {repo_url}.', flush=True)
elif repo_type == REPO_TYPE_DATASET:
visibilities = {k: v for k, v in DatasetVisibility.__dict__.items() if not k.startswith('__')}
visibility: int = visibilities.get(visibility.upper())
if visibility is None:
raise ValueError(f'Invalid visibility: {visibility}, '
f'supported visibilities: `public`, `private`, `internal`')
repo_url: str = self.create_dataset(
dataset_name=repo_name,
namespace=namespace,
chinese_name=chinese_name,
license=license,
visibility=visibility,
)
print(f'New dataset created successfully at {repo_url}.', flush=True)
else:
raise ValueError(f'Invalid repo type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
return repo_url
def create_commit(
self,
repo_id: str,
operations: Iterable[CommitOperation],
*,
commit_message: str,
commit_description: Optional[str] = None,
token: str = None,
repo_type: Optional[str] = REPO_TYPE_MODEL,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION,
endpoint: Optional[str] = None,
max_retries: int = 3,
timeout: int = 180,
) -> CommitInfo:
"""
Create a commit on the ModelScope Hub with retry mechanism.
Args:
repo_id (str): The repo id in the format of `owner_name/repo_name`.
operations (Iterable[CommitOperation]): The commit operations.
commit_message (str): The commit message.
commit_description (Optional[str]): The commit description.
token (str): The access token. If None, will use the cookies from the local cache.
See `https://modelscope.cn/my/myaccesstoken` to get your token.
repo_type (Optional[str]): The repo type, should be `model` or `dataset`. Defaults to `model`.
revision (Optional[str]): The branch or tag name. Defaults to `DEFAULT_REPOSITORY_REVISION`.
endpoint (Optional[str]): The endpoint to use.
In the format of `https://www.modelscope.cn` or 'https://www.modelscope.ai'
max_retries (int): Number of max retry attempts (default: 3).
timeout (int): Timeout for each request in seconds (default: 180).
Returns:
CommitInfo: The commit info.
Raises:
requests.exceptions.RequestException: If all retry attempts fail.
"""
if not repo_id:
raise ValueError('Repo id cannot be empty!')
if not endpoint:
endpoint = self.endpoint
if repo_type not in REPO_TYPE_SUPPORT:
raise ValueError(f'Invalid repo type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
url = f'{endpoint}/api/v1/repos/{repo_type}s/{repo_id}/commit/{revision}'
commit_message = commit_message or f'Commit to {repo_id}'
commit_description = commit_description or ''
cookies = self.get_cookies(access_token=token, cookies_required=True)
# Construct payload
payload = self._prepare_commit_payload(
operations=operations,
commit_message=commit_message,
)
# POST with retry mechanism
last_exception = None
for attempt in range(max_retries):
try:
if attempt > 0:
logger.info(f'Attempt {attempt + 1} to create commit for {repo_id}...')
response = requests.post(
url,
headers=self.builder_headers(self.headers),
data=json.dumps(payload),
cookies=cookies,
timeout=timeout,
)
if response.status_code != 200:
try:
error_detail = response.json()
except json.JSONDecodeError:
error_detail = response.text
error_msg = (
f'HTTP {response.status_code} error from {url}: '
f'{error_detail}'
)
# If server error (5xx), we can retry, otherwise (4xx) raise immediately
if 500 <= response.status_code < 600:
logger.warning(
f'Server error on attempt {attempt + 1}: {error_msg}'
)
else:
raise ValueError(f'Client request failed: {error_msg}')
else:
resp = response.json()
oid = resp.get('Data', {}).get('oid', '')
logger.info(f'Commit succeeded: {url}')
return CommitInfo(
commit_url=url,
commit_message=commit_message,
commit_description=commit_description,
oid=oid,
)
except requests.exceptions.RequestException as e:
last_exception = e
logger.warning(f'Request failed on attempt {attempt + 1}: {str(e)}')
except Exception as e:
last_exception = e
logger.error(f'Unexpected error on attempt {attempt + 1}: {str(e)}')
if attempt == max_retries - 1:
raise
if attempt < max_retries - 1:
time.sleep(1)
# All retries exhausted
raise requests.exceptions.RequestException(
f'Failed to create commit after {max_retries} attempts. Last error: {last_exception}'
)
def upload_file(
self,
*,
path_or_fileobj: Union[str, Path, bytes, BinaryIO],
path_in_repo: str,
repo_id: str,
token: Union[str, None] = None,
repo_type: Optional[str] = REPO_TYPE_MODEL,
commit_message: Optional[str] = None,
commit_description: Optional[str] = None,
buffer_size_mb: Optional[int] = 1,
tqdm_desc: Optional[str] = '[Uploading]',
disable_tqdm: Optional[bool] = False,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION
) -> CommitInfo:
"""
Upload a file to the ModelScope Hub.
Args:
path_or_fileobj (Union[str, Path, bytes, BinaryIO]):
The local file path or file-like object (BinaryIO) or bytes to upload.
path_in_repo (str): The path in the repo to upload to.
repo_id (str): The repo id in the format of `owner_name/repo_name`.
token (Union[str, None]): The access token. If None, will use the cookies from the local cache.
See `https://modelscope.cn/my/myaccesstoken` to get your token.
repo_type (Optional[str]): The repo type, default to `model`.
commit_message (Optional[str]): The commit message.
commit_description (Optional[str]): The commit description.
buffer_size_mb (Optional[int]): The buffer size in MB for reading the file. Default to 1MB.
tqdm_desc (Optional[str]): The description for the tqdm progress bar. Default to '[Uploading]'.
disable_tqdm (Optional[bool]): Whether to disable the tqdm progress bar. Default to False.
revision (Optional[str]): The branch or tag name. Defaults to `DEFAULT_REPOSITORY_REVISION`.
Returns:
CommitInfo: The commit info.
Examples:
>>> from modelscope.hub.api import HubApi
>>> api = HubApi()
>>> commit_info = api.upload_file(
... path_or_fileobj='/path/to/your/file.txt',
... path_in_repo='optional/path/in/repo/file.txt',
... repo_id='your-namespace/your-repo-name',
... commit_message='Upload file.txt to ModelScope hub'
... )
>>> print(commit_info)
"""
if repo_type not in REPO_TYPE_SUPPORT:
raise ValueError(f'Invalid repo type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
if not path_or_fileobj:
raise ValueError('Path or file object cannot be empty!')
# Check authentication first
self.get_cookies(access_token=token, cookies_required=True)
if isinstance(path_or_fileobj, (str, Path)):
path_or_fileobj = os.path.abspath(os.path.expanduser(path_or_fileobj))
path_in_repo = path_in_repo or os.path.basename(path_or_fileobj)
else:
# If path_or_fileobj is bytes or BinaryIO, then path_in_repo must be provided
if not path_in_repo:
raise ValueError('Arg `path_in_repo` cannot be empty!')
# Read file content if path_or_fileobj is a file-like object (BinaryIO)
# TODO: to be refined
if isinstance(path_or_fileobj, io.BufferedIOBase):
path_or_fileobj = path_or_fileobj.read()
self.upload_checker.check_file(path_or_fileobj)
self.upload_checker.check_normal_files(
file_path_list=[path_or_fileobj],
repo_type=repo_type,
)
commit_message = (
commit_message if commit_message is not None else f'Upload {path_in_repo} to ModelScope hub'
)
if buffer_size_mb <= 0:
raise ValueError('Buffer size: `buffer_size_mb` must be greater than 0')
hash_info_d: dict = get_file_hash(
file_path_or_obj=path_or_fileobj,
buffer_size_mb=buffer_size_mb,
)
file_size: int = hash_info_d['file_size']
file_hash: str = hash_info_d['file_hash']
self.create_repo(repo_id=repo_id,
token=token,
repo_type=repo_type,
endpoint=self.endpoint,
exist_ok=True,
create_default_config=False)
upload_res: dict = self._upload_blob(
repo_id=repo_id,
repo_type=repo_type,
sha256=file_hash,
size=file_size,
data=path_or_fileobj,
disable_tqdm=disable_tqdm,
tqdm_desc=tqdm_desc,
)
# Construct commit info and create commit
add_operation: CommitOperationAdd = CommitOperationAdd(
path_in_repo=path_in_repo,
path_or_fileobj=path_or_fileobj,
file_hash_info=hash_info_d,
)
add_operation._upload_mode = 'lfs' if self.upload_checker.is_lfs(path_or_fileobj, repo_type) else 'normal'
add_operation._is_uploaded = upload_res['is_uploaded']
operations = [add_operation]
print(f'Committing file to {repo_id} ...', flush=True)
commit_info: CommitInfo = self.create_commit(
repo_id=repo_id,
operations=operations,
commit_message=commit_message,
commit_description=commit_description,
token=token,
repo_type=repo_type,
revision=revision,
)
return commit_info
def upload_folder(
self,
*,
repo_id: str,
folder_path: Union[str, Path, List[str], List[Path]],
path_in_repo: Optional[str] = '',
commit_message: Optional[str] = None,
commit_description: Optional[str] = None,
token: Union[str, None] = None,
repo_type: Optional[str] = REPO_TYPE_MODEL,
allow_patterns: Optional[Union[List[str], str]] = None,
ignore_patterns: Optional[Union[List[str], str]] = None,
max_workers: int = DEFAULT_MAX_WORKERS,
revision: Optional[str] = DEFAULT_REPOSITORY_REVISION,
) -> Union[CommitInfo, List[CommitInfo]]:
"""
Upload a folder to the ModelScope Hub.
Args:
repo_id (str): The repo id in the format of `owner_name/repo_name`.
folder_path (Union[str, Path, List[str], List[Path]]): The folder path or list of file paths to upload.
path_in_repo (Optional[str]): The path in the repo to upload to.
commit_message (Optional[str]): The commit message.
commit_description (Optional[str]): The commit description.
token (Union[str, None]): The access token. If None, will use the cookies from the local cache.
See `https://modelscope.cn/my/myaccesstoken` to get your token.
repo_type (Optional[str]): The repo type, default to `model`.
allow_patterns (Optional[Union[List[str], str]]): The patterns to allow.
ignore_patterns (Optional[Union[List[str], str]]): The patterns to ignore.
max_workers (int): The maximum number of workers to use for uploading files concurrently.
Defaults to `DEFAULT_MAX_WORKERS`.
revision (Optional[str]): The branch or tag name. Defaults to `DEFAULT_REPOSITORY_REVISION`.
Returns:
Union[CommitInfo, List[CommitInfo]]:
The commit info or list of commit infos if multiple batches are committed.
Examples:
>>> from modelscope.hub.api import HubApi
>>> api = HubApi()
>>> commit_info = api.upload_folder(
... repo_id='your-namespace/your-repo-name',
... folder_path='/path/to/your/folder',
... path_in_repo='optional/path/in/repo',
... commit_message='Upload my folder',
... token='your-access-token'
... )
>>> print(commit_info.commit_url)
"""
if not repo_id:
raise ValueError('The arg `repo_id` cannot be empty!')
if folder_path is None:
raise ValueError('The arg `folder_path` cannot be None!')
if repo_type not in REPO_TYPE_SUPPORT:
raise ValueError(f'Invalid repo type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
# Check authentication first
self.get_cookies(access_token=token, cookies_required=True)
allow_patterns = allow_patterns if allow_patterns else None
ignore_patterns = ignore_patterns if ignore_patterns else None
# Ignore .git folder
if ignore_patterns is None:
ignore_patterns = []
elif isinstance(ignore_patterns, str):
ignore_patterns = [ignore_patterns]
ignore_patterns += DEFAULT_IGNORE_PATTERNS
commit_message = (
commit_message if commit_message is not None else f'Upload to {repo_id} on ModelScope hub'
)
commit_description = commit_description or 'Uploading files'
# Get the list of files to upload, e.g. [('data/abc.png', '/path/to/abc.png'), ...]
logger.info('Preparing files to upload ...')
prepared_repo_objects = self._prepare_upload_folder(
folder_path_or_files=folder_path,
path_in_repo=path_in_repo,
allow_patterns=allow_patterns,
ignore_patterns=ignore_patterns,
)
if len(prepared_repo_objects) == 0:
raise ValueError(f'No files to upload in the folder: {folder_path} !')
logger.info(f'Checking {len(prepared_repo_objects)} files to upload ...')
self.upload_checker.check_normal_files(
file_path_list=[item for _, item in prepared_repo_objects],
repo_type=repo_type,
)
self.create_repo(repo_id=repo_id,
token=token,
repo_type=repo_type,
endpoint=self.endpoint,
exist_ok=True,
create_default_config=False)
@thread_executor(max_workers=max_workers, disable_tqdm=False)
def _upload_items(item_pair, **kwargs):
file_path_in_repo, file_path = item_pair
hash_info_d: dict = get_file_hash(
file_path_or_obj=file_path,
)
file_size: int = hash_info_d['file_size']
file_hash: str = hash_info_d['file_hash']
upload_res: dict = self._upload_blob(
repo_id=repo_id,
repo_type=repo_type,
sha256=file_hash,
size=file_size,
data=file_path,
disable_tqdm=file_size <= UPLOAD_BLOB_TQDM_DISABLE_THRESHOLD,
tqdm_desc='[Uploading ' + file_path_in_repo + ']',
)
return {
'file_path_in_repo': file_path_in_repo,
'file_path': file_path,
'is_uploaded': upload_res['is_uploaded'],
'file_hash_info': hash_info_d,
}
uploaded_items_list = _upload_items(
prepared_repo_objects,
repo_id=repo_id,
token=token,
repo_type=repo_type,
commit_message=commit_message,
commit_description=commit_description,
buffer_size_mb=1,
disable_tqdm=False,
)
# Construct commit info and create commit
operations = []
for item_d in uploaded_items_list:
prepared_path_in_repo: str = item_d['file_path_in_repo']
prepared_file_path: str = item_d['file_path']
is_uploaded: bool = item_d['is_uploaded']
file_hash_info: dict = item_d['file_hash_info']
opt = CommitOperationAdd(
path_in_repo=prepared_path_in_repo,
path_or_fileobj=prepared_file_path,
file_hash_info=file_hash_info,
)
# check normal or lfs
opt._upload_mode = 'lfs' if self.upload_checker.is_lfs(prepared_file_path, repo_type) else 'normal'
opt._is_uploaded = is_uploaded
operations.append(opt)
if len(operations) == 0:
raise ValueError(f'No files to upload in the folder: {folder_path} !')
# Commit the operations in batches
commit_batch_size: int = UPLOAD_COMMIT_BATCH_SIZE if UPLOAD_COMMIT_BATCH_SIZE > 0 else len(operations)
num_batches = (len(operations) - 1) // commit_batch_size + 1
print(f'Committing {len(operations)} files in {num_batches} batch(es) of size {commit_batch_size}.',
flush=True)
commit_infos: List[CommitInfo] = []
for i in tqdm(range(num_batches), desc='[Committing batches] ', total=num_batches):
batch_operations = operations[i * commit_batch_size: (i + 1) * commit_batch_size]
batch_commit_message = f'{commit_message} (batch {i + 1}/{num_batches})'
commit_info: CommitInfo = self.create_commit(
repo_id=repo_id,
operations=batch_operations,
commit_message=batch_commit_message,
commit_description=commit_description,
token=token,
repo_type=repo_type,
revision=revision,
)
commit_infos.append(commit_info)
return commit_infos[0] if len(commit_infos) == 1 else commit_infos
def _upload_blob(
self,
*,
repo_id: str,
repo_type: str,
sha256: str,
size: int,
data: Union[str, Path, bytes, BinaryIO],
disable_tqdm: Optional[bool] = False,
tqdm_desc: Optional[str] = '[Uploading]',
buffer_size_mb: Optional[int] = 1,
) -> dict:
res_d: dict = dict(
url=None,
is_uploaded=False,
status_code=None,
status_msg=None,
)
objects = [{'oid': sha256, 'size': size}]
upload_objects = self._validate_blob(
repo_id=repo_id,
repo_type=repo_type,
objects=objects,
)
# upload_object: {'url': 'xxx', 'oid': 'xxx'}
upload_object = upload_objects[0] if len(upload_objects) == 1 else None
if upload_object is None:
logger.debug(f'Blob {sha256[:8]} has already uploaded, reuse it.')
res_d['is_uploaded'] = True
return res_d
cookies = ModelScopeConfig.get_cookies()
cookies = dict(cookies) if cookies else None
if cookies is None:
raise ValueError('Token does not exist, please login first.')
self.headers.update({'Cookie': f"m_session_id={cookies['m_session_id']}"})
headers = self.builder_headers(self.headers)
def read_in_chunks(file_object, pbar, chunk_size=buffer_size_mb * 1024 * 1024):
"""Lazy function (generator) to read a file piece by piece."""
while True:
ck = file_object.read(chunk_size)
if not ck:
break
pbar.update(len(ck))
yield ck
with tqdm(
total=size,
unit='B',
unit_scale=True,
desc=tqdm_desc,
disable=disable_tqdm
) as pbar:
if isinstance(data, (str, Path)):
with open(data, 'rb') as f:
response = requests.put(
upload_object['url'],
headers=headers,
data=read_in_chunks(f, pbar)
)
elif isinstance(data, bytes):
response = requests.put(
upload_object['url'],
headers=headers,
data=read_in_chunks(io.BytesIO(data), pbar)
)
elif isinstance(data, io.BufferedIOBase):
response = requests.put(
upload_object['url'],
headers=headers,
data=read_in_chunks(data, pbar)
)
else:
raise ValueError('Invalid data type to upload')
raise_for_http_status(rsp=response)
resp = response.json()
raise_on_error(rsp=resp)
res_d['url'] = upload_object['url']
res_d['status_code'] = resp['Code']
res_d['status_msg'] = resp['Message']
return res_d
def _validate_blob(
self,
*,
repo_id: str,
repo_type: str,
objects: List[Dict[str, Any]],
endpoint: Optional[str] = None
) -> List[Dict[str, Any]]:
"""
Check the blob has already uploaded.
True -- uploaded; False -- not uploaded.
Args:
repo_id (str): The repo id ModelScope.
repo_type (str): The repo type. `dataset`, `model`, etc.
objects (List[Dict[str, Any]]): The objects to check.
oid (str): The sha256 hash value.
size (int): The size of the blob.
endpoint: the endpoint to use, default to None to use endpoint specified in the class
Returns:
List[Dict[str, Any]]: The result of the check.
"""
# construct URL
if not endpoint:
endpoint = self.endpoint
url = f'{endpoint}/api/v1/repos/{repo_type}s/{repo_id}/info/lfs/objects/batch'
# build payload
payload = {
'operation': 'upload',
'objects': objects,
}
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise ValueError('Token does not exist, please login first.')
response = requests.post(
url,
headers=self.builder_headers(self.headers),
data=json.dumps(payload),
cookies=cookies
)
raise_for_http_status(rsp=response)
resp = response.json()
raise_on_error(rsp=resp)
upload_objects = [] # list of objects to upload, [{'url': 'xxx', 'oid': 'xxx'}, ...]
resp_objects = resp['Data']['objects']
for obj in resp_objects:
upload_objects.append(
{'url': obj['actions']['upload']['href'],
'oid': obj['oid']}
)
return upload_objects
def _prepare_upload_folder(
self,
folder_path_or_files: Union[str, Path, List[str], List[Path]],
path_in_repo: str,
allow_patterns: Optional[Union[List[str], str]] = None,
ignore_patterns: Optional[Union[List[str], str]] = None,
) -> List[Union[tuple, list]]:
folder_path = None
files_path = None
if isinstance(folder_path_or_files, list):
if os.path.isfile(folder_path_or_files[0]):
files_path = folder_path_or_files
else:
raise ValueError('Uploading multiple folders is not supported now.')
else:
if os.path.isfile(folder_path_or_files):
files_path = [folder_path_or_files]
else:
folder_path = folder_path_or_files
if files_path is None:
self.upload_checker.check_folder(folder_path)
folder_path = Path(folder_path).expanduser().resolve()
if not folder_path.is_dir():
raise ValueError(f"Provided path: '{folder_path}' is not a directory")
# List files from folder
relpath_to_abspath = {
path.relative_to(folder_path).as_posix(): path
for path in sorted(folder_path.glob('**/*')) # sorted to be deterministic
if path.is_file()
}
else:
relpath_to_abspath = {}
for path in files_path:
if os.path.isfile(path):
self.upload_checker.check_file(path)
relpath_to_abspath[os.path.basename(path)] = path
# Filter files
filtered_repo_objects = list(
RepoUtils.filter_repo_objects(
relpath_to_abspath.keys(), allow_patterns=allow_patterns, ignore_patterns=ignore_patterns
)
)
prefix = f"{path_in_repo.strip('/')}/" if path_in_repo else ''
prepared_repo_objects = [
(prefix + relpath, str(relpath_to_abspath[relpath]))
for relpath in filtered_repo_objects
]
logger.info(f'Prepared {len(prepared_repo_objects)} files for upload.')
return prepared_repo_objects
@staticmethod
def _prepare_commit_payload(
operations: Iterable[CommitOperation],
commit_message: str,
) -> Dict[str, Any]:
"""
Prepare the commit payload to be sent to the ModelScope hub.
"""
payload = {
'commit_message': commit_message,
'actions': []
}
nb_ignored_files = 0
# 2. Send operations, one per line
for operation in operations:
# Skip ignored files
if isinstance(operation, CommitOperationAdd) and operation._should_ignore:
logger.debug(f"Skipping file '{operation.path_in_repo}' in commit (ignored by gitignore file).")
nb_ignored_files += 1
continue
# 2.a. Case adding a normal file
if isinstance(operation, CommitOperationAdd) and operation._upload_mode == 'normal':
commit_action = {
'action': 'update' if operation._is_uploaded else 'create',
'path': operation.path_in_repo,
'type': 'normal',
'size': operation.upload_info.size,
'sha256': '',
'content': operation.b64content().decode(),
'encoding': 'base64',
}
payload['actions'].append(commit_action)
# 2.b. Case adding an LFS file
elif isinstance(operation, CommitOperationAdd) and operation._upload_mode == 'lfs':
commit_action = {
'action': 'update' if operation._is_uploaded else 'create',
'path': operation.path_in_repo,
'type': 'lfs',
'size': operation.upload_info.size,
'sha256': operation.upload_info.sha256,
'content': '',
'encoding': '',
}
payload['actions'].append(commit_action)
else:
raise ValueError(
f'Unknown operation to commit. Operation: {operation}. Upload mode:'
f" {getattr(operation, '_upload_mode', None)}"
)
if nb_ignored_files > 0:
logger.info(f'Skipped {nb_ignored_files} file(s) in commit (ignored by gitignore file).')
return payload
def _get_internal_acceleration_domain(self, internal_timeout: float = 0.2):
"""
Get the internal acceleration domain.
Args:
internal_timeout (float): The timeout for the request. Default to 0.2s
Returns:
str: The internal acceleration domain. e.g. `cn-hangzhou`, `cn-zhangjiakou`
"""
def send_request(url: str, timeout: float):
try:
response = requests.get(url, timeout=timeout)
response.raise_for_status()
except requests.exceptions.RequestException:
response = None
return response
internal_url = f'{self.endpoint}/api/v1/repos/internalAccelerationInfo'
# Get internal url and region for acceleration
internal_info_response = send_request(url=internal_url, timeout=internal_timeout)
region_id: str = ''
if internal_info_response is not None:
internal_info_response = internal_info_response.json()
if 'Data' in internal_info_response:
query_addr = internal_info_response['Data']['InternalRegionQueryAddress']
else:
query_addr: str = ''
if query_addr:
domain_response = send_request(query_addr, timeout=internal_timeout)
if domain_response is not None:
region_id = domain_response.text.strip()
return region_id
def delete_files(self,
repo_id: str,
repo_type: str,
delete_patterns: Union[str, List[str]],
*,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
endpoint: Optional[str] = None) -> Dict[str, Any]:
"""
Delete files in batch using glob (wildcard) patterns, e.g. '*.py', 'data/*.csv', 'foo*', etc.
Example:
# Delete all Python and Markdown files in a model repo
api.delete_files(
repo_id='your_username/your_model',
repo_type=REPO_TYPE_MODEL,
delete_patterns=['*.py', '*.md']
)
# Delete all CSV files in the data/ directory of a dataset repo
api.delete_files(
repo_id='your_username/your_dataset',
repo_type=REPO_TYPE_DATASET,
delete_patterns='data/*.csv'
)
Args:
repo_id (str): 'owner/repo_name' or 'owner/dataset_name', e.g. 'Koko/my_model'
repo_type (str): REPO_TYPE_MODEL or REPO_TYPE_DATASET
delete_patterns (str or List[str]): List of glob patterns, e.g. '*.py', 'data/*.csv', 'foo*'
revision (str, optional): Branch or tag name
endpoint (str, optional): API endpoint
Returns:
dict: Deletion result
"""
if repo_type not in REPO_TYPE_SUPPORT:
raise ValueError(f'Unsupported repo_type: {repo_type}')
if not delete_patterns:
raise ValueError('delete_patterns cannot be empty')
if isinstance(delete_patterns, str):
delete_patterns = [delete_patterns]
cookies = ModelScopeConfig.get_cookies()
if not endpoint:
endpoint = self.endpoint
if cookies is None:
raise ValueError('Token does not exist, please login first.')
headers = self.builder_headers(self.headers)
# List all files in the repo
if repo_type == REPO_TYPE_MODEL:
files = self.get_model_files(
repo_id,
revision=revision or DEFAULT_MODEL_REVISION,
recursive=True,
endpoint=endpoint,
use_cookies=cookies,
)
file_paths = [f['Path'] for f in files]
elif repo_type == REPO_TYPE_DATASET:
file_paths = []
page_number = 1
page_size = 100
while True:
try:
dataset_files: List[Dict[str, Any]] = self.get_dataset_files(
repo_id=repo_id,
revision=revision or DEFAULT_DATASET_REVISION,
recursive=True,
page_number=page_number,
page_size=page_size,
endpoint=endpoint,
)
except Exception as e:
logger.error(f'Get dataset: {repo_id} file list failed, message: {str(e)}')
break
# Parse data (Type: 'tree' or 'blob')
for file_info_d in dataset_files:
if file_info_d['Type'] != 'tree':
file_paths.append(file_info_d['Path'])
if len(dataset_files) < page_size:
break
page_number += 1
else:
raise ValueError(f'Unsupported repo_type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
# Glob pattern matching
to_delete = []
for path in file_paths:
for delete_pattern in delete_patterns:
if fnmatch.fnmatch(path, delete_pattern):
to_delete.append(path)
break
deleted_files, failed_files = [], []
for path in to_delete:
try:
if repo_type == REPO_TYPE_MODEL:
owner, repo_name = repo_id.split('/')
url = f'{endpoint}/api/v1/models/{owner}/{repo_name}/file'
params = {
'Revision': revision or DEFAULT_MODEL_REVISION,
'FilePath': path
}
elif repo_type == REPO_TYPE_DATASET:
owner, dataset_name = repo_id.split('/')
url = f'{endpoint}/api/v1/datasets/{owner}/{dataset_name}/repo'
params = {
'FilePath': path
}
else:
raise ValueError(f'Unsupported repo_type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
r = self.session.delete(url, params=params, cookies=cookies, headers=headers)
raise_for_http_status(r)
resp = r.json()
raise_on_error(resp)
deleted_files.append(path)
except Exception as e:
failed_files.append(path)
logger.error(f'Failed to delete {path}: {str(e)}')
return {
'deleted_files': deleted_files,
'failed_files': failed_files,
'total_files': len(to_delete)
}
class ModelScopeConfig:
path_credential = expanduser(MODELSCOPE_CREDENTIALS_PATH)
COOKIES_FILE_NAME = 'cookies'
GIT_TOKEN_FILE_NAME = 'git_token'
USER_INFO_FILE_NAME = 'user'
USER_SESSION_ID_FILE_NAME = 'session'
cookie_expired_warning = False
@staticmethod
def make_sure_credential_path_exist():
os.makedirs(ModelScopeConfig.path_credential, exist_ok=True)
@staticmethod
def save_cookies(cookies: CookieJar):
ModelScopeConfig.make_sure_credential_path_exist()
with open(
os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.COOKIES_FILE_NAME), 'wb+') as f:
pickle.dump(cookies, f)
@staticmethod
def get_cookies():
cookies_path = os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.COOKIES_FILE_NAME)
if os.path.exists(cookies_path):
with open(cookies_path, 'rb') as f:
cookies = pickle.load(f)
for cookie in cookies:
if cookie.name == 'm_session_id' and cookie.is_expired() and \
not ModelScopeConfig.cookie_expired_warning:
ModelScopeConfig.cookie_expired_warning = True
logger.info('Not logged-in, you can login for uploading'
'or accessing controlled entities.')
return None
return cookies
return None
@staticmethod
def get_user_session_id():
session_path = os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.USER_SESSION_ID_FILE_NAME)
session_id = ''
if os.path.exists(session_path):
with open(session_path, 'rb') as f:
session_id = str(f.readline().strip(), encoding='utf-8')
return session_id
if session_id == '' or len(session_id) != 32:
session_id = str(uuid.uuid4().hex)
ModelScopeConfig.make_sure_credential_path_exist()
with open(session_path, 'w+') as wf:
wf.write(session_id)
return session_id
@staticmethod
def save_token(token: str):
ModelScopeConfig.make_sure_credential_path_exist()
with open(
os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.GIT_TOKEN_FILE_NAME), 'w+') as f:
f.write(token)
@staticmethod
def save_user_info(user_name: str, user_email: str):
ModelScopeConfig.make_sure_credential_path_exist()
with open(
os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.USER_INFO_FILE_NAME), 'w+') as f:
f.write('%s:%s' % (user_name, user_email))
@staticmethod
def get_user_info() -> Tuple[str, str]:
try:
with open(
os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.USER_INFO_FILE_NAME),
'r',
encoding='utf-8') as f:
info = f.read()
return info.split(':')[0], info.split(':')[1]
except FileNotFoundError:
pass
return None, None
@staticmethod
def get_token() -> Optional[str]:
"""
Get token or None if not existent.
Returns:
`str` or `None`: The token, `None` if it doesn't exist.
"""
token = None
try:
with open(
os.path.join(ModelScopeConfig.path_credential,
ModelScopeConfig.GIT_TOKEN_FILE_NAME),
'r',
encoding='utf-8') as f:
token = f.read()
except FileNotFoundError:
pass
return token
@staticmethod
def get_user_agent(user_agent: Union[Dict, str, None] = None, ) -> str:
"""Formats a user-agent string with basic info about a request.
Args:
user_agent (`str`, `dict`, *optional*):
The user agent info in the form of a dictionary or a single string.
Returns:
The formatted user-agent string.
"""
# include some more telemetrics when executing in dedicated
# cloud containers
env = 'custom'
if MODELSCOPE_CLOUD_ENVIRONMENT in os.environ:
env = os.environ[MODELSCOPE_CLOUD_ENVIRONMENT]
user_name = 'unknown'
if MODELSCOPE_CLOUD_USERNAME in os.environ:
user_name = os.environ[MODELSCOPE_CLOUD_USERNAME]
from modelscope import __version__
ua = 'modelscope/%s; python/%s; session_id/%s; platform/%s; processor/%s; env/%s; user/%s' % (
__version__,
platform.python_version(),
ModelScopeConfig.get_user_session_id(),
platform.platform(),
platform.processor(),
env,
user_name,
)
if isinstance(user_agent, dict):
ua += '; ' + '; '.join(f'{k}/{v}' for k, v in user_agent.items())
elif isinstance(user_agent, str):
ua += '; ' + user_agent
return ua
class UploadingCheck:
"""
Check the files and folders to be uploaded.
Args:
max_file_count (int): The maximum number of files to be uploaded. Default to `UPLOAD_MAX_FILE_COUNT`.
max_file_count_in_dir (int): The maximum number of files in a directory.
Default to `UPLOAD_MAX_FILE_COUNT_IN_DIR`.
max_file_size (int): The maximum size of a single file in bytes. Default to `UPLOAD_MAX_FILE_SIZE`.
size_threshold_to_enforce_lfs (int): The size threshold to enforce LFS in bytes.
Files larger than this size will be enforced to be uploaded via LFS.
Default to `UPLOAD_SIZE_THRESHOLD_TO_ENFORCE_LFS`.
normal_file_size_total_limit (int): The total size limit of normal files in bytes.
Default to `UPLOAD_NORMAL_FILE_SIZE_TOTAL_LIMIT`.
Examples:
>>> from modelscope.hub.api import UploadingCheck
>>> upload_checker = UploadingCheck()
>>> upload_checker.check_file('/path/to/your/file.txt')
>>> upload_checker.check_folder('/path/to/your/folder')
>>> is_lfs = upload_checker.is_lfs('/path/to/your/file.txt', repo_type='model')
>>> print(f'Is LFS: {is_lfs}')
"""
def __init__(
self,
max_file_count: int = UPLOAD_MAX_FILE_COUNT,
max_file_count_in_dir: int = UPLOAD_MAX_FILE_COUNT_IN_DIR,
max_file_size: int = UPLOAD_MAX_FILE_SIZE,
size_threshold_to_enforce_lfs: int = UPLOAD_SIZE_THRESHOLD_TO_ENFORCE_LFS,
normal_file_size_total_limit: int = UPLOAD_NORMAL_FILE_SIZE_TOTAL_LIMIT,
):
self.max_file_count = max_file_count
self.max_file_count_in_dir = max_file_count_in_dir
self.max_file_size = max_file_size
self.size_threshold_to_enforce_lfs = size_threshold_to_enforce_lfs
self.normal_file_size_total_limit = normal_file_size_total_limit
def check_file(self, file_path_or_obj) -> None:
"""
Check a single file to be uploaded.
Args:
file_path_or_obj (Union[str, Path, bytes, BinaryIO]): The file path or file-like object to be checked.
Raises:
ValueError: If the file does not exist or exceeds the size limit.
"""
if isinstance(file_path_or_obj, (str, Path)):
if not os.path.exists(file_path_or_obj):
raise ValueError(f'File {file_path_or_obj} does not exist')
file_size: int = get_file_size(file_path_or_obj)
if file_size > self.max_file_size:
logger.warning(f'File exceeds size limit: {self.max_file_size / (1024 ** 3)} GB, '
f'got {round(file_size / (1024 ** 3), 4)} GB')
def check_folder(self, folder_path: Union[str, Path]):
"""
Check a folder to be uploaded.
Args:
folder_path (Union[str, Path]): The folder path to be checked.
Raises:
ValueError: If the folder does not exist or exceeds the file count limit.
"""
file_count = 0
dir_count = 0
if isinstance(folder_path, str):
folder_path = Path(folder_path)
for item in folder_path.iterdir():
if item.is_file():
file_count += 1
item_size: int = get_file_size(item)
if item_size > self.max_file_size:
logger.warning(f'File {item} exceeds size limit: {self.max_file_size / (1024 ** 3)} GB',
f'got {round(item_size / (1024 ** 3), 4)} GB')
elif item.is_dir():
dir_count += 1
# Count items in subdirectories recursively
sub_file_count, sub_dir_count = self.check_folder(item)
if (sub_file_count + sub_dir_count) > self.max_file_count_in_dir:
raise ValueError(f'Directory {item} contains {sub_file_count + sub_dir_count} items '
f'and exceeds limit: {self.max_file_count_in_dir}')
file_count += sub_file_count
dir_count += sub_dir_count
if file_count > self.max_file_count:
raise ValueError(f'Total file count {file_count} and exceeds limit: {self.max_file_count}')
return file_count, dir_count
def is_lfs(self, file_path_or_obj: Union[str, Path, bytes, BinaryIO], repo_type: str) -> bool:
"""
Check if a file should be uploaded via LFS.
Args:
file_path_or_obj (Union[str, Path, bytes, BinaryIO]): The file path or file-like object to be checked.
repo_type (str): The repo type, either `model` or `dataset`.
Returns:
bool: True if the file should be uploaded via LFS, False otherwise.
"""
hit_lfs_suffix = True
if isinstance(file_path_or_obj, (str, Path)):
file_path_or_obj = Path(file_path_or_obj)
if not file_path_or_obj.exists():
raise ValueError(f'File {file_path_or_obj} does not exist')
if repo_type == REPO_TYPE_MODEL:
if file_path_or_obj.suffix not in MODEL_LFS_SUFFIX:
hit_lfs_suffix = False
elif repo_type == REPO_TYPE_DATASET:
if file_path_or_obj.suffix not in DATASET_LFS_SUFFIX:
hit_lfs_suffix = False
else:
raise ValueError(f'Invalid repo type: {repo_type}, supported repos: {REPO_TYPE_SUPPORT}')
file_size: int = get_file_size(file_path_or_obj)
return file_size > self.size_threshold_to_enforce_lfs or hit_lfs_suffix
def check_normal_files(self, file_path_list: List[Union[str, Path]], repo_type: str) -> None:
"""
Check a list of normal files to be uploaded.
Args:
file_path_list (List[Union[str, Path]]): The list of file paths to be checked.
repo_type (str): The repo type, either `model` or `dataset`.
Raises:
ValueError: If the total size of normal files exceeds the limit.
Returns: None
"""
normal_file_list = [item for item in file_path_list if not self.is_lfs(item, repo_type)]
total_size = sum([get_file_size(item) for item in normal_file_list])
if total_size > self.normal_file_size_total_limit:
raise ValueError(f'Total size of non-lfs files {total_size / (1024 * 1024)}MB '
f'and exceeds limit: {self.normal_file_size_total_limit / (1024 * 1024)}MB')
Reference in New Issue View Git Blame Copy Permalink