Files
modelscope/modelscope/hub/api.py

1004 lines
42 KiB
Python

# Copyright (c) Alibaba, Inc. and its affiliates.
# yapf: disable
import datetime
import functools
import os
import pickle
import platform
import re
import shutil
import tempfile
import uuid
from collections import defaultdict
from http import HTTPStatus
from http.cookiejar import CookieJar
from os.path import expanduser
from typing import Dict, List, Optional, Tuple, Union
import pandas as pd
import requests
from requests import Session
from requests.adapters import HTTPAdapter, Retry
from modelscope.hub.constants import (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_CREDENTIALS_PATH,
MODELSCOPE_CLOUD_ENVIRONMENT,
MODELSCOPE_CLOUD_USERNAME,
ONE_YEAR_SECONDS,
REQUESTS_API_HTTP_METHOD, Licenses,
ModelVisibility)
from modelscope.hub.errors import (InvalidParameter, NotExistError,
NotLoginException, NoValidRevisionError,
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.repository import Repository
from modelscope.utils.constant import (DEFAULT_DATASET_REVISION,
DEFAULT_MODEL_REVISION,
DEFAULT_REPOSITORY_REVISION,
MASTER_MODEL_BRANCH, META_FILES_FORMAT,
DatasetFormations, DatasetMetaFormats,
DatasetVisibilityMap, DownloadChannel,
DownloadMode, ModelFile,
VirgoDatasetConfig)
from modelscope.utils.logger import get_logger
from .utils.utils import (get_endpoint, get_release_datetime,
model_id_to_group_owner_name)
logger = get_logger()
class HubApi:
"""Model hub api interface.
"""
def __init__(self, endpoint: Optional[str] = None):
"""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=2,
read=2,
connect=2,
backoff_factor=1,
status_forcelist=(500, 502, 503, 504),
)
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=API_HTTP_CLIENT_TIMEOUT))
def login(
self,
access_token: str,
) -> tuple():
"""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.
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.
"""
path = f'{self.endpoint}/api/v1/login'
r = self.session.post(
path, json={'AccessToken': access_token}, 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] = '') -> str:
"""Create model repo at ModelScope Hub.
Args:
model_id (str): The model id
visibility (int, optional): visibility of the model(1-private, 5-public), default 5.
license (str, optional): license of the model, default none.
chinese_name (str, optional): chinese name of the model.
original_model_id (str, optional): the base model id which this model is trained from
Returns:
Name of the model created
Raises:
InvalidParameter: If model_id is invalid.
ValueError: If not login.
Note:
model_id = {owner}/{name}
"""
if model_id is None:
raise InvalidParameter('model_id is required!')
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise ValueError('Token does not exist, please login first.')
path = f'{self.endpoint}/api/v1/models'
owner_or_group, name = model_id_to_group_owner_name(model_id)
body = {
'Path': owner_or_group,
'Name': name,
'ChineseName': chinese_name,
'Visibility': visibility, # server check
'License': license,
'OriginalModelId': original_model_id,
'TrainId': os.environ.get('MODELSCOPE_TRAIN_ID', ''),
}
r = self.session.post(
path, json=body, cookies=cookies, headers=self.headers)
handle_http_post_error(r, path, body)
raise_on_error(r.json())
model_repo_url = f'{get_endpoint()}/{model_id}'
return model_repo_url
def delete_model(self, model_id: str):
"""Delete model_id from ModelScope.
Args:
model_id (str): The model id.
Raises:
ValueError: If not login.
Note:
model_id = {owner}/{name}
"""
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise ValueError('Token does not exist, please login first.')
path = f'{self.endpoint}/api/v1/models/{model_id}'
r = self.session.delete(path, cookies=cookies, headers=self.headers)
raise_for_http_status(r)
raise_on_error(r.json())
def get_model_url(self, model_id: str):
return f'{self.endpoint}/api/v1/models/{model_id}.git'
def get_model(
self,
model_id: str,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
) -> str:
"""Get model information at ModelScope
Args:
model_id (str): The model id.
revision (str optional): revision of model.
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 revision:
path = f'{self.endpoint}/api/v1/models/{owner_or_group}/{name}?Revision={revision}'
else:
path = f'{self.endpoint}/api/v1/models/{owner_or_group}/{name}'
r = self.session.get(path, cookies=cookies, 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 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):
"""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.
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
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):
raise ValueError(f'{model_dir} must contain a configuration.json.')
cookies = ModelScopeConfig.get_cookies()
if cookies is None:
raise NotLoginException('Must login before upload!')
files_to_save = os.listdir(model_dir)
if ignore_file_pattern is None:
ignore_file_pattern = []
if isinstance(ignore_file_pattern, str):
ignore_file_pattern = [ignore_file_pattern]
try:
self.get_model(model_id=model_id)
except Exception:
if visibility is None or license is None:
raise InvalidParameter(
'visibility and license cannot be empty if want to create new repo'
)
logger.info('Create 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 = tempfile.mkdtemp()
git_wrapper = GitCommandWrapper()
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('Create 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)
repo.push(
commit_message=commit_message,
local_branch=revision,
remote_branch=revision)
if tag is not None:
repo.tag_and_push(tag, tag)
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) -> 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
Raises:
RequestError: The request error.
Returns:
dict: {"models": "list of models", "TotalCount": total_number_of_models_in_owner_or_group}
"""
cookies = ModelScopeConfig.get_cookies()
path = f'{self.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.headers)
handle_http_response(r, logger, cookies, 'list_model')
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:
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
"""
cookies = self._check_cookie(use_cookies)
if cutoff_timestamp is None:
cutoff_timestamp = get_release_datetime()
path = f'{self.endpoint}/api/v1/models/{model_id}/revisions?EndTime=%s' % cutoff_timestamp
r = self.session.get(path, cookies=cookies, 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
tags = [x['Revision'] for x in info['RevisionMap']['Tags']
] if info['RevisionMap']['Tags'] else []
return tags
def get_valid_revision(self,
model_id: str,
revision=None,
cookies: Optional[CookieJar] = None):
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)
if release_timestamp > current_timestamp + ONE_YEAR_SECONDS:
branches, tags = self.get_model_branches_and_tags(
model_id, use_cookies=False if cookies is None else cookies)
if revision is None:
revision = MASTER_MODEL_BRANCH
logger.info(
'Model revision not specified, use default: %s in development mode'
% revision)
if revision not in branches and revision not in tags:
raise NotExistError('The model: %s has no revision : %s .' % (model_id, revision))
logger.info('Development mode use revision: %s' % revision)
else:
if revision is None: # user not specified revision, use latest revision before release time
revisions = self.list_model_revisions(
model_id,
cutoff_timestamp=release_timestamp,
use_cookies=False if cookies is None else cookies)
if len(revisions) == 0:
raise NoValidRevisionError(
'The model: %s has no valid revision!' % model_id)
# tags (revisions) returned from backend are guaranteed to be ordered by create-time
# we shall obtain the latest revision created earlier than release version of this branch
revision = revisions[0]
logger.info(
'Model revision not specified, use the latest revision: %s'
% revision)
else:
# use user-specified revision
revisions = self.list_model_revisions(
model_id,
cutoff_timestamp=current_timestamp,
use_cookies=False if cookies is None else cookies)
if revision not in revisions:
raise NotExistError('The model: %s has no revision: %s !' %
(model_id, revision))
logger.info('Use user-specified model revision: %s' % revision)
return revision
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
"""
cookies = self._check_cookie(use_cookies)
path = f'{self.endpoint}/api/v1/models/{model_id}/revisions'
r = self.session.get(path, cookies=cookies, headers=self.headers)
handle_http_response(r, logger, cookies, model_id)
d = r.json()
raise_on_error(d)
info = d[API_RESPONSE_FIELD_DATA]
branches = [x['Revision'] for x in info['RevisionMap']['Branches']
] if info['RevisionMap']['Branches'] else []
tags = [x['Revision'] for x in info['RevisionMap']['Tags']
] if info['RevisionMap']['Tags'] else []
return branches, tags
def get_model_files(self,
model_id: str,
revision: Optional[str] = DEFAULT_MODEL_REVISION,
root: Optional[str] = None,
recursive: Optional[str] = False,
use_cookies: Union[bool, CookieJar] = False,
headers: Optional[dict] = {}) -> 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[str], 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
Returns:
List[dict]: Model file list.
"""
if revision:
path = '%s/api/v1/models/%s/repo/files?Revision=%s&Recursive=%s' % (
self.endpoint, model_id, revision, recursive)
else:
path = '%s/api/v1/models/%s/repo/files?Recursive=%s' % (
self.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
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 = []
for file in d[API_RESPONSE_FIELD_DATA]['Files']:
if file['Name'] == '.gitignore' or file['Name'] == '.gitattributes':
continue
files.append(file)
return files
def list_datasets(self):
path = f'{self.endpoint}/api/v1/datasets'
params = {}
r = self.session.get(path, params=params, 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 get_dataset_id_and_type(self, dataset_name: str, namespace: str):
""" Get the dataset id and type. """
datahub_url = f'{self.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)
dataset_id = resp['Data']['Id']
dataset_type = resp['Data']['Type']
return dataset_id, dataset_type
def get_dataset_meta_file_list(self, dataset_name: str, namespace: str, dataset_id: str, revision: str):
""" Get the meta file-list of the dataset. """
datahub_url = f'{self.endpoint}/api/v1/datasets/{dataset_id}/repo/tree?Revision={revision}'
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(datahub_url, cookies=cookies, headers=self.headers)
resp = r.json()
datahub_raise_on_error(datahub_url, resp)
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):
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)
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'{self.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
import json
from tqdm import tqdm
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)
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):
if file_name and os.path.splitext(file_name)[-1] in META_FILES_FORMAT:
file_name = f'{self.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):
datahub_url = f'{self.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):
datahub_url = f'{self.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.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.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):
datahub_url = f'{self.endpoint}/api/v1/datasets/{namespace}/{dataset_name}'
cookies = ModelScopeConfig.get_cookies()
r = self.session.get(url=datahub_url, cookies=cookies, headers=self.headers)
resp = r.json()
# get visibility of the dataset
raise_on_error(resp)
data = resp['Data']
visibility = DatasetVisibilityMap.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.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):
url = f'{self.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) -> str:
if not object_name or not dataset_name or not namespace or not revision:
raise ValueError('Args cannot be empty!')
url = f'{self.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) -> str:
if not object_name or not dataset_name or not namespace or not revision:
raise ValueError('Args cannot be empty!')
url = f'{self.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)
return resp['Data']
def dataset_download_statistics(self, dataset_name: str, namespace: str, use_streaming: bool) -> None:
is_ci_test = os.getenv('CI_TEST') == 'True'
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'{self.endpoint}/api/v1/datasets/{namespace}/{dataset_name}/download/increase'
download_count_resp = self.session.post(download_count_url, cookies=cookies, 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'{self.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.headers)
download_uv_resp = download_uv_resp.json()
raise_on_error(download_uv_resp)
except Exception as e:
logger.error(e)
class ModelScopeConfig:
path_credential = expanduser(DEFAULT_CREDENTIALS_PATH)
COOKIES_FILE_NAME = 'cookies'
GIT_TOKEN_FILE_NAME = 'git_token'
USER_INFO_FILE_NAME = 'user'
USER_SESSION_ID_FILE_NAME = 'session'
@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.is_expired():
logger.warning(
'Authentication has expired, '
'please re-login if you need to access private models or datasets.')
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