
"""simple docstring"""


import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


_lowercase				 =					'''__DUMMY_TRANSFORMERS_USER__'''
_lowercase				 =					'''Dummy User'''
_lowercase				 =					'''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'''

_lowercase				 =					'''https://hub-ci.huggingface.co'''
_lowercase				 =					CI_HUB_ENDPOINT + '''/datasets/{repo_id}/resolve/{revision}/{path}'''
_lowercase				 =					CI_HUB_ENDPOINT + '''/{repo_id}/resolve/{revision}/{filename}'''
_lowercase				 =					Path('''~/.huggingface/hub_ci_token''').expanduser()






@pytest.fixture
def    _snake_case					(		snake_case__ :  List[Any]  ):
	monkeypatch.setattr(
	    'huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE'						,   snake_case__  )






@pytest.fixture
def    _snake_case					(		snake_case__ :  int  ):
	monkeypatch.setattr('datasets.config.HF_ENDPOINT'						,   snake_case__  )
	monkeypatch.setattr('datasets.config.HUB_DATASETS_URL'						,   snake_case__  )






@pytest.fixture
def    _snake_case					(		snake_case__ :  List[Any]  ):
	monkeypatch.setattr('huggingface_hub.hf_api.HfFolder.path_token'						,   snake_case__  )






@pytest.fixture
def    _snake_case					(		snake_case__ :  Tuple						,   snake_case__ :  Any  ):
	HfFolder.save_token(snake_case__  )
	yield
	HfFolder.delete_token()






@pytest.fixture(scope='session'  )
def    _snake_case					(		):
	return HfApi(endpoint=snake_case__  )






@pytest.fixture(scope='session'  )
def    _snake_case					(		snake_case__ :  HfApi  ):
	A     = HfFolder.get_token()
	HfFolder.save_token(snake_case__  )
	yield CI_HUB_USER_TOKEN
	if previous_token is not None:
		HfFolder.save_token(snake_case__  )






@pytest.fixture
def    _snake_case					(		snake_case__ :  Optional[int]  ):
	def _cleanup_repo(snake_case__ :  Dict  ):
		hf_api.delete_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'  )

	return _cleanup_repo






@pytest.fixture
def    _snake_case					(		snake_case__ :  Optional[Any]  ):
	@contextmanager
	def _temporary_repo(snake_case__ :  Dict  ):
		try:
			yield repo_id
		finally:
			cleanup_repo(snake_case__  )

	return _temporary_repo






@pytest.fixture(scope='session'  )
def    _snake_case					(		snake_case__ :  HfApi						,   snake_case__ :  Union[str, Any]						,   snake_case__ :  List[Any]  ):
	A     = F'repo_txt_data-{int(time.time() * 10e3  )}'
	A     = F'{CI_HUB_USER}/{repo_name}'
	hf_api.create_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'						,   private=snake_case__  )
	hf_api.upload_file(
	    token=snake_case__						,   path_or_fileobj=str(snake_case__  )						,   path_in_repo='data/text_data.txt'						,   repo_id=snake_case__						,   repo_type='dataset'						,   )
	yield repo_id
	try:
		hf_api.delete_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'  )
	except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
		pass






@pytest.fixture()
def    _snake_case					(		snake_case__ :  str						,   snake_case__ :  Dict						,   snake_case__ :  Dict  ):
	return hf_private_dataset_repo_txt_data_






@pytest.fixture(scope='session'  )
def    _snake_case					(		snake_case__ :  HfApi						,   snake_case__ :  Any						,   snake_case__ :  str  ):
	A     = F'repo_zipped_txt_data-{int(time.time() * 10e3  )}'
	A     = F'{CI_HUB_USER}/{repo_name}'
	hf_api.create_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'						,   private=snake_case__  )
	hf_api.upload_file(
	    token=snake_case__						,   path_or_fileobj=str(snake_case__  )						,   path_in_repo='data.zip'						,   repo_id=snake_case__						,   repo_type='dataset'						,   )
	yield repo_id
	try:
		hf_api.delete_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'  )
	except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
		pass






@pytest.fixture()
def    _snake_case					(		snake_case__ :  Union[str, Any]						,   snake_case__ :  str						,   snake_case__ :  Dict  ):
	return hf_private_dataset_repo_zipped_txt_data_






@pytest.fixture(scope='session'  )
def    _snake_case					(		snake_case__ :  HfApi						,   snake_case__ :  Union[str, Any]						,   snake_case__ :  Optional[int]  ):
	A     = F'repo_zipped_img_data-{int(time.time() * 10e3  )}'
	A     = F'{CI_HUB_USER}/{repo_name}'
	hf_api.create_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'						,   private=snake_case__  )
	hf_api.upload_file(
	    token=snake_case__						,   path_or_fileobj=str(snake_case__  )						,   path_in_repo='data.zip'						,   repo_id=snake_case__						,   repo_type='dataset'						,   )
	yield repo_id
	try:
		hf_api.delete_repo(snake_case__						,   token=snake_case__						,   repo_type='dataset'  )
	except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
		pass






@pytest.fixture()
def    _snake_case					(		snake_case__ :  Optional[int]						,   snake_case__ :  int						,   snake_case__ :  Union[str, Any]  ):
	return hf_private_dataset_repo_zipped_img_data_


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_UpperCAmelCase						:  Tuple									=			{
    """configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
    """tokenization_m2m_100""": ["""M2M100Tokenizer"""],
}


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase						:  Tuple									=			[
					    """M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """M2M100ForConditionalGeneration""",
					    """M2M100Model""",
					    """M2M100PreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
					from .tokenization_mam_aaa import MaMaaaTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mam_aaa import (
										    M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaMaaaForConditionalGeneration,
										    MaMaaaModel,
										    MaMaaaPreTrainedModel,
										)


else:
					import sys

					_UpperCAmelCase						:  Any									=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




