


"""simple docstring"""


import time
from contextlib import contextmanager
from pathlib import Path

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


_snake_case          =							"__DUMMY_TRANSFORMERS_USER__"
_snake_case          =							"Dummy User"
_snake_case          =							"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"

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



@pytest.fixture
def   snake_case						(				_a:     Union[str, Any]							)->		Tuple:
      '''simple docstring'''


      monkeypatch.setattr(
          'huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE'		,   _a							)



@pytest.fixture
def   snake_case						(				_a:     List[Any]							)->		Any:
      '''simple docstring'''


      monkeypatch.setattr('datasets.config.HF_ENDPOINT'		,   _a							)
      monkeypatch.setattr('datasets.config.HUB_DATASETS_URL'		,   _a							)



@pytest.fixture
def   snake_case						(				_a:     Optional[Any]							)->		List[Any]:
      '''simple docstring'''


      monkeypatch.setattr('huggingface_hub.hf_api.HfFolder.path_token'		,   _a							)



@pytest.fixture
def   snake_case						(				_a:     List[Any]		,   _a:     List[Any]							)->		List[Any]:
      '''simple docstring'''


      HfFolder.save_token(_a							)
      yield
      HfFolder.delete_token()



@pytest.fixture(scope='session'							)
def   snake_case						(				)->		List[Any]:
      '''simple docstring'''


      return HfApi(endpoint=_a							)



@pytest.fixture(scope='session'							)
def   snake_case						(				_a:     HfApi							)->		Dict:
      '''simple docstring'''


      lowerCamelCase__           =		HfFolder.get_token()
      HfFolder.save_token(_a							)
      yield CI_HUB_USER_TOKEN
      if previous_token is not None:
            HfFolder.save_token(_a							)



@pytest.fixture
def   snake_case						(				_a:     int							)->		Optional[Any]:
      '''simple docstring'''


      def _cleanup_repo(_a:     int							):
            hf_api.delete_repo(_a		,   token=_a		,   repo_type='dataset'							)

      return _cleanup_repo



@pytest.fixture
def   snake_case						(				_a:     Tuple							)->		str:
      '''simple docstring'''


      @contextmanager
      def _temporary_repo(_a:     Any							):
            try:
                  yield repo_id
            finally:
                  cleanup_repo(_a							)

      return _temporary_repo



@pytest.fixture(scope='session'							)
def   snake_case						(				_a:     HfApi		,   _a:     Dict		,   _a:     Optional[int]							)->		Dict:
      '''simple docstring'''


      lowerCamelCase__           =		F'repo_txt_data-{int(time.time() * 10E3							)}'
      lowerCamelCase__           =		F'{CI_HUB_USER}/{repo_name}'
      hf_api.create_repo(_a		,   token=_a		,   repo_type='dataset'		,   private=_a							)
      hf_api.upload_file(
          token=_a		,   path_or_fileobj=str(_a							)		,   path_in_repo='data/text_data.txt'		,   repo_id=_a		,   repo_type='dataset'		,   )
      yield repo_id
      try:
            hf_api.delete_repo(_a		,   token=_a		,   repo_type='dataset'							)
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass



@pytest.fixture()
def   snake_case						(				_a:     Dict		,   _a:     int		,   _a:     Any							)->		Tuple:
      '''simple docstring'''


      return hf_private_dataset_repo_txt_data_



@pytest.fixture(scope='session'							)
def   snake_case						(				_a:     HfApi		,   _a:     Dict		,   _a:     Optional[Any]							)->		str:
      '''simple docstring'''


      lowerCamelCase__           =		F'repo_zipped_txt_data-{int(time.time() * 10E3							)}'
      lowerCamelCase__           =		F'{CI_HUB_USER}/{repo_name}'
      hf_api.create_repo(_a		,   token=_a		,   repo_type='dataset'		,   private=_a							)
      hf_api.upload_file(
          token=_a		,   path_or_fileobj=str(_a							)		,   path_in_repo='data.zip'		,   repo_id=_a		,   repo_type='dataset'		,   )
      yield repo_id
      try:
            hf_api.delete_repo(_a		,   token=_a		,   repo_type='dataset'							)
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass



@pytest.fixture()
def   snake_case						(				_a:     List[Any]		,   _a:     Tuple		,   _a:     Dict							)->		Optional[Any]:
      '''simple docstring'''


      return hf_private_dataset_repo_zipped_txt_data_



@pytest.fixture(scope='session'							)
def   snake_case						(				_a:     HfApi		,   _a:     Optional[Any]		,   _a:     Tuple							)->		int:
      '''simple docstring'''


      lowerCamelCase__           =		F'repo_zipped_img_data-{int(time.time() * 10E3							)}'
      lowerCamelCase__           =		F'{CI_HUB_USER}/{repo_name}'
      hf_api.create_repo(_a		,   token=_a		,   repo_type='dataset'		,   private=_a							)
      hf_api.upload_file(
          token=_a		,   path_or_fileobj=str(_a							)		,   path_in_repo='data.zip'		,   repo_id=_a		,   repo_type='dataset'		,   )
      yield repo_id
      try:
            hf_api.delete_repo(_a		,   token=_a		,   repo_type='dataset'							)
      except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
            pass






@pytest.fixture()
def   snake_case						(				_a:     Optional[Any]		,   _a:     Optional[Any]		,   _a:     List[str]							)->		str:
      '''simple docstring'''


      return hf_private_dataset_repo_zipped_img_data_







"""simple docstring"""


from typing import TYPE_CHECKING

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


_snake_case          =							{
    "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:
   _snake_case          =							[
       "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

   _snake_case          =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



