





'''simple docstring'''







import time
from contextlib import contextmanager
from pathlib import Path

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


lowerCAmelCase_					:    Tuple      	=			'__DUMMY_TRANSFORMERS_USER__'
lowerCAmelCase_					:    Dict      	=			'Dummy User'
lowerCAmelCase_					:    Optional[Any]      	=			'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'

lowerCAmelCase_					:    Union[str, Any]      	=			'https://hub-ci.huggingface.co'
lowerCAmelCase_					:    Union[str, Any]      	=			CI_HUB_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
lowerCAmelCase_					:    Optional[int]      	=			CI_HUB_ENDPOINT + '/{repo_id}/resolve/{revision}/{filename}'
lowerCAmelCase_					:    Optional[Any]      	=			Path('~/.huggingface/hub_ci_token').expanduser()






@pytest.fixture
def  _lowerCamelCase				( lowercase						:      Optional[int]						)	->	Optional[Any]:
				monkeypatch.setattr(
				    "huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"    ,							a_						)






@pytest.fixture
def  _lowerCamelCase				( lowercase						:      Union[str, Any]						)	->	Optional[int]:
				monkeypatch.setattr("datasets.config.HF_ENDPOINT"    ,							a_						)
				monkeypatch.setattr("datasets.config.HUB_DATASETS_URL"    ,							a_						)






@pytest.fixture
def  _lowerCamelCase				( lowercase						:      str						)	->	List[str]:
				monkeypatch.setattr("huggingface_hub.hf_api.HfFolder.path_token"    ,							a_						)






@pytest.fixture
def  _lowerCamelCase				( lowercase						:      int    ,							lowercase						:      str						)	->	List[Any]:
				HfFolder.save_token(a_						)
				yield
				HfFolder.delete_token()






@pytest.fixture(scope="session"						)
def  _lowerCamelCase				( )	->	Tuple:
				return HfApi(endpoint=a_						)






@pytest.fixture(scope="session"						)
def  _lowerCamelCase				( lowercase						:      List[str]						)	->	Any:
				_a								= 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  _lowerCamelCase				( lowercase						:      Tuple						)	->	Optional[Any]:
				def _cleanup_repo(lowercase						:      Tuple						):
								hf_api.delete_repo(a_    ,							token=a_    ,							repo_type="dataset"						)

				return _cleanup_repo






@pytest.fixture
def  _lowerCamelCase				( lowercase						:      Any						)	->	Union[str, Any]:
				@contextmanager
				def _temporary_repo(lowercase						:      Any						):
								try:
												yield repo_id
								finally:
												cleanup_repo(a_						)

				return _temporary_repo






@pytest.fixture(scope="session"						)
def  _lowerCamelCase				( lowercase						:      Union[str, Any]    ,							lowercase						:      Dict    ,							lowercase						:      int						)	->	Optional[int]:
				_a								= F'repo_txt_data-{int(time.time() * 1_0E3						)}'
				_a								= 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  _lowerCamelCase				( lowercase						:      Dict    ,							lowercase						:      Optional[Any]    ,							lowercase						:      int						)	->	int:
				return hf_private_dataset_repo_txt_data_






@pytest.fixture(scope="session"						)
def  _lowerCamelCase				( lowercase						:      Dict    ,							lowercase						:      Union[str, Any]    ,							lowercase						:      str						)	->	int:
				_a								= F'repo_zipped_txt_data-{int(time.time() * 1_0E3						)}'
				_a								= 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  _lowerCamelCase				( lowercase						:      Tuple    ,							lowercase						:      Union[str, Any]    ,							lowercase						:      Any						)	->	List[Any]:
				return hf_private_dataset_repo_zipped_txt_data_






@pytest.fixture(scope="session"						)
def  _lowerCamelCase				( lowercase						:      str    ,							lowercase						:      Dict    ,							lowercase						:      List[str]						)	->	Tuple:
				_a								= F'repo_zipped_img_data-{int(time.time() * 1_0E3						)}'
				_a								= 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  _lowerCamelCase				( lowercase						:      Optional[int]    ,							lowercase						:      Dict    ,							lowercase						:      List[str]						)	->	Optional[Any]:
				return hf_private_dataset_repo_zipped_img_data_








from typing import TYPE_CHECKING

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


lowercase  							=					{
    "configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
    "tokenization_tapas": ["TapasTokenizer"],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TapasForMaskedLM",
	    "TapasForQuestionAnswering",
	    "TapasForSequenceClassification",
	    "TapasModel",
	    "TapasPreTrainedModel",
	    "load_tf_weights_in_tapas",
	]
try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFTapasForMaskedLM",
	    "TFTapasForQuestionAnswering",
	    "TFTapasForSequenceClassification",
	    "TFTapasModel",
	    "TFTapasPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
	from .tokenization_tapas import TapasTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tapas import (
		    TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TapasForMaskedLM,
		    TapasForQuestionAnswering,
		    TapasForSequenceClassification,
		    TapasModel,
		    TapasPreTrainedModel,
		    load_tf_weights_in_tapas,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_tapas import (
		    TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTapasForMaskedLM,
		    TFTapasForQuestionAnswering,
		    TFTapasForSequenceClassification,
		    TFTapasModel,
		    TFTapasPreTrainedModel,
		)


else:
	import sys

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





