





'''simple docstring'''





import json

import requests

from .fetch_github_info import AUTHENTICATED_USER_ENDPOINT, fetch_github_info


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Optional[Any] )      ->       Union[str, Any]:




		'''simple docstring'''


		class 			__lowerCAmelCase				:


			'''simple docstring'''





			def __init__(	self:	Union[str, Any],				lowerCamelCase_:	Dict ):
					assert isinstance(lowerCamelCase_,				(bytes, str) )
					lowercase__				:			str            =		content





			def       snake_case__(	self:	List[str] ):
					return json.loads(self.content )

		def mock_response(*_lowercase    :   int      ,						**_lowercase    :   Optional[int] ):
				assert args[0] == AUTHENTICATED_USER_ENDPOINT
				assert "Authorization" in kwargs["headers"]
				assert kwargs["headers"]["Authorization"].startswith('token ' )
				assert "Accept" in kwargs["headers"]
				return FakeResponse(B'{"login":"test","id":1}' )

		monkeypatch.setattr(_lowercase      ,						'get'      ,						_lowercase )
		lowercase__				:			Optional[int]            =		fetch_github_info('token' )
		assert result["login"] == "test"
		assert result["id"] == 1









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCamelCase:  Dict   =   {
    """configuration_deberta_v2""": ["""DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DebertaV2Config""", """DebertaV2OnnxConfig"""],
    """tokenization_deberta_v2""": ["""DebertaV2Tokenizer"""],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  List[Any]   =   ["""DebertaV2TokenizerFast"""]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  str   =   [
			    """TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """TFDebertaV2ForMaskedLM""",
			    """TFDebertaV2ForQuestionAnswering""",
			    """TFDebertaV2ForSequenceClassification""",
			    """TFDebertaV2ForTokenClassification""",
			    """TFDebertaV2Model""",
			    """TFDebertaV2PreTrainedModel""",
			]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__UpperCamelCase:  Tuple   =   [
			    """DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """DebertaV2ForMaskedLM""",
			    """DebertaV2ForMultipleChoice""",
			    """DebertaV2ForQuestionAnswering""",
			    """DebertaV2ForSequenceClassification""",
			    """DebertaV2ForTokenClassification""",
			    """DebertaV2Model""",
			    """DebertaV2PreTrainedModel""",
			]


if TYPE_CHECKING:
			from .configuration_deberta_va import (
			    DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    DebertaVaConfig,
			    DebertaVaOnnxConfig,
			)
			from .tokenization_deberta_va import DebertaVaTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_deberta_va import (
						    TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFDebertaVaForMaskedLM,
						    TFDebertaVaForQuestionAnswering,
						    TFDebertaVaForSequenceClassification,
						    TFDebertaVaForTokenClassification,
						    TFDebertaVaModel,
						    TFDebertaVaPreTrainedModel,
						)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_deberta_va import (
						    DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    DebertaVaForMaskedLM,
						    DebertaVaForMultipleChoice,
						    DebertaVaForQuestionAnswering,
						    DebertaVaForSequenceClassification,
						    DebertaVaForTokenClassification,
						    DebertaVaModel,
						    DebertaVaPreTrainedModel,
						)

else:
			import sys

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


