
'''simple docstring'''

import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format






class  A  :
	snake_case__   :Dict   =  None





	def 				__SCREAMING_SNAKE_CASE	(       self      :							Optional[Any]				):


				"""simple docstring"""

				lowerCAmelCase__										=				self.feature_extraction_class(**self.feat_extract_dict				)
				lowerCAmelCase__										=				json.loads(feat_extract.to_json_string()				)
				for key, value in self.feat_extract_dict.items():
							self.assertEqual(obj[key]   ,				__magic_name__				)





	def 				__SCREAMING_SNAKE_CASE	(       self      :							Any				):


				"""simple docstring"""

				lowerCAmelCase__										=				self.feature_extraction_class(**self.feat_extract_dict				)

				with tempfile.TemporaryDirectory() as tmpdirname:
							lowerCAmelCase__										=				os.path.join(__magic_name__   ,				"feat_extract.json"				)
							feat_extract_first.to_json_file(__magic_name__				)
							lowerCAmelCase__										=				self.feature_extraction_class.from_json_file(__magic_name__				)

				self.assertEqual(feat_extract_second.to_dict()   ,				feat_extract_first.to_dict()				)





	def 				__SCREAMING_SNAKE_CASE	(       self      :							List[str]				):


				"""simple docstring"""

				lowerCAmelCase__										=				self.feature_extraction_class(**self.feat_extract_dict				)

				with tempfile.TemporaryDirectory() as tmpdirname:
							lowerCAmelCase__										=				feat_extract_first.save_pretrained(__magic_name__				)[0]
							check_json_file_has_correct_format(__magic_name__				)
							lowerCAmelCase__										=				self.feature_extraction_class.from_pretrained(__magic_name__				)

				self.assertEqual(feat_extract_second.to_dict()   ,				feat_extract_first.to_dict()				)







	def 				__SCREAMING_SNAKE_CASE	(       self      :							str				):


				"""simple docstring"""

				lowerCAmelCase__										=				self.feature_extraction_class()
				self.assertIsNotNone(__magic_name__				)










'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase		     =  {
    '''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase		     =  [
							    '''ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''ErnieForCausalLM''',
							    '''ErnieForMaskedLM''',
							    '''ErnieForMultipleChoice''',
							    '''ErnieForNextSentencePrediction''',
							    '''ErnieForPreTraining''',
							    '''ErnieForQuestionAnswering''',
							    '''ErnieForSequenceClassification''',
							    '''ErnieForTokenClassification''',
							    '''ErnieModel''',
							    '''ErniePreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_ernie import (
														    ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ErnieForCausalLM,
														    ErnieForMaskedLM,
														    ErnieForMultipleChoice,
														    ErnieForNextSentencePrediction,
														    ErnieForPreTraining,
														    ErnieForQuestionAnswering,
														    ErnieForSequenceClassification,
														    ErnieForTokenClassification,
														    ErnieModel,
														    ErniePreTrainedModel,
														)

else:
							import sys

							__lowerCAmelCase		     =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




