



from typing import TYPE_CHECKING

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


__snake_case     :Tuple			       ={
    'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvBertConfig', 'ConvBertOnnxConfig'],
    'tokenization_convbert': ['ConvBertTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__snake_case     :Dict			       =['ConvBertTokenizerFast']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__snake_case     :Optional[int]			       =[
				    'CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'ConvBertForMaskedLM',
				    'ConvBertForMultipleChoice',
				    'ConvBertForQuestionAnswering',
				    'ConvBertForSequenceClassification',
				    'ConvBertForTokenClassification',
				    'ConvBertLayer',
				    'ConvBertModel',
				    'ConvBertPreTrainedModel',
				    'load_tf_weights_in_convbert',
				]


try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__snake_case     :Optional[Any]			       =[
				    'TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'TFConvBertForMaskedLM',
				    'TFConvBertForMultipleChoice',
				    'TFConvBertForQuestionAnswering',
				    'TFConvBertForSequenceClassification',
				    'TFConvBertForTokenClassification',
				    'TFConvBertLayer',
				    'TFConvBertModel',
				    'TFConvBertPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertOnnxConfig
				from .tokenization_convbert import ConvBertTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_convbert_fast import ConvBertTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_convbert import (
								    CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ConvBertForMaskedLM,
								    ConvBertForMultipleChoice,
								    ConvBertForQuestionAnswering,
								    ConvBertForSequenceClassification,
								    ConvBertForTokenClassification,
								    ConvBertLayer,
								    ConvBertModel,
								    ConvBertPreTrainedModel,
								    load_tf_weights_in_convbert,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_convbert import (
								    TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFConvBertForMaskedLM,
								    TFConvBertForMultipleChoice,
								    TFConvBertForQuestionAnswering,
								    TFConvBertForSequenceClassification,
								    TFConvBertForTokenClassification,
								    TFConvBertLayer,
								    TFConvBertModel,
								    TFConvBertPreTrainedModel,
								)


else:
				import sys

				__snake_case     :Dict			       =_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




import argparse
from collections import defaultdict






def  lowerCamelCase_	(      lowerCAmelCase__	:	List[str]			,	lowerCAmelCase__	:	List[str]			,	lowerCAmelCase__	:	Tuple			,	lowerCAmelCase__	:	Optional[int]			,	lowerCAmelCase__	:	List[str]				)       ->							Union[str, Any]:

							'''simple docstring'''






							A      						=    F'''{file}_{class_name}_{test_name}'''
							done_test[_id] += 1

							with open(lowerCAmelCase__			,	'r'				) as f:
														A      						=    f.readlines()

							A      						=    F'''class {class_name}('''
							A      						=    F'''{4 * " "}def {test_name}('''
							A      						=    F'''{8 * " "}{correct_line.split()[0]}'''
							A      						=    F'''{16 * " "}{correct_line.split()[0]}'''
							A      						=    False
							A      						=    False
							A      						=    False
							A      						=    False
							A      						=    0
							A      						=    0

							A      						=    []
							for line in lines:
														if line.startswith(lowerCAmelCase__				):
																					A      						=    True
														elif in_class and line.startswith(lowerCAmelCase__				):
																					A      						=    True
														elif in_class and in_func and (line.startswith(lowerCAmelCase__				) or line.startswith(lowerCAmelCase__				)):
																					A      						=    len(line.split(correct_line.split()[0]				)[0]				)
																					count += 1

																					if count == done_test[_id]:
																												A      						=    True

														if in_class and in_func and in_line:
																					if ")" not in line:
																												continue
																					else:
																												A      						=    True

														if in_class and in_func and in_line and insert_line:
																					new_lines.append(F'''{spaces * " "}{correct_line}'''				)
																					A      						=    A      						=    A      						=    A      						=    False
														else:
																					new_lines.append(lowerCAmelCase__				)

							with open(lowerCAmelCase__			,	'w'				) as f:
														for line in new_lines:
																					f.write(lowerCAmelCase__				)






def  lowerCamelCase_	(      lowerCAmelCase__	:	str			,	lowerCAmelCase__	:	Tuple=None				)       ->							Union[str, Any]:

							'''simple docstring'''






							if fail is not None:
														with open(lowerCAmelCase__			,	'r'				) as f:
																					A      						=    {l.strip() for l in f.readlines()}
							else:
														A      						=    None

							with open(lowerCAmelCase__			,	'r'				) as f:
														A      						=    f.readlines()

							A      						=    defaultdict(lowerCAmelCase__				)
							for line in correct_lines:
														A						,   A						,   A						,   A      						=    line.split(';'				)
														if test_failures is None or "::".join([file, class_name, test_name]				) in test_failures:
																					overwrite_file(lowerCAmelCase__			,	lowerCAmelCase__			,	lowerCAmelCase__			,	lowerCAmelCase__			,	lowerCAmelCase__				)


if __name__ == "__main__":
				__snake_case     :List[Any]			       =argparse.ArgumentParser()
				parser.add_argument('--correct_filename', help='filename of tests with expected result')
				parser.add_argument('--fail_filename', help='filename of test failures', type=str, default=None)
				__snake_case     :Optional[int]			       =parser.parse_args()

				main(args.correct_filename, args.fail_filename)