
'''simple docstring'''



import re
from pathlib import Path
from unittest import TestCase

import pytest




@pytest.mark.integration
class   UpperCAmelCase_					(		_A			):






						'''simple docstring'''






						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												with open(__SCREAMING_SNAKE_CASE   ,       encoding="""utf-8"""				) as input_file:
																		_lowerCAmelCase  						=			re.compile(R"""(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"""				)
																		_lowerCAmelCase  						=			input_file.read()
																		_lowerCAmelCase  						=			regexp.search(__SCREAMING_SNAKE_CASE				)

												return match




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												with open(__SCREAMING_SNAKE_CASE   ,       encoding="""utf-8"""				) as input_file:
																		_lowerCAmelCase  						=			re.compile(R"""#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"""   ,       re.DOTALL				)
																		_lowerCAmelCase  						=			input_file.read()
																		# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
																		_lowerCAmelCase  						=			regexp.finditer(__SCREAMING_SNAKE_CASE				)

												_lowerCAmelCase  						=			[match for match in matches if match is not None and match.group(1				) is not None]
												return matches[0] if matches else None




						def  _lowercase     ( self				):

												"""simple docstring"""



												_lowerCAmelCase  						=			Path("""./datasets"""				)
												_lowerCAmelCase  						=			list(dataset_paths.absolute().glob("""**/*.py"""				)				)

												for dataset in dataset_files:
																		if self._no_encoding_on_file_open(str(__SCREAMING_SNAKE_CASE				)				):
																								raise AssertionError(F'open(...) must use utf-8 encoding in {dataset}'				)




						def  _lowercase     ( self				):

												"""simple docstring"""



												_lowerCAmelCase  						=			Path("""./datasets"""				)
												_lowerCAmelCase  						=			list(dataset_paths.absolute().glob("""**/*.py"""				)				)

												for dataset in dataset_files:
																		if self._no_print_statements(str(__SCREAMING_SNAKE_CASE				)				):
																								raise AssertionError(F'print statement found in {dataset}. Use datasets.logger/logging instead.'				)






'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase    =		logging.get_logger(__name__)

_lowercase    =		{
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}




class   UpperCAmelCase_					(		_SCREAMING_SNAKE_CASE			):






						'''simple docstring'''






						_lowercase		:				List[Any]									=       '''convbert'''




						def __init__( self   ,       _lowercase=30_522   ,       _lowercase=768   ,       _lowercase=12   ,       _lowercase=12   ,       _lowercase=3_072   ,       _lowercase="gelu"   ,       _lowercase=0.1   ,       _lowercase=0.1   ,       _lowercase=512   ,       _lowercase=2   ,       _lowercase=0.02   ,       _lowercase=1e-12   ,       _lowercase=1   ,       _lowercase=0   ,       _lowercase=2   ,       _lowercase=768   ,       _lowercase=2   ,       _lowercase=9   ,       _lowercase=1   ,       _lowercase=None   ,       **_lowercase   ,       ):

												"""simple docstring"""



												super().__init__(
												    pad_token_id=_lowercase   ,       bos_token_id=_lowercase   ,       eos_token_id=_lowercase   ,       **_lowercase   ,       )

												_lowerCAmelCase  						=			vocab_size
												_lowerCAmelCase  						=			hidden_size
												_lowerCAmelCase  						=			num_hidden_layers
												_lowerCAmelCase  						=			num_attention_heads
												_lowerCAmelCase  						=			intermediate_size
												_lowerCAmelCase  						=			hidden_act
												_lowerCAmelCase  						=			hidden_dropout_prob
												_lowerCAmelCase  						=			attention_probs_dropout_prob
												_lowerCAmelCase  						=			max_position_embeddings
												_lowerCAmelCase  						=			type_vocab_size
												_lowerCAmelCase  						=			initializer_range
												_lowerCAmelCase  						=			layer_norm_eps
												_lowerCAmelCase  						=			embedding_size
												_lowerCAmelCase  						=			head_ratio
												_lowerCAmelCase  						=			conv_kernel_size
												_lowerCAmelCase  						=			num_groups
												_lowerCAmelCase  						=			classifier_dropout






class   UpperCAmelCase_					(		_SCREAMING_SNAKE_CASE			):






						'''simple docstring'''






						@property
						def  _lowercase     ( self				):

												"""simple docstring"""



												if self.task == "multiple-choice":
																		_lowerCAmelCase  						=			{0: """batch""", 1: """choice""", 2: """sequence"""}
												else:
																		_lowerCAmelCase  						=			{0: """batch""", 1: """sequence"""}
												return OrderedDict(
												    [
												        ("""input_ids""", dynamic_axis),
												        ("""attention_mask""", dynamic_axis),
												        ("""token_type_ids""", dynamic_axis),
												    ]				)
