
'''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    =		{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    """bert-large-uncased""": """https://huggingface.co/bert-large-uncased/resolve/main/config.json""",
    """bert-base-cased""": """https://huggingface.co/bert-base-cased/resolve/main/config.json""",
    """bert-large-cased""": """https://huggingface.co/bert-large-cased/resolve/main/config.json""",
    """bert-base-multilingual-uncased""": """https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json""",
    """bert-base-multilingual-cased""": """https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json""",
    """bert-base-chinese""": """https://huggingface.co/bert-base-chinese/resolve/main/config.json""",
    """bert-base-german-cased""": """https://huggingface.co/bert-base-german-cased/resolve/main/config.json""",
    """bert-large-uncased-whole-word-masking""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-uncased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-base-cased-finetuned-mrpc""": """https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json""",
    """bert-base-german-dbmdz-cased""": """https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json""",
    """bert-base-german-dbmdz-uncased""": """https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese""": """https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-cased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-uncased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json"""
    ),
    """wietsedv/bert-base-dutch-cased""": """https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json""",
    # See all BERT models at https://huggingface.co/models?filter=bert
}




class   UpperCAmelCase_					(		__A			):






						'''simple docstring'''






						_lowercase		:				Union[str, Any]									=       'bert'




						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=0   ,       _lowercase="absolute"   ,       _lowercase=True   ,       _lowercase=None   ,       **_lowercase   ,       ):

												"""simple docstring"""



												super().__init__(pad_token_id=__lowercase   ,       **__lowercase				)

												_lowerCAmelCase  						=			vocab_size
												_lowerCAmelCase  						=			hidden_size
												_lowerCAmelCase  						=			num_hidden_layers
												_lowerCAmelCase  						=			num_attention_heads
												_lowerCAmelCase  						=			hidden_act
												_lowerCAmelCase  						=			intermediate_size
												_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  						=			position_embedding_type
												_lowerCAmelCase  						=			use_cache
												_lowerCAmelCase  						=			classifier_dropout






class   UpperCAmelCase_					(		__A			):






						'''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),
												    ]				)


'''simple docstring'''



from __future__ import annotations




class   UpperCAmelCase_					:






						'''simple docstring'''






						def __init__( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			order

												# a_{0} ... a_{k}
												_lowerCAmelCase  						=			[1.0] + [0.0] * order
												# b_{0} ... b_{k}
												_lowerCAmelCase  						=			[1.0] + [0.0] * order

												# x[n-1] ... x[n-k]
												_lowerCAmelCase  						=			[0.0] * self.order
												# y[n-1] ... y[n-k]
												_lowerCAmelCase  						=			[0.0] * self.order




						def  _lowercase     ( self   ,       _lowercase   ,       _lowercase				):

												"""simple docstring"""



												if len(_lowercase				) < self.order:
																		_lowerCAmelCase  						=			[1.0, *a_coeffs]

												if len(_lowercase				) != self.order + 1:
																		_lowerCAmelCase  						=			(
																		    F'Expected a_coeffs to have {self.order + 1} elements '
																		    F'for {self.order}-order filter, got {len(_lowercase				)}'
																		)
																		raise ValueError(_lowercase				)

												if len(_lowercase				) != self.order + 1:
																		_lowerCAmelCase  						=			(
																		    F'Expected b_coeffs to have {self.order + 1} elements '
																		    F'for {self.order}-order filter, got {len(_lowercase				)}'
																		)
																		raise ValueError(_lowercase				)

												_lowerCAmelCase  						=			a_coeffs
												_lowerCAmelCase  						=			b_coeffs




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			0.0

												# Start at index 1 and do index 0 at the end.
												for i in range(1   ,       self.order + 1				):
																		result += (
																		    self.b_coeffs[i] * self.input_history[i - 1]
																		    - self.a_coeffs[i] * self.output_history[i - 1]
																		)

												_lowerCAmelCase  						=			(result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

												_lowerCAmelCase  						=			self.input_history[:-1]
												_lowerCAmelCase  						=			self.output_history[:-1]

												_lowerCAmelCase  						=			sample
												_lowerCAmelCase  						=			result

												return result
