


from collections import OrderedDict
from typing import Any, Mapping, Optional

from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import TensorType, is_torch_available, logging


UpperCAmelCase_	:     str							     =	logging.get_logger(__name__)

UpperCAmelCase_	:     Tuple							     =	{
    'google/bigbird-pegasus-large-arxiv': (
        'https://huggingface.co/google/bigbird-pegasus-large-arxiv/resolve/main/config.json'
    ),
    'google/bigbird-pegasus-large-pubmed': (
        'https://huggingface.co/google/bigbird-pegasus-large-pubmed/resolve/main/config.json'
    ),
    'google/bigbird-pegasus-large-bigpatent': (
        'https://huggingface.co/google/bigbird-pegasus-large-bigpatent/resolve/main/config.json'
    ),
    # See all BigBirdPegasus models at https://huggingface.co/models?filter=bigbird_pegasus
}





class 					lowercase__						(		_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						"""bigbird_pegasus"""
							A_							:   Optional[int]   			=						["""past_key_values"""]
							A_							:   int   			=						{
							    """num_attention_heads""": """encoder_attention_heads""",
							    """hidden_size""": """d_model""",
							    """attention_probs_dropout_prob""": """attention_dropout""",
							}






							def __init__(					self					,      __snake_case=9_6103					,      __snake_case=4096					,      __snake_case=16					,      __snake_case=4096					,      __snake_case=16					,      __snake_case=16					,      __snake_case=4096					,      __snake_case=16					,      __snake_case=0.0					,      __snake_case=0.0					,      __snake_case=True					,      __snake_case=True					,      __snake_case="gelu_new"					,      __snake_case=1024					,      __snake_case=0.1					,      __snake_case=0.0					,      __snake_case=0.0					,      __snake_case=0.02					,      __snake_case=2					,      __snake_case=0.0					,      __snake_case=True					,      __snake_case=0					,      __snake_case=2					,      __snake_case=1					,      __snake_case="block_sparse"					,      __snake_case=64					,      __snake_case=3					,      __snake_case=False					,      **__snake_case					,      ):
											_SCREAMING_SNAKE_CASE				: Any  	=   vocab_size
											_SCREAMING_SNAKE_CASE				: Any  	=   max_position_embeddings
											_SCREAMING_SNAKE_CASE				: Optional[int]  	=   d_model
											_SCREAMING_SNAKE_CASE				: List[Any]  	=   encoder_ffn_dim
											_SCREAMING_SNAKE_CASE				: Dict  	=   encoder_layers
											_SCREAMING_SNAKE_CASE				: Optional[int]  	=   encoder_attention_heads
											_SCREAMING_SNAKE_CASE				: str  	=   decoder_ffn_dim
											_SCREAMING_SNAKE_CASE				: List[Any]  	=   decoder_layers
											_SCREAMING_SNAKE_CASE				: Any  	=   decoder_attention_heads
											_SCREAMING_SNAKE_CASE				: Tuple  	=   dropout
											_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   attention_dropout
											_SCREAMING_SNAKE_CASE				: List[Any]  	=   activation_dropout
											_SCREAMING_SNAKE_CASE				: Tuple  	=   activation_function
											_SCREAMING_SNAKE_CASE				: str  	=   init_std
											_SCREAMING_SNAKE_CASE				: Tuple  	=   encoder_layerdrop
											_SCREAMING_SNAKE_CASE				: List[Any]  	=   decoder_layerdrop
											_SCREAMING_SNAKE_CASE				: Any  	=   classifier_dropout
											_SCREAMING_SNAKE_CASE				: str  	=   use_cache
											_SCREAMING_SNAKE_CASE				: Any  	=   encoder_layers
											_SCREAMING_SNAKE_CASE				: int  	=   scale_embedding  # scale factor will be sqrt(d_model) if True

											# extra config
											_SCREAMING_SNAKE_CASE				: Dict  	=   attention_type
											_SCREAMING_SNAKE_CASE				: Optional[int]  	=   block_size
											_SCREAMING_SNAKE_CASE				: List[str]  	=   num_random_blocks
											_SCREAMING_SNAKE_CASE				: Tuple  	=   use_bias

											super().__init__(
											    pad_token_id=__snake_case					,      bos_token_id=__snake_case					,      eos_token_id=__snake_case					,      is_encoder_decoder=__snake_case					,      decoder_start_token_id=__snake_case					,      **__snake_case					,      )





class 					lowercase__						(		_snake_case      ):





							'''simple docstring'''


							@property
							def UpperCAmelCase_			(					self						):
											if self.task in ["default", "seq2seq-lm"]:
															_SCREAMING_SNAKE_CASE				: str  	=   OrderedDict(
															    [
															        ("""input_ids""", {0: """batch""", 1: """encoder_sequence"""}),
															        ("""attention_mask""", {0: """batch""", 1: """encoder_sequence"""}),
															    ]						)

															if self.use_past:
																			_SCREAMING_SNAKE_CASE				: int  	=   {0: """batch"""}
																			_SCREAMING_SNAKE_CASE				: Tuple  	=   {0: """batch""", 1: """past_decoder_sequence + sequence"""}
															else:
																			_SCREAMING_SNAKE_CASE				: int  	=   {0: """batch""", 1: """decoder_sequence"""}
																			_SCREAMING_SNAKE_CASE				: str  	=   {0: """batch""", 1: """decoder_sequence"""}

															if self.use_past:
																			self.fill_with_past_key_values_(__snake_case					,      direction="""inputs"""						)
											elif self.task == "causal-lm":
															# TODO: figure this case out.
															_SCREAMING_SNAKE_CASE				: int  	=   OrderedDict(
															    [
															        ("""input_ids""", {0: """batch""", 1: """encoder_sequence"""}),
															        ("""attention_mask""", {0: """batch""", 1: """encoder_sequence"""}),
															    ]						)
															if self.use_past:
																			_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   self.num_layers
																			for i in range(__snake_case						):
																							_SCREAMING_SNAKE_CASE				: Dict  	=   {0: """batch""", 2: """past_sequence + sequence"""}
																							_SCREAMING_SNAKE_CASE				: str  	=   {0: """batch""", 2: """past_sequence + sequence"""}
											else:
															_SCREAMING_SNAKE_CASE				: Any  	=   OrderedDict(
															    [
															        ("""input_ids""", {0: """batch""", 1: """encoder_sequence"""}),
															        ("""attention_mask""", {0: """batch""", 1: """encoder_sequence"""}),
															        ("""decoder_input_ids""", {0: """batch""", 1: """decoder_sequence"""}),
															        ("""decoder_attention_mask""", {0: """batch""", 1: """decoder_sequence"""}),
															    ]						)

											return common_inputs






							@property
							def UpperCAmelCase_			(					self						):
											if self.task in ["default", "seq2seq-lm"]:
															_SCREAMING_SNAKE_CASE				: str  	=   super().outputs
											else:
															_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   super(__snake_case					,      self						).outputs
															if self.use_past:
																			_SCREAMING_SNAKE_CASE				: Optional[int]  	=   self.num_layers
																			for i in range(__snake_case						):
																							_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   {0: """batch""", 2: """past_sequence + sequence"""}
																							_SCREAMING_SNAKE_CASE				: str  	=   {0: """batch""", 2: """past_sequence + sequence"""}
											return common_outputs






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case = -1					,      __snake_case = -1					,      __snake_case = False					,      __snake_case = None					,      ):
											_SCREAMING_SNAKE_CASE				: List[str]  	=   self._generate_dummy_inputs_for_sequence_classification_and_question_answering(
											    __snake_case					,      __snake_case					,      __snake_case					,      __snake_case					,      __snake_case						)

											# Generate decoder inputs
											_SCREAMING_SNAKE_CASE				: Tuple  	=   seq_length if not self.use_past else 1
											_SCREAMING_SNAKE_CASE				: Dict  	=   self._generate_dummy_inputs_for_sequence_classification_and_question_answering(
											    __snake_case					,      __snake_case					,      __snake_case					,      __snake_case					,      __snake_case						)
											_SCREAMING_SNAKE_CASE				: Dict  	=   {f"""decoder_{name}""": tensor for name, tensor in decoder_inputs.items()}
											_SCREAMING_SNAKE_CASE				: int  	=   dict(**__snake_case					,      **__snake_case						)

											if self.use_past:
															if not is_torch_available():
																			raise ValueError("""Cannot generate dummy past_keys inputs without PyTorch installed."""						)
															else:
																			import torch
															_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   common_inputs["""input_ids"""].shape
															_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   common_inputs["""decoder_input_ids"""].shape[1]
															_SCREAMING_SNAKE_CASE				: Any  	=   self.num_attention_heads
															_SCREAMING_SNAKE_CASE				: Tuple  	=   (
															    batch,
															    num_encoder_attention_heads,
															    encoder_seq_length,
															    self._config.hidden_size // num_encoder_attention_heads,
															)
															_SCREAMING_SNAKE_CASE				: Tuple  	=   decoder_seq_length + 3
															_SCREAMING_SNAKE_CASE				: List[Any]  	=   (
															    batch,
															    num_decoder_attention_heads,
															    decoder_past_length,
															    self._config.hidden_size // num_decoder_attention_heads,
															)

															_SCREAMING_SNAKE_CASE				: List[Any]  	=   torch.cat(
															    [common_inputs["""decoder_attention_mask"""], torch.ones(__snake_case					,      __snake_case						)]					,      dim=1						)

															_SCREAMING_SNAKE_CASE				: Dict  	=   []
															# If the number of encoder and decoder layers are present in the model configuration, both are considered
															_SCREAMING_SNAKE_CASE				: List[str]  	=   self.num_layers
															_SCREAMING_SNAKE_CASE				: Tuple  	=   min(__snake_case					,      __snake_case						)
															_SCREAMING_SNAKE_CASE				: Dict  	=   max(__snake_case					,      __snake_case						) - min_num_layers
															_SCREAMING_SNAKE_CASE				: Tuple  	=   """encoder""" if num_encoder_layers > num_decoder_layers else """decoder"""

															for _ in range(__snake_case						):
																			common_inputs["past_key_values"].append(
																			    (
																			        torch.zeros(__snake_case						),
																			        torch.zeros(__snake_case						),
																			        torch.zeros(__snake_case						),
																			        torch.zeros(__snake_case						),
																			    )						)
															# TODO: test this.
															_SCREAMING_SNAKE_CASE				: List[str]  	=   encoder_shape if remaining_side_name == """encoder""" else decoder_shape
															for _ in range(__snake_case					,      __snake_case						):
																			common_inputs["past_key_values"].append((torch.zeros(__snake_case						), torch.zeros(__snake_case						))						)
											return common_inputs






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case = -1					,      __snake_case = -1					,      __snake_case = False					,      __snake_case = None					,      ):
											_SCREAMING_SNAKE_CASE				: Tuple  	=   self._generate_dummy_inputs_for_sequence_classification_and_question_answering(
											    __snake_case					,      __snake_case					,      __snake_case					,      __snake_case					,      __snake_case						)

											if self.use_past:
															if not is_torch_available():
																			raise ValueError("""Cannot generate dummy past_keys inputs without PyTorch installed."""						)
															else:
																			import torch
															_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   common_inputs["""input_ids"""].shape
															# Not using the same length for past_key_values
															_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   seqlen + 2
															_SCREAMING_SNAKE_CASE				: int  	=   self.num_layers
															_SCREAMING_SNAKE_CASE				: Tuple  	=   self.num_attention_heads
															_SCREAMING_SNAKE_CASE				: Tuple  	=   (
															    batch,
															    num_encoder_attention_heads,
															    past_key_values_length,
															    self._config.hidden_size // num_encoder_attention_heads,
															)

															_SCREAMING_SNAKE_CASE				: Tuple  	=   common_inputs["""attention_mask"""].dtype
															_SCREAMING_SNAKE_CASE				: Optional[int]  	=   torch.cat(
															    [common_inputs["""attention_mask"""], torch.ones(__snake_case					,      __snake_case					,      dtype=__snake_case						)]					,      dim=1						)
															_SCREAMING_SNAKE_CASE				: str  	=   [
															    (torch.zeros(__snake_case						), torch.zeros(__snake_case						)) for _ in range(__snake_case						)
															]
											return common_inputs






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case = -1					,      __snake_case = -1					,      __snake_case = False					,      __snake_case = None					,      ):
											# Copied from OnnxConfig.generate_dummy_inputs
											# Did not use super(OnnxConfigWithPast, self).generate_dummy_inputs for code clarity.
											# If dynamic axis (-1) we forward with a fixed dimension of 2 samples to avoid optimizations made by ONNX
											_SCREAMING_SNAKE_CASE				: Optional[int]  	=   compute_effective_axis_dimension(
											    __snake_case					,      fixed_dimension=OnnxConfig.default_fixed_batch					,      num_token_to_add=0						)

											# If dynamic axis (-1) we forward with a fixed dimension of 8 tokens to avoid optimizations made by ONNX
											_SCREAMING_SNAKE_CASE				: Tuple  	=   tokenizer.num_special_tokens_to_add(__snake_case						)
											_SCREAMING_SNAKE_CASE				: List[str]  	=   compute_effective_axis_dimension(
											    __snake_case					,      fixed_dimension=OnnxConfig.default_fixed_sequence					,      num_token_to_add=__snake_case						)

											# Generate dummy inputs according to compute batch and sequence
											_SCREAMING_SNAKE_CASE				: Tuple  	=   [""" """.join([tokenizer.unk_token]						) * seq_length] * batch_size
											_SCREAMING_SNAKE_CASE				: str  	=   dict(tokenizer(__snake_case					,      return_tensors=__snake_case						)						)
											return common_inputs






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case = -1					,      __snake_case = -1					,      __snake_case = False					,      __snake_case = None					,      ):
											if self.task in ["default", "seq2seq-lm"]:
															_SCREAMING_SNAKE_CASE				: Any  	=   self._generate_dummy_inputs_for_default_and_seqaseq_lm(
															    __snake_case					,      batch_size=__snake_case					,      seq_length=__snake_case					,      is_pair=__snake_case					,      framework=__snake_case						)

											elif self.task == "causal-lm":
															_SCREAMING_SNAKE_CASE				: Optional[Any]  	=   self._generate_dummy_inputs_for_causal_lm(
															    __snake_case					,      batch_size=__snake_case					,      seq_length=__snake_case					,      is_pair=__snake_case					,      framework=__snake_case						)
											else:
															_SCREAMING_SNAKE_CASE				: Dict  	=   self._generate_dummy_inputs_for_sequence_classification_and_question_answering(
															    __snake_case					,      batch_size=__snake_case					,      seq_length=__snake_case					,      is_pair=__snake_case					,      framework=__snake_case						)

											return common_inputs






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case					,      __snake_case					,      __snake_case						):
											if self.task in ["default", "seq2seq-lm"]:
															_SCREAMING_SNAKE_CASE				: Dict  	=   super()._flatten_past_key_values_(__snake_case					,      __snake_case					,      __snake_case					,      __snake_case						)
											else:
															_SCREAMING_SNAKE_CASE				: List[Any]  	=   super(__snake_case					,      self						)._flatten_past_key_values_(
															    __snake_case					,      __snake_case					,      __snake_case					,      __snake_case						)








'''simple docstring'''


from ..utils import DummyObject, requires_backends





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[str]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   str   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Union[str, Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[str]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Tuple   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Tuple   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   str   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Dict   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   str   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   str   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Tuple   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[str]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[str]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   int   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Tuple   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Dict   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[int]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Union[str, Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[str]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Dict   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Tuple   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[str]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Any   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Dict   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Union[str, Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   Optional[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)





class 					lowercase__						(		metaclass=_snake_case      ):





							'''simple docstring'''


							A_							:   List[Any]   			=						["""tokenizers"""]






							def __init__(					self					,      *__snake_case					,      **__snake_case						):
											requires_backends(self					,      ["""tokenizers"""]						)




