

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


lowerCAmelCase__             =		logging.get_logger(__name__)

lowerCAmelCase__             =		{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

lowerCAmelCase__             =		{
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
    """tokenizer_file""": {
        """allenai/longformer-base-4096""": (
            """https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
    },
}

lowerCAmelCase__             =		{
    """allenai/longformer-base-4096""": 4_0_9_6,
    """allenai/longformer-large-4096""": 4_0_9_6,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 4_0_9_6,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 4_0_9_6,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 4_0_9_6,
}







class 						lowercase     (					_a				):


		"""simple docstring"""




		a__       							=	VOCAB_FILES_NAMES
		a__       							=	PRETRAINED_VOCAB_FILES_MAP
		a__       							=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		a__       							=	["input_ids", "attention_mask"]
		a__       							=	LongformerTokenizer


		def __init__(					self						,							__snake_case=None						,							__snake_case=None						,							__snake_case=None						,							__snake_case="replace"						,							__snake_case="<s>"						,							__snake_case="</s>"						,							__snake_case="</s>"						,							__snake_case="<s>"						,							__snake_case="<unk>"						,							__snake_case="<pad>"						,							__snake_case="<mask>"						,							__snake_case=False						,							__snake_case=True						,							**__snake_case						,							):
			super().__init__(
			    _A						,							_A						,							tokenizer_file=_A						,							errors=_A						,							bos_token=_A						,							eos_token=_A						,							sep_token=_A						,							cls_token=_A						,							unk_token=_A						,							pad_token=_A						,							mask_token=_A						,							add_prefix_space=_A						,							trim_offsets=_A						,							**_A						,							)

			_UpperCamelCase :		Union[str, Any]								=    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
			if pre_tok_state.get('add_prefix_space'						,							_A) != add_prefix_space:
				_UpperCamelCase :		Tuple								=    getattr(_A						,							pre_tok_state.pop('type'))
				_UpperCamelCase :		Optional[Any]								=    add_prefix_space
				_UpperCamelCase :		Optional[Any]								=    pre_tok_class(**_A)

			_UpperCamelCase :		Optional[int]								=    add_prefix_space

			_UpperCamelCase :		Optional[Any]								=    'post_processor'
			_UpperCamelCase :		Union[str, Any]								=    getattr(self.backend_tokenizer						,							_A						,							_A)
			if tokenizer_component_instance:
				_UpperCamelCase :		Union[str, Any]								=    json.loads(tokenizer_component_instance.__getstate__())

				# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
				if "sep" in state:
					_UpperCamelCase :		Tuple								=    tuple(state['sep'])
				if "cls" in state:
					_UpperCamelCase :		Tuple								=    tuple(state['cls'])

				_UpperCamelCase :		Any								=    False

				if state.get('add_prefix_space'						,							_A) != add_prefix_space:
					_UpperCamelCase :		Union[str, Any]								=    add_prefix_space
					_UpperCamelCase :		Tuple								=    True

				if state.get('trim_offsets'						,							_A) != trim_offsets:
					_UpperCamelCase :		Tuple								=    trim_offsets
					_UpperCamelCase :		int								=    True

				if changes_to_apply:
					_UpperCamelCase :		List[Any]								=    getattr(_A						,							state.pop('type'))
					_UpperCamelCase :		Optional[int]								=    component_class(**_A)
					setattr(self.backend_tokenizer						,							_A						,							_A)


		@property
		def 		A__       (					self):
			if self._mask_token is None:
				if self.verbose:
					logger.error('Using mask_token, but it is not set yet.')
				return None
			return str(self._mask_token)


		@mask_token.setter
		def 		A__       (					self						,							__snake_case):
			_UpperCamelCase :		int								=    AddedToken(_A						,							lstrip=_A						,							rstrip=_A) if isinstance(_A						,							_A) else value
			_UpperCamelCase :		Any								=    value


		def 		A__       (					self						,							*__snake_case						,							**__snake_case):
			_UpperCamelCase :		Tuple								=    kwargs.get('is_split_into_words'						,							_A)
			assert self.add_prefix_space or not is_split_into_words, (
			    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
			    "to use it with pretokenized inputs."
			)

			return super()._batch_encode_plus(*_A						,							**_A)


		def 		A__       (					self						,							*__snake_case						,							**__snake_case):
			_UpperCamelCase :		Optional[Any]								=    kwargs.get('is_split_into_words'						,							_A)

			assert self.add_prefix_space or not is_split_into_words, (
			    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
			    "to use it with pretokenized inputs."
			)

			return super()._encode_plus(*_A						,							**_A)


		def 		A__       (					self						,							__snake_case						,							__snake_case = None):
			_UpperCamelCase :		Union[str, Any]								=    self._tokenizer.model.save(_A						,							name=_A)
			return tuple(_A)


		def 		A__       (					self						,							__snake_case						,							__snake_case=None):
			_UpperCamelCase :		Optional[Any]								=    [self.bos_token_id] + token_ids_a + [self.eos_token_id]
			if token_ids_a is None:
				return output

			return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






		def 		A__       (					self						,							__snake_case						,							__snake_case = None):
			_UpperCamelCase :		List[Any]								=    [self.sep_token_id]
			_UpperCamelCase :		Tuple								=    [self.cls_token_id]

			if token_ids_a is None:
				return len(cls + token_ids_a + sep) * [0]
			return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]







from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase   					=  logging.get_logger(__name__)

lowerCamelCase   					=  {
    '''microsoft/prophetnet-large-uncased''': (
        '''https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'''
    ),
}





class      snake_case_      (					_a				):


							"""simple docstring"""





							__UpperCAmelCase      ="""prophetnet"""
							__UpperCAmelCase      =["""past_key_values"""]
							__UpperCAmelCase      ={
							    """num_attention_heads""": """num_encoder_attention_heads""",
							}




							def __init__(			self       ,    _A = 0.1       ,    _A = "gelu"       ,    _A = 3_0_5_2_2       ,    _A = 1_0_2_4       ,    _A = 4_0_9_6       ,    _A = 1_2       ,    _A = 1_6       ,    _A = 4_0_9_6       ,    _A = 1_2       ,    _A = 1_6       ,    _A = 0.1       ,    _A = 0.1       ,    _A = 5_1_2       ,    _A = 0.02       ,    _A = True       ,    _A = True       ,    _A = 0       ,    _A = 2       ,    _A = 3_2       ,    _A = 1_2_8       ,    _A = False       ,    _A = 0.0       ,    _A = True       ,    _A = 0       ,    _A = 1       ,    _A = 2       ,    **_A       ,    ):
												__lowerCAmelCase       =				vocab_size
												__lowerCAmelCase       =				hidden_size
												__lowerCAmelCase       =				encoder_ffn_dim
												__lowerCAmelCase       =				num_encoder_layers
												__lowerCAmelCase       =				num_encoder_attention_heads
												__lowerCAmelCase       =				decoder_ffn_dim
												__lowerCAmelCase       =				num_decoder_layers
												__lowerCAmelCase       =				num_decoder_attention_heads
												__lowerCAmelCase       =				max_position_embeddings
												__lowerCAmelCase       =				init_std  # Normal(0, this parameter)
												__lowerCAmelCase       =				activation_function

												# parameters for prophetnet
												__lowerCAmelCase       =				ngram
												__lowerCAmelCase       =				num_buckets
												__lowerCAmelCase       =				relative_max_distance
												__lowerCAmelCase       =				disable_ngram_loss
												__lowerCAmelCase       =				eps

												# 3 Types of Dropout
												__lowerCAmelCase       =				attention_dropout
												__lowerCAmelCase       =				activation_dropout
												__lowerCAmelCase       =				dropout

												__lowerCAmelCase       =				use_cache

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




							@property
							def 							A__	(			self				):
												return self.num_encoder_layers + self.num_decoder_layers




							@num_hidden_layers.setter
							def 							A__	(			self       ,    _A				):
												raise NotImplementedError(
												    'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
												    ' `num_decoder_layers`.'				)






