
'''simple docstring'''



import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


_lowercase          =						logging.get_logger(__name__)


_lowercase          =						{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

# See all LED models at https://huggingface.co/models?filter=LED
_lowercase          =						{
    """vocab_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json""",
    },
}

_lowercase          =						{
    """allenai/led-base-16384""": 16384,
}


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def A ():
						_lowerCAmelCase    		=					(
						    list(range(ord("""!"""						)					,      ord("""~"""						) + 1						)						) + list(range(ord("""¡"""						)					,      ord("""¬"""						) + 1						)						) + list(range(ord("""®"""						)					,      ord("""ÿ"""						) + 1						)						)
						)
						_lowerCAmelCase    		=					bs[:]
						_lowerCAmelCase    		=					0
						for b in range(2**8						):
												if b not in bs:
																		bs.append(__lowerCamelCase						)
																		cs.append(2**8 + n						)
																		n += 1
						_lowerCAmelCase    		=					[chr(__lowerCamelCase						) for n in cs]
						return dict(zip(__lowerCamelCase					,      __lowerCamelCase						)						)


def A (__lowerCamelCase :List[str]						):
						_lowerCAmelCase    		=					set()
						_lowerCAmelCase    		=					word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)						)
												_lowerCAmelCase    		=					char
						return pairs





class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						_lowercase						: Optional[int]										=  VOCAB_FILES_NAMES
						_lowercase						: Union[str, Any]										=  PRETRAINED_VOCAB_FILES_MAP
						_lowercase						: Tuple										=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowercase						: List[str]										=  ['''input_ids''', '''attention_mask''']




						def __init__(   self       ,  _lowercase       ,  _lowercase       ,  _lowercase="replace"       ,  _lowercase="<s>"       ,  _lowercase="</s>"       ,  _lowercase="</s>"       ,  _lowercase="<s>"       ,  _lowercase="<unk>"       ,  _lowercase="<pad>"       ,  _lowercase="<mask>"       ,  _lowercase=False       ,  **_lowercase       ,  ):

												"""simple docstring"""



												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else bos_token
												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else eos_token
												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else sep_token
												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else cls_token
												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else unk_token
												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else pad_token

												# Mask token behave like a normal word, i.e. include the space before it
												_lowerCAmelCase    		=					AddedToken(_lowercase       ,  lstrip=_lowercase       ,  rstrip=_lowercase ) if isinstance(_lowercase       ,  _lowercase ) else mask_token

												super().__init__(
												    errors=_lowercase       ,  bos_token=_lowercase       ,  eos_token=_lowercase       ,  unk_token=_lowercase       ,  sep_token=_lowercase       ,  cls_token=_lowercase       ,  pad_token=_lowercase       ,  mask_token=_lowercase       ,  add_prefix_space=_lowercase       ,  **_lowercase       ,  )

												with open(_lowercase       ,  encoding="""utf-8""" ) as vocab_handle:
																		_lowerCAmelCase    		=					json.load(_lowercase )
												_lowerCAmelCase    		=					{v: k for k, v in self.encoder.items()}
												_lowerCAmelCase    		=					errors  # how to handle errors in decoding
												_lowerCAmelCase    		=					bytes_to_unicode()
												_lowerCAmelCase    		=					{v: k for k, v in self.byte_encoder.items()}
												with open(_lowercase       ,  encoding="""utf-8""" ) as merges_handle:
																		_lowerCAmelCase    		=					merges_handle.read().split("""\n""" )[1:-1]
												_lowerCAmelCase    		=					[tuple(merge.split() ) for merge in bpe_merges]
												_lowerCAmelCase    		=					dict(zip(_lowercase       ,  range(len(_lowercase ) ) ) )
												_lowerCAmelCase    		=					{}
												_lowerCAmelCase    		=					add_prefix_space

												# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
												_lowerCAmelCase    		=					re.compile(R"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""" )




						@property
						# Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
						def    _lowercase      (   self ):

												"""simple docstring"""



												return len(self.encoder )




						def    _lowercase      (   self ):

												"""simple docstring"""



												return dict(self.encoder       ,  **self.added_tokens_encoder )




						def    _lowercase      (   self       ,  _lowercase ):

												"""simple docstring"""



												if token in self.cache:
																		return self.cache[token]
												_lowerCAmelCase    		=					tuple(_lowercase )
												_lowerCAmelCase    		=					get_pairs(_lowercase )

												if not pairs:
																		return token

												while True:
																		_lowerCAmelCase    		=					min(_lowercase       ,  key=lambda _lowercase : self.bpe_ranks.get(_lowercase       ,  float("""inf""" ) ) )
																		if bigram not in self.bpe_ranks:
																								break
																		_lowerCAmelCase		,       _lowerCAmelCase    		=					bigram
																		_lowerCAmelCase    		=					[]
																		_lowerCAmelCase    		=					0
																		while i < len(_lowercase ):
																								try:
																														_lowerCAmelCase    		=					word.index(_lowercase       ,  _lowercase )
																								except ValueError:
																														new_word.extend(word[i:] )
																														break
																								else:
																														new_word.extend(word[i:j] )
																														_lowerCAmelCase    		=					j

																								if word[i] == first and i < len(_lowercase ) - 1 and word[i + 1] == second:
																														new_word.append(first + second )
																														i += 2
																								else:
																														new_word.append(word[i] )
																														i += 1
																		_lowerCAmelCase    		=					tuple(_lowercase )
																		_lowerCAmelCase    		=					new_word
																		if len(_lowercase ) == 1:
																								break
																		else:
																								_lowerCAmelCase    		=					get_pairs(_lowercase )
												_lowerCAmelCase    		=					""" """.join(_lowercase )
												_lowerCAmelCase    		=					word
												return word




						def    _lowercase      (   self       ,  _lowercase ):

												"""simple docstring"""



												_lowerCAmelCase    		=					[]
												for token in re.findall(self.pat       ,  _lowercase ):
																		_lowerCAmelCase    		=					"""""".join(
																		    self.byte_encoder[b] for b in token.encode("""utf-8""" ) )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
																		bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_lowercase ).split(""" """ ) )
												return bpe_tokens




						def    _lowercase      (   self       ,  _lowercase ):

												"""simple docstring"""



												return self.encoder.get(_lowercase       ,  self.encoder.get(self.unk_token ) )




						def    _lowercase      (   self       ,  _lowercase ):

												"""simple docstring"""



												return self.decoder.get(_lowercase )




						def    _lowercase      (   self       ,  _lowercase ):

												"""simple docstring"""



												_lowerCAmelCase    		=					"""""".join(_lowercase )
												_lowerCAmelCase    		=					bytearray([self.byte_decoder[c] for c in text] ).decode("""utf-8"""       ,  errors=self.errors )
												return text




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase = None ):

												"""simple docstring"""



												if not os.path.isdir(_lowercase ):
																		logger.error(F'Vocabulary path ({save_directory}) should be a directory' )
																		return
												_lowerCAmelCase    		=					os.path.join(
												    _lowercase       ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )
												_lowerCAmelCase    		=					os.path.join(
												    _lowercase       ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""] )

												with open(_lowercase       ,  """w"""       ,  encoding="""utf-8""" ) as f:
																		f.write(json.dumps(self.encoder       ,  indent=2       ,  sort_keys=_lowercase       ,  ensure_ascii=_lowercase ) + """\n""" )

												_lowerCAmelCase    		=					0
												with open(_lowercase       ,  """w"""       ,  encoding="""utf-8""" ) as writer:
																		writer.write("""#version: 0.2\n""" )
																		for bpe_tokens, token_index in sorted(self.bpe_ranks.items()       ,  key=lambda _lowercase : kv[1] ):
																								if index != token_index:
																														logger.warning(
																														    F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
																														    """ Please check that the tokenizer is not corrupted!""" )
																														_lowerCAmelCase    		=					token_index
																								writer.write(""" """.join(_lowercase ) + """\n""" )
																								index += 1

												return vocab_file, merge_file




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase = None ):

												"""simple docstring"""



												if token_ids_a is None:
																		return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												_lowerCAmelCase    		=					[self.cls_token_id]
												_lowerCAmelCase    		=					[self.sep_token_id]
												return cls + token_ids_a + sep + sep + token_ids_a + sep




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase = None       ,  _lowercase = False ):

												"""simple docstring"""



												if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=_lowercase       ,  token_ids_a=_lowercase       ,  already_has_special_tokens=_lowercase )

												if token_ids_a is None:
																		return [1] + ([0] * len(_lowercase )) + [1]
												return [1] + ([0] * len(_lowercase )) + [1, 1] + ([0] * len(_lowercase )) + [1]




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase = None ):

												"""simple docstring"""



												_lowerCAmelCase    		=					[self.sep_token_id]
												_lowerCAmelCase    		=					[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]




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase=False       ,  **_lowercase ):

												"""simple docstring"""



												_lowerCAmelCase    		=					kwargs.pop("""add_prefix_space"""       ,  self.add_prefix_space )
												if (is_split_into_words or add_prefix_space) and (len(_lowercase ) > 0 and not text[0].isspace()):
																		_lowerCAmelCase    		=					""" """ + text
												return (text, kwargs)




						def    _lowercase      (   self       ,  _lowercase       ,  _lowercase = None       ,  _lowercase = PaddingStrategy.DO_NOT_PAD       ,  _lowercase = None       ,  _lowercase = None       ,  ):

												"""simple docstring"""



												_lowerCAmelCase    		=					super()._pad(
												    encoded_inputs=_lowercase       ,  max_length=_lowercase       ,  padding_strategy=_lowercase       ,  pad_to_multiple_of=_lowercase       ,  return_attention_mask=_lowercase       ,  )

												# Load from model defaults
												if return_attention_mask is None:
																		_lowerCAmelCase    		=					"""attention_mask""" in self.model_input_names

												if return_attention_mask and "global_attention_mask" in encoded_inputs:
																		_lowerCAmelCase    		=					encoded_inputs[self.model_input_names[0]]
																		# `global_attention_mask` need to have the same length as other (sequential) inputs.
																		_lowerCAmelCase    		=					len(encoded_inputs["""global_attention_mask"""] ) != len(_lowercase )

																		if needs_to_be_padded:
																								_lowerCAmelCase    		=					len(_lowercase ) - len(encoded_inputs["""global_attention_mask"""] )

																								if self.padding_side == "right":
																														# Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
																														_lowerCAmelCase    		=					(
																														    encoded_inputs["""global_attention_mask"""] + [-1] * difference
																														)
																								elif self.padding_side == "left":
																														_lowerCAmelCase    		=					[-1] * difference + encoded_inputs[
																														    """global_attention_mask"""
																														]
																								else:
																														raise ValueError("""Invalid padding strategy:""" + str(self.padding_side ) )

												return encoded_inputs





"""simple docstring"""







from typing import Callable, Optional, Union

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


a_							=    logging.get_logger(__name__)

a_							=    {
    """microsoft/xprophetnet-large-wiki100-cased""": (
        """https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json"""
    ),
}







class 					A_(SCREAMING_SNAKE_CASE_      ):







			"""simple docstring"""



			a_       :			List[Any]												=			"""xlm-prophetnet"""
			a_       :			Any												=			["""past_key_values"""]
			a_       :			Optional[int]												=			{
			    """num_attention_heads""": """num_encoder_attention_heads""",
			}
			def __init__(	self				,   A = 0.1				,   A = "gelu"				,   A = 3_0522				,   A = 1024				,   A = 4096				,   A = 12				,   A = 16				,   A = 4096				,   A = 12				,   A = 16				,   A = 0.1				,   A = 0.1				,   A = 512				,   A = 0.0_2				,   A = True				,   A = True				,   A = 0				,   A = 2				,   A = 32				,   A = 128				,   A = False				,   A = 0.0				,   A = True				,   A = 0				,   A = 1				,   A = 2				,   **A				,   ):
						_lowerCamelCase					:					Dict	       =    vocab_size
						_lowerCamelCase					:					List[Any]	       =    hidden_size
						_lowerCamelCase					:					List[Any]	       =    encoder_ffn_dim
						_lowerCamelCase					:					Any	       =    num_encoder_layers
						_lowerCamelCase					:					Any	       =    num_encoder_attention_heads
						_lowerCamelCase					:					List[str]	       =    decoder_ffn_dim
						_lowerCamelCase					:					Optional[int]	       =    num_decoder_layers
						_lowerCamelCase					:					List[str]	       =    num_decoder_attention_heads
						_lowerCamelCase					:					Optional[Any]	       =    max_position_embeddings
						_lowerCamelCase					:					Optional[Any]	       =    init_std  # Normal(0, this parameter)
						_lowerCamelCase					:					Optional[int]	       =    activation_function

						# parameters for xlmprophetnet
						_lowerCamelCase					:					Any	       =    ngram
						_lowerCamelCase					:					Dict	       =    num_buckets
						_lowerCamelCase					:					Dict	       =    relative_max_distance
						_lowerCamelCase					:					Optional[Any]	       =    disable_ngram_loss
						_lowerCamelCase					:					Union[str, Any]	       =    eps

						# 3 Types of Dropout
						_lowerCamelCase					:					int	       =    attention_dropout
						_lowerCamelCase					:					str	       =    activation_dropout
						_lowerCamelCase					:					Optional[int]	       =    dropout

						_lowerCamelCase					:					List[Any]	       =    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    _lowerCAmelCase		(	self							):
						return self.num_encoder_layers + self.num_decoder_layers

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





