


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_bart import BartTokenizer


UpperCAmelCase_      : int  					=       logging.get_logger(__name__)


UpperCAmelCase_      : Union[str, Any]  					=       {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all BART models at https://huggingface.co/models?filter=bart
UpperCAmelCase_      : Any  					=       {
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

UpperCAmelCase_      : int  					=       {
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      snake_case__				:     Dict        =						VOCAB_FILES_NAMES
      snake_case__				:     Union[str, Any]        =						PRETRAINED_VOCAB_FILES_MAP
      snake_case__				:     Any        =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      snake_case__				:     Any        =						['''input_ids''', '''attention_mask''']
      snake_case__				:     List[Any]        =						BartTokenizer
      def __init__(       self				:       Union[str, Any]     ,							SCREAMING_SNAKE_CASE__				:       List[str]=None     ,							SCREAMING_SNAKE_CASE__				:       Dict=None     ,							SCREAMING_SNAKE_CASE__				:       Dict=None     ,							SCREAMING_SNAKE_CASE__				:       Dict="replace"     ,							SCREAMING_SNAKE_CASE__				:       List[Any]="<s>"     ,							SCREAMING_SNAKE_CASE__				:       str="</s>"     ,							SCREAMING_SNAKE_CASE__				:       Union[str, Any]="</s>"     ,							SCREAMING_SNAKE_CASE__				:       str="<s>"     ,							SCREAMING_SNAKE_CASE__				:       Optional[int]="<unk>"     ,							SCREAMING_SNAKE_CASE__				:       Dict="<pad>"     ,							SCREAMING_SNAKE_CASE__				:       int="<mask>"     ,							SCREAMING_SNAKE_CASE__				:       List[Any]=False     ,							SCREAMING_SNAKE_CASE__				:       Dict=True     ,							**SCREAMING_SNAKE_CASE__				:       int     ,							)		->			List[Any]:
             super().__init__(
                 SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     ,							tokenizer_file=SCREAMING_SNAKE_CASE__     ,							errors=SCREAMING_SNAKE_CASE__     ,							bos_token=SCREAMING_SNAKE_CASE__     ,							eos_token=SCREAMING_SNAKE_CASE__     ,							sep_token=SCREAMING_SNAKE_CASE__     ,							cls_token=SCREAMING_SNAKE_CASE__     ,							unk_token=SCREAMING_SNAKE_CASE__     ,							pad_token=SCREAMING_SNAKE_CASE__     ,							mask_token=SCREAMING_SNAKE_CASE__     ,							add_prefix_space=SCREAMING_SNAKE_CASE__     ,							trim_offsets=SCREAMING_SNAKE_CASE__     ,							**SCREAMING_SNAKE_CASE__     ,							)

             a_					:		Dict							=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
             if pre_tok_state.get('add_prefix_space'     ,							SCREAMING_SNAKE_CASE__     ) != add_prefix_space:
                    a_					:		Any							=  getattr(SCREAMING_SNAKE_CASE__     ,							pre_tok_state.pop('type'     )     )
                    a_					:		Any							=  add_prefix_space
                    a_					:		Optional[int]							=  pre_tok_class(**SCREAMING_SNAKE_CASE__     )

             a_					:		List[str]							=  add_prefix_space

             # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
             a_					:		int							=  'post_processor'
             a_					:		str							=  getattr(self.backend_tokenizer     ,							SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
             if tokenizer_component_instance:
                    a_					:		Dict							=  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:
                           a_					:		List[str]							=  tuple(state['sep']     )
                    if "cls" in state:
                           a_					:		Dict							=  tuple(state['cls']     )

                    a_					:		List[str]							=  False

                    if state.get('add_prefix_space'     ,							SCREAMING_SNAKE_CASE__     ) != add_prefix_space:
                           a_					:		List[str]							=  add_prefix_space
                           a_					:		str							=  True

                    if state.get('trim_offsets'     ,							SCREAMING_SNAKE_CASE__     ) != trim_offsets:
                           a_					:		Union[str, Any]							=  trim_offsets
                           a_					:		Dict							=  True

                    if changes_to_apply:
                           a_					:		Any							=  getattr(SCREAMING_SNAKE_CASE__     ,							state.pop('type'     )     )
                           a_					:		Tuple							=  component_class(**SCREAMING_SNAKE_CASE__     )
                           setattr(self.backend_tokenizer     ,							SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
      @property
      def        SCREAMING_SNAKE_CASE							(       self				:       List[str]     )		->			str:
             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        SCREAMING_SNAKE_CASE							(       self				:       List[Any]     ,							SCREAMING_SNAKE_CASE__				:       Any     )		->			Tuple:
             a_					:		Tuple							=  AddedToken(SCREAMING_SNAKE_CASE__     ,							lstrip=SCREAMING_SNAKE_CASE__     ,							rstrip=SCREAMING_SNAKE_CASE__     ) if isinstance(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     ) else value
             a_					:		List[Any]							=  value
      def        SCREAMING_SNAKE_CASE							(       self				:       int     ,							*SCREAMING_SNAKE_CASE__				:       Optional[int]     ,							**SCREAMING_SNAKE_CASE__				:       int     )		->			BatchEncoding:
             a_					:		Dict							=  kwargs.get('is_split_into_words'     ,							SCREAMING_SNAKE_CASE__     )

             if is_split_into_words and not self.add_prefix_space:
                    raise ValueError(
                        F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
                        'to use it with pretokenized inputs.'     )

             return super()._batch_encode_plus(*SCREAMING_SNAKE_CASE__     ,							**SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Dict     ,							*SCREAMING_SNAKE_CASE__				:       Dict     ,							**SCREAMING_SNAKE_CASE__				:       Optional[int]     )		->			BatchEncoding:
             a_					:		Union[str, Any]							=  kwargs.get('is_split_into_words'     ,							SCREAMING_SNAKE_CASE__     )

             if is_split_into_words and not self.add_prefix_space:
                    raise ValueError(
                        F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
                        'to use it with pretokenized inputs.'     )

             return super()._encode_plus(*SCREAMING_SNAKE_CASE__     ,							**SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       List[Any]     ,							SCREAMING_SNAKE_CASE__				:       str     ,							SCREAMING_SNAKE_CASE__				:       Optional[str] = None     )		->			Tuple[str]:
             a_					:		List[Any]							=  self._tokenizer.model.save(SCREAMING_SNAKE_CASE__     ,							name=SCREAMING_SNAKE_CASE__     )
             return tuple(SCREAMING_SNAKE_CASE__     )
      def        SCREAMING_SNAKE_CASE							(       self				:       Optional[Any]     ,							SCREAMING_SNAKE_CASE__				:       Optional[int]     ,							SCREAMING_SNAKE_CASE__				:       Union[str, Any]=None     )		->			Union[str, Any]:
             a_					:		Dict							=  [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        SCREAMING_SNAKE_CASE							(       self				:       int     ,							SCREAMING_SNAKE_CASE__				:       List[int]     ,							SCREAMING_SNAKE_CASE__				:       Optional[List[int]] = None     )		->			List[int]:
             a_					:		Optional[int]							=  [self.sep_token_id]
             a_					:		Union[str, Any]							=  [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]






import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


UpperCAmelCase_      : Optional[Any]  					=       logging.get_logger(__name__)

UpperCAmelCase_      : str  					=       'T5Config'







def        SCREAMING_SNAKE_CASE_						(			__A :			jnp.array  ,    __A :			int  ,    __A :			int				)	->		jnp.ndarray:

       """simple docstring"""

       a_					:		Dict							=  jnp.zeros_like(__A				)
       a_					:		Dict							=  shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]				)
       a_					:		str							=  shifted_input_ids.at[:, 0].set(__A				)

       a_					:		int							=  jnp.where(shifted_input_ids == -1_00  ,    __A  ,    __A				)
       return shifted_input_ids
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      snake_case__				:     str        =						'''mt5'''
      snake_case__				:     List[Any]        =						MTaConfig
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      snake_case__				:     str        =						'''mt5'''
      snake_case__				:     List[str]        =						MTaConfig
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      snake_case__				:     Any        =						'''mt5'''
      snake_case__				:     Union[str, Any]        =						MTaConfig


