




import builtins
import sys

from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP


__magic_name__  :  int					=       False
try:
      __magic_name__  :  str					=       _is_package_available("""google.colab""")
except ModuleNotFoundError:
      pass





@input.register
class     SCREAMING_SNAKE_CASE__		:
     def __init__(						self	:		List[str]       ,						__lowerCamelCase	:		str = None       ,						__lowerCamelCase	:		list = []						):



       """simple docstring"""
       lowerCAmelCase__										=      0
       lowerCAmelCase__										=      choices
       lowerCAmelCase__										=      prompt
       if sys.platform == "win32":
         lowerCAmelCase__										=      '''*'''
       else:
         lowerCAmelCase__										=      '''➔ '''
     def        A__      (						self	:		Union[str, Any]       ,						__lowerCamelCase	:		Optional[int]       ,						__lowerCamelCase	:		str = ""						):



       """simple docstring"""
       if sys.platform != "win32":
         writeColor(self.choices[index]       ,						32       ,						__lowerCamelCase						)
       else:
         forceWrite(self.choices[index]       ,						__lowerCamelCase						)
     def        A__      (						self	:		Dict       ,						__lowerCamelCase	:		int						):



       """simple docstring"""
       if index == self.position:
         forceWrite(F""" {self.arrow_char} """						)
         self.write_choice(__lowerCamelCase						)
       else:
         forceWrite(F"""    {self.choices[index]}"""						)
       reset_cursor()
     def        A__      (						self	:		List[str]       ,						__lowerCamelCase	:		Direction       ,						__lowerCamelCase	:		int = 1						):



       """simple docstring"""
       lowerCAmelCase__										=      self.position
       if direction == Direction.DOWN:
         if self.position + 1 >= len(self.choices						):
           return
         self.position += num_spaces
       else:
         if self.position - 1 < 0:
           return
         self.position -= num_spaces
       clear_line()
       self.print_choice(__lowerCamelCase						)
       move_cursor(__lowerCamelCase       ,						direction.name						)
       self.print_choice(self.position						)
     @input.mark(KEYMAP['''up''']						)
     def        A__      (						self	:		Dict						):



       """simple docstring"""
       self.move_direction(Direction.UP						)
     @input.mark(KEYMAP['''down''']						)
     def        A__      (						self	:		Dict						):



       """simple docstring"""
       self.move_direction(Direction.DOWN						)
     @input.mark(KEYMAP['''newline''']						)
     def        A__      (						self	:		List[Any]						):



       """simple docstring"""
       move_cursor(len(self.choices						) - self.position       ,						'''DOWN'''						)
       return self.position
     @input.mark(KEYMAP['''interrupt''']						)
     def        A__      (						self	:		str						):



       """simple docstring"""
       move_cursor(len(self.choices						) - self.position       ,						'''DOWN'''						)
       raise KeyboardInterrupt
     @input.mark_multiple(*[KEYMAP[str(__lowerCamelCase						)] for number in range(10						)]						)
     def        A__      (						self	:		List[str]						):



       """simple docstring"""
       lowerCAmelCase__										=      int(chr(self.current_selection						)						)
       lowerCAmelCase__										=      index - self.position
       if index == self.position:
         return
       if index < len(self.choices						):
         if self.position > index:
           self.move_direction(Direction.UP       ,						-movement						)
         elif self.position < index:
           self.move_direction(Direction.DOWN       ,						__lowerCamelCase						)
         else:
           return
       else:
         return



     def        A__      (						self	:		Dict       ,						__lowerCamelCase	:		int = 0						):



       """simple docstring"""
       if self.prompt:
         linebreak()
         forceWrite(self.prompt       ,						'''\n'''						)
         if in_colab:
           forceWrite('''Please input a choice index (starting from 0), and press enter'''       ,						'''\n'''						)
         else:
           forceWrite('''Please select a choice using the arrow or number keys, and selecting with enter'''       ,						'''\n'''						)
       lowerCAmelCase__										=      default_choice
       for i in range(len(self.choices						)						):
         self.print_choice(__lowerCamelCase						)
         forceWrite('''\n'''						)
       move_cursor(len(self.choices						) - self.position       ,						'''UP'''						)
       with cursor.hide():
         while True:
           if in_colab:
             try:
               lowerCAmelCase__										=      int(builtins.input()						)
             except ValueError:
               lowerCAmelCase__										=      default_choice
           else:
             lowerCAmelCase__										=      self.handle_input()
           if choice is not None:
             reset_cursor()
             for _ in range(len(self.choices						) + 1						):
               move_cursor(1       ,						'''UP'''						)
               clear_line()
             self.write_choice(__lowerCamelCase       ,						'''\n'''						)
             return choice







import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_ta import TaTokenizer
else:
      __magic_name__  :  Dict					=       None


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

__magic_name__  :  Optional[Any]					=       {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

__magic_name__  :  Union[str, Any]					=       {
    """vocab_file""": {
        """t5-small""": """https://huggingface.co/t5-small/resolve/main/spiece.model""",
        """t5-base""": """https://huggingface.co/t5-base/resolve/main/spiece.model""",
        """t5-large""": """https://huggingface.co/t5-large/resolve/main/spiece.model""",
        """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/spiece.model""",
        """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """t5-small""": """https://huggingface.co/t5-small/resolve/main/tokenizer.json""",
        """t5-base""": """https://huggingface.co/t5-base/resolve/main/tokenizer.json""",
        """t5-large""": """https://huggingface.co/t5-large/resolve/main/tokenizer.json""",
        """t5-3b""": """https://huggingface.co/t5-3b/resolve/main/tokenizer.json""",
        """t5-11b""": """https://huggingface.co/t5-11b/resolve/main/tokenizer.json""",
    },
}


# TODO(PVP) - this should be removed in Transformers v5
__magic_name__  :  Tuple					=       {
    """t5-small""": 5_12,
    """t5-base""": 5_12,
    """t5-large""": 5_12,
    """t5-3b""": 5_12,
    """t5-11b""": 5_12,
}





class     SCREAMING_SNAKE_CASE__		(_a			):
     lowercase_ :      Dict				= VOCAB_FILES_NAMES
     lowercase_ :      Any				= PRETRAINED_VOCAB_FILES_MAP
     lowercase_ :      Tuple				= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase_ :      Tuple				= ["input_ids", "attention_mask"]
     lowercase_ :      Any				= TaTokenizer

     lowercase_ :      List[int]				= []
     def __init__(						self	:		Tuple       ,						__lowerCamelCase	:		Tuple=None       ,						__lowerCamelCase	:		str=None       ,						__lowerCamelCase	:		Optional[int]="</s>"       ,						__lowerCamelCase	:		Optional[Any]="<unk>"       ,						__lowerCamelCase	:		int="<pad>"       ,						__lowerCamelCase	:		int=1_00       ,						__lowerCamelCase	:		List[str]=None       ,						**__lowerCamelCase	:		Tuple       ,						):



       """simple docstring"""
       # Add extra_ids to the special token list
       if extra_ids > 0 and additional_special_tokens is None:
         lowerCAmelCase__										=      [F"""<extra_id_{i}>""" for i in range(__lowerCamelCase						)]
       elif extra_ids > 0 and additional_special_tokens is not None:
         # Check that we have the right number of extra special tokens
         lowerCAmelCase__										=      len(set(filter(lambda __lowerCamelCase						: bool('''extra_id_''' in str(__lowerCamelCase						)						)       ,						__lowerCamelCase						)						)						)
         if extra_tokens != extra_ids:
           raise ValueError(
               F"""Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"""
               ''' provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids'''
               ''' tokens'''						)

       super().__init__(
           __lowerCamelCase       ,						tokenizer_file=__lowerCamelCase       ,						eos_token=__lowerCamelCase       ,						unk_token=__lowerCamelCase       ,						pad_token=__lowerCamelCase       ,						extra_ids=__lowerCamelCase       ,						additional_special_tokens=__lowerCamelCase       ,						**__lowerCamelCase       ,						)

       lowerCAmelCase__										=      vocab_file
       lowerCAmelCase__										=      False if not self.vocab_file else True
       lowerCAmelCase__										=      extra_ids
     @staticmethod
     def        A__      (						__lowerCamelCase	:		Dict       ,						__lowerCamelCase	:		List[str]       ,						__lowerCamelCase	:		Any						):



       """simple docstring"""
       if pretrained_model_name_or_path in TaTokenizerFast.max_model_input_sizes:
         lowerCAmelCase__										=      TaTokenizerFast.max_model_input_sizes[pretrained_model_name_or_path]
         if init_max_model_length is not None and init_max_model_length != max_model_length:
           return init_max_model_length
         elif init_max_model_length is None:
           warnings.warn(
               '''This tokenizer was incorrectly instantiated with a model max length of'''
               F""" {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this"""
               ''' behavior is kept to avoid breaking backwards compatibility when padding/encoding with'''
               ''' `truncation is True`.\n- Be aware that you SHOULD NOT rely on'''
               F""" {pretrained_model_name_or_path} automatically truncating your input to"""
               F""" {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences"""
               F""" longer than {deprecated_max_model_length} you can either instantiate this tokenizer with"""
               ''' `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please'''
               ''' instantiate this tokenizer with `model_max_length` set to your preferred value.'''       ,						__lowerCamelCase       ,						)

       return max_model_length
     def        A__      (						self	:		int       ,						__lowerCamelCase	:		str       ,						__lowerCamelCase	:		Optional[str] = None						):



       """simple docstring"""
       if not self.can_save_slow_tokenizer:
         raise ValueError(
             '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
             '''tokenizer.'''						)

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

       if os.path.abspath(self.vocab_file						) != os.path.abspath(__lowerCamelCase						):
         copyfile(self.vocab_file       ,						__lowerCamelCase						)
         logger.info(F"""Copy vocab file to {out_vocab_file}"""						)

       return (out_vocab_file,)
     def        A__      (						self	:		Optional[Any]       ,						__lowerCamelCase	:		List[int]       ,						__lowerCamelCase	:		Optional[List[int]] = None						):



       """simple docstring"""
       lowerCAmelCase__										=      token_ids_a + [self.eos_token_id]
       if token_ids_a is None:
         return self.prefix_tokens + token_ids_a
       else:
         lowerCAmelCase__										=      token_ids_a + [self.eos_token_id]
         return self.prefix_tokens + token_ids_a + token_ids_a
     def        A__      (						self	:		int       ,						__lowerCamelCase	:		List[int]       ,						__lowerCamelCase	:		Optional[List[int]] = None						):



       """simple docstring"""
       lowerCAmelCase__										=      [self.eos_token_id]

       if token_ids_a is None:
         return len(token_ids_a + eos						) * [0]
       return len(token_ids_a + eos + token_ids_a + eos						) * [0]
     def        A__      (						self	:		int						):



       """simple docstring"""
       return list(
           set(filter(lambda __lowerCamelCase						: bool(re.search(r'''<extra_id_\d+>'''       ,						__lowerCamelCase						)						) is not None       ,						self.additional_special_tokens						)						)						)



     def        A__      (						self	:		Dict						):



       """simple docstring"""
       return [self.convert_tokens_to_ids(__lowerCamelCase						) for token in self.get_sentinel_tokens()]

