




from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
 from ..models.auto import AutoTokenizer







class 						A:



 '''simple docstring'''


 def        a__				(       self      :						Optional[Any]		,							A_      :						Dict						)     ->			List[Any]:

       """simple docstring"""






       raise NotImplementedError()





 def        a__				(       self      :						Tuple						)     ->			str:

       """simple docstring"""






       raise NotImplementedError()







class 						A(		__lowercase     ):



 '''simple docstring'''


 def __init__(       self      :						List[Any]		,							A_      :						List[Any]		,							A_      :						List[Any] = False		,							**A_      :						Optional[Any]						)     ->			Dict:

       """simple docstring"""






       lowerCamelCase_	  =					tokenizer
       lowerCamelCase_	  =					skip_prompt
       lowerCamelCase_	  =					decode_kwargs

       # variables used in the streaming process
       lowerCamelCase_	  =					[]
       lowerCamelCase_	  =					0
       lowerCamelCase_	  =					True

 def        a__				(       self      :						Tuple		,							A_      :						Union[str, Any]						)     ->			int:

       """simple docstring"""






       if len(value.shape						) > 1 and value.shape[0] > 1:
             raise ValueError('TextStreamer only supports batch size 1'						)
       elif len(value.shape						) > 1:
             lowerCamelCase_	  =					value[0]

       if self.skip_prompt and self.next_tokens_are_prompt:
             lowerCamelCase_	  =					False
             return

       # Add the new token to the cache and decodes the entire thing.
       self.token_cache.extend(value.tolist()						)
       lowerCamelCase_	  =					self.tokenizer.decode(self.token_cache		,							**self.decode_kwargs						)

       # After the symbol for a new line, we flush the cache.
       if text.endswith('\n'						):
             lowerCamelCase_	  =					text[self.print_len :]
             lowerCamelCase_	  =					[]
             lowerCamelCase_	  =					0
       # If the last token is a CJK character, we print the characters.
       elif len(__A						) > 0 and self._is_chinese_char(ord(text[-1]						)						):
             lowerCamelCase_	  =					text[self.print_len :]
             self.print_len += len(__A						)
       # Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
       # which may change with the subsequent token -- there are probably smarter ways to do this!)
       else:
             lowerCamelCase_	  =					text[self.print_len : text.rfind(' '						) + 1]
             self.print_len += len(__A						)

       self.on_finalized_text(__A						)

 def        a__				(       self      :						Any						)     ->			int:

       """simple docstring"""






       if len(self.token_cache						) > 0:
             lowerCamelCase_	  =					self.tokenizer.decode(self.token_cache		,							**self.decode_kwargs						)
             lowerCamelCase_	  =					text[self.print_len :]
             lowerCamelCase_	  =					[]
             lowerCamelCase_	  =					0
       else:
             lowerCamelCase_	  =					''

       lowerCamelCase_	  =					True
       self.on_finalized_text(__A		,							stream_end=__A						)

 def        a__				(       self      :						Dict		,							A_      :						List[Any]		,							A_      :						Dict = False						)     ->			Tuple:

       """simple docstring"""






       print(__A		,							flush=__A		,							end='' if not stream_end else None						)





 def        a__				(       self      :						str		,							A_      :						str						)     ->			str:

       """simple docstring"""






       if (
           (cp >= 0X4E_00 and cp <= 0X9F_FF)
           or (cp >= 0X34_00 and cp <= 0X4D_BF)  #
           or (cp >= 0X2_00_00 and cp <= 0X2_A6_DF)  #
           or (cp >= 0X2_A7_00 and cp <= 0X2_B7_3F)  #
           or (cp >= 0X2_B7_40 and cp <= 0X2_B8_1F)  #
           or (cp >= 0X2_B8_20 and cp <= 0X2_CE_AF)  #
           or (cp >= 0XF9_00 and cp <= 0XFA_FF)
           or (cp >= 0X2_F8_00 and cp <= 0X2_FA_1F)  #
       ):  #
             return True

       return False







class 						A(		__lowercase     ):



 '''simple docstring'''


 def __init__(       self      :						int		,							A_      :						Dict		,							A_      :						Any = False		,							A_      :						Optional[int] = None		,							**A_      :						str						)     ->			List[Any]:

       """simple docstring"""






       super().__init__(__A		,							__A		,							**__A						)
       lowerCamelCase_	  =					Queue()
       lowerCamelCase_	  =					None
       lowerCamelCase_	  =					timeout

 def        a__				(       self      :						Dict		,							A_      :						int		,							A_      :						Optional[Any] = False						)     ->			Any:

       """simple docstring"""






       self.text_queue.put(__A		,							timeout=self.timeout						)
       if stream_end:
             self.text_queue.put(self.stop_signal		,							timeout=self.timeout						)

 def __iter__(       self      :						Optional[Any]						)     ->			Optional[int]:

       """simple docstring"""






       return self





 def        a__				(       self      :						Tuple						)     ->			List[str]:

       """simple docstring"""






       lowerCamelCase_	  =					self.text_queue.get(timeout=self.timeout						)
       if value == self.stop_signal:
             raise StopIteration()
       else:
             return value









from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate







@dataclass(frozen=UpperCamelCase     )
class 						A(		UpperCamelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		field(default='''language-modeling'''							,   metadata={'''include_in_asdict_even_if_is_default''': True}     )

 UpperCamelCase		     =		Features({'''text''': Value('''string'''     )}     )
 UpperCamelCase		     =		Features({}     )
 UpperCamelCase		     =		"text"

 @property
 def        a__				(       self      :						List[Any]						)     ->			Dict[str, str]:

       """simple docstring"""






       return {self.text_column: "text"}



