





'''simple docstring'''




from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
  from ..models.auto import AutoTokenizer







class   A_	:




 def      lowercase	(					self       :    str	,			snake_case_       :    int    ):
      raise NotImplementedError()




 def      lowercase	(					self       :    Any    ):
      raise NotImplementedError()







class   A_	(  lowerCAmelCase_			):




 def __init__(					self       :    str	,			snake_case_       :    "AutoTokenizer"	,			snake_case_       :    bool = False	,			**snake_case_       :    Tuple    ):
      _UpperCAmelCase     							=   tokenizer
      _UpperCAmelCase     							=   skip_prompt
      _UpperCAmelCase     							=   decode_kwargs

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




 def      lowercase	(					self       :    Tuple	,			snake_case_       :    List[str]    ):
      if len(value.shape    ) > 1 and value.shape[0] > 1:
           raise ValueError("TextStreamer only supports batch size 1"    )
      elif len(value.shape    ) > 1:
           _UpperCAmelCase     							=   value[0]

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

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

      # After the symbol for a new line, we flush the cache.
      if text.endswith("\n"    ):
           _UpperCAmelCase     							=   text[self.print_len :]
           _UpperCAmelCase     							=   []
           _UpperCAmelCase     							=   0
      # If the last token is a CJK character, we print the characters.
      elif len(snake_case_    ) > 0 and self._is_chinese_char(ord(text[-1]    )    ):
           _UpperCAmelCase     							=   text[self.print_len :]
           self.print_len += len(snake_case_    )
      # 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:
           _UpperCAmelCase     							=   text[self.print_len : text.rfind(" "    ) + 1]
           self.print_len += len(snake_case_    )

      self.on_finalized_text(snake_case_    )




 def      lowercase	(					self       :    Optional[int]    ):
      # Flush the cache, if it exists
      if len(self.token_cache    ) > 0:
           _UpperCAmelCase     							=   self.tokenizer.decode(self.token_cache	,			**self.decode_kwargs    )
           _UpperCAmelCase     							=   text[self.print_len :]
           _UpperCAmelCase     							=   []
           _UpperCAmelCase     							=   0
      else:
           _UpperCAmelCase     							=   ""

      _UpperCAmelCase     							=   True
      self.on_finalized_text(snake_case_	,			stream_end=snake_case_    )




 def      lowercase	(					self       :    Any	,			snake_case_       :    str	,			snake_case_       :    bool = False    ):
      print(snake_case_	,			flush=snake_case_	,			end="" if not stream_end else None    )




 def      lowercase	(					self       :    Optional[Any]	,			snake_case_       :    Tuple    ):
      # This defines a "chinese character" as anything in the CJK Unicode block:
      #   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
      #
      # Note that the CJK Unicode block is NOT all Japanese and Korean characters,
      # despite its name. The modern Korean Hangul alphabet is a different block,
      # as is Japanese Hiragana and Katakana. Those alphabets are used to write
      # space-separated words, so they are not treated specially and handled
      # like the all of the other languages.
      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_	(  lowerCAmelCase_			):




 def __init__(					self       :    List[Any]	,			snake_case_       :    "AutoTokenizer"	,			snake_case_       :    bool = False	,			snake_case_       :    Optional[float] = None	,			**snake_case_       :    Union[str, Any]    ):
      super().__init__(snake_case_	,			snake_case_	,			**snake_case_    )
      _UpperCAmelCase     							=   Queue()
      _UpperCAmelCase     							=   None
      _UpperCAmelCase     							=   timeout




 def      lowercase	(					self       :    Tuple	,			snake_case_       :    str	,			snake_case_       :    bool = False    ):
      self.text_queue.put(snake_case_	,			timeout=self.timeout    )
      if stream_end:
           self.text_queue.put(self.stop_signal	,			timeout=self.timeout    )




 def __iter__(					self       :    str    ):
      return self




 def      lowercase	(					self       :    Any    ):
      _UpperCAmelCase     							=   self.text_queue.get(timeout=self.timeout    )
      if value == self.stop_signal:
           raise StopIteration()
      else:
           return value











'''simple docstring'''




import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
    "kwargs, expected"			,     [
        ({"num_shards": 0, "max_num_jobs": 1}, []),
        ({"num_shards": 10, "max_num_jobs": 1}, [range(10       )]),
        ({"num_shards": 10, "max_num_jobs": 10}, [range(__lowercase			,     i + 1       ) for i in range(10       )]),
        ({"num_shards": 1, "max_num_jobs": 10}, [range(1       )]),
        ({"num_shards": 10, "max_num_jobs": 3}, [range(0			,     4       ), range(4			,     7       ), range(7			,     10       )]),
        ({"num_shards": 3, "max_num_jobs": 10}, [range(0			,     1       ), range(1			,     2       ), range(2			,     3       )]),
    ]			,     )
def 	UpperCAmelCase_							(					__lowercase							:      int			,     __lowercase							:      Dict       )		->       List[Any]:


     '''simple docstring'''



     _UpperCAmelCase     							=   _distribute_shards(**__lowercase       )
     assert out == expected
@pytest.mark.parametrize(
    "gen_kwargs, max_num_jobs, expected"			,     [
        ({"foo": 0}, 10, [{"foo": 0}]),
        ({"shards": [0, 1, 2, 3]}, 1, [{"shards": [0, 1, 2, 3]}]),
        ({"shards": [0, 1, 2, 3]}, 4, [{"shards": [0]}, {"shards": [1]}, {"shards": [2]}, {"shards": [3]}]),
        ({"shards": [0, 1]}, 4, [{"shards": [0]}, {"shards": [1]}]),
        ({"shards": [0, 1, 2, 3]}, 2, [{"shards": [0, 1]}, {"shards": [2, 3]}]),
    ]			,     )
def 	UpperCAmelCase_							(					__lowercase							:      Dict			,     __lowercase							:      Optional[Any]			,     __lowercase							:      int       )		->       str:


     '''simple docstring'''



     _UpperCAmelCase     							=   _split_gen_kwargs(__lowercase			,     __lowercase       )
     assert out == expected






@pytest.mark.parametrize(
    "gen_kwargs, expected"			,     [
        ({"foo": 0}, 1),
        ({"shards": [0]}, 1),
        ({"shards": [0, 1, 2, 3]}, 4),
        ({"shards": [0, 1, 2, 3], "foo": 0}, 4),
        ({"shards": [0, 1, 2, 3], "other": (0, 1)}, 4),
        ({"shards": [0, 1, 2, 3], "shards2": [0, 1]}, RuntimeError),
    ]			,     )
def 	UpperCAmelCase_							(					__lowercase							:      Optional[Any]			,     __lowercase							:      List[Any]       )		->       List[Any]:


     '''simple docstring'''



     if expected is RuntimeError:
          with pytest.raises(__lowercase       ):
               _number_of_shards_in_gen_kwargs(__lowercase       )
     else:
          _UpperCAmelCase     							=   _number_of_shards_in_gen_kwargs(__lowercase       )
          assert out == expected




