


"""simple docstring"""







import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


lowerCAmelCase__				    =       logging.get_logger(__name__)

lowerCAmelCase__				    =       {'''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase__				    =       {
    '''tokenizer_file''': {
        '''bigscience/tokenizer''': '''https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json''',
        '''bigscience/bloom-560m''': '''https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b1''': '''https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b7''': '''https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json''',
        '''bigscience/bloom-3b''': '''https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json''',
        '''bigscience/bloom-7b1''': '''https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json''',
        '''bigscience/bloom''': '''https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json''',
    },
}


class 				SCREAMING_SNAKE_CASE__    (		lowercase    ):
       """simple docstring"""


       a  :    Any       =VOCAB_FILES_NAMES
       a  :    Optional[int]       =PRETRAINED_VOCAB_FILES_MAP
       a  :    List[str]       =["input_ids", "attention_mask"]
       a  :    str       =None

       def __init__(						self		,					snake_case__=None		,					snake_case__=None		,					snake_case__=None		,					snake_case__="<unk>"		,					snake_case__="<s>"		,					snake_case__="</s>"		,					snake_case__="<pad>"		,					snake_case__=False		,					snake_case__=False		,					**snake_case__		,					):






         """simple docstring"""





         super().__init__(
             snake_case__		,					snake_case__		,					tokenizer_file=snake_case__		,					unk_token=snake_case__		,					bos_token=snake_case__		,					eos_token=snake_case__		,					pad_token=snake_case__		,					add_prefix_space=snake_case__		,					clean_up_tokenization_spaces=snake_case__		,					**snake_case__		,					)
         lowerCAmelCase					:					str								=							json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
         if pre_tok_state.get("add_prefix_space"		,					snake_case__						) != add_prefix_space:
           lowerCAmelCase					:					Tuple								=							getattr(snake_case__		,					pre_tok_state.pop("type"						)						)
           lowerCAmelCase					:					Optional[int]								=							add_prefix_space
           lowerCAmelCase					:					List[Any]								=							pre_tok_class(**snake_case__						)

         lowerCAmelCase					:					List[str]								=							add_prefix_space

       def 	lowercase__							(						self		,					*snake_case__		,					**snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Union[str, Any]								=							kwargs.get("is_split_into_words"		,					snake_case__						)
         if not (self.add_prefix_space or not is_split_into_words):
           raise Exception(
               f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
               " pretokenized inputs."						)

         return super()._batch_encode_plus(*snake_case__		,					**snake_case__						)

       def 	lowercase__							(						self		,					*snake_case__		,					**snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					List[Any]								=							kwargs.get("is_split_into_words"		,					snake_case__						)

         if not (self.add_prefix_space or not is_split_into_words):
           raise Exception(
               f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"""
               " pretokenized inputs."						)

         return super()._encode_plus(*snake_case__		,					**snake_case__						)

       def 	lowercase__							(						self		,					snake_case__		,					snake_case__ = None						):






         """simple docstring"""





         lowerCAmelCase					:					Union[str, Any]								=							self._tokenizer.model.save(snake_case__		,					name=snake_case__						)
         return tuple(snake_case__						)







       def 	lowercase__							(						self		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					List[str]								=							[]
         for is_user, text in conversation.iter_texts():
           input_ids.extend(self.encode(snake_case__		,					add_special_tokens=snake_case__						) + [self.eos_token_id]						)

         if len(snake_case__						) > self.model_max_length:
           lowerCAmelCase					:					Optional[Any]								=							input_ids[-self.model_max_length :]
         return input_ids









"""simple docstring"""







from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
lowerCAmelCase__				    =       1.0_5_4_5_7_1_8_1_7e-3_4  # unit of ℏ : J * s

lowerCAmelCase__				    =       3e8  # unit of c : m * s^-1
def  a__      (    SCREAMING_SNAKE_CASE   :   float    ,				SCREAMING_SNAKE_CASE   :   float    ,				SCREAMING_SNAKE_CASE   :   float    ):


  '''simple docstring'''







  if (force, area, distance).count(0    ) != 1:
    raise ValueError("One and only one argument must be 0"    )
  if force < 0:
    raise ValueError("Magnitude of force can not be negative"    )
  if distance < 0:
    raise ValueError("Distance can not be negative"    )
  if area < 0:
    raise ValueError("Area can not be negative"    )
  if force == 0:
    lowerCAmelCase					:					Any								=							(REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
        2_4_0 * (distance) ** 4
    )
    return {"force": force}
  elif area == 0:
    lowerCAmelCase					:					Any								=							(2_4_0 * force * (distance) ** 4) / (
        REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
    )
    return {"area": area}
  elif distance == 0:
    lowerCAmelCase					:					Dict								=							(
        (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (2_4_0 * force)
    ) ** (1 / 4)
    return {"distance": distance}
  raise ValueError("One and only one argument must be 0"    )


# Run doctest
if __name__ == "__main__":
     import doctest

     doctest.testmod()





