
'''simple docstring'''







import math







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			float:
	if (
	    not isinstance(__A    ,       (int, float)			)
	    or power_factor < -1
	    or power_factor > 1
	):
		raise ValueError('power_factor must be a valid float value between -1 and 1.'			)
	return apparent_power * power_factor







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A			) ->			float:
	if (
	    not isinstance(__A    ,       (int, float)			)
	    or power_factor < -1
	    or power_factor > 1
	):
		raise ValueError('power_factor must be a valid float value between -1 and 1.'			)
	return apparent_power * math.sqrt(1 - power_factor**2			)


if __name__ == "__main__":
					import doctest

					doctest.testmod()



'''simple docstring'''







from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


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

lowercase					:							str   =      {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

lowercase					:							Optional[Any]   =      {
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

lowercase					:							List[Any]   =      {
    "facebook/blenderbot_small-90M": 512,
}


class 		__UpperCAmelCase   (      _lowerCamelCase		):
							__lowercase   	= VOCAB_FILES_NAMES
							__lowercase   	= PRETRAINED_VOCAB_FILES_MAP
							__lowercase   	= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase   	= BlenderbotSmallTokenizer


							def __init__( self					,     lowerCAmelCase_=None					,     lowerCAmelCase_=None					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_=False					,     lowerCAmelCase_=True					,     **lowerCAmelCase_					,     ):





								"""simple docstring"""






								super().__init__(
								    ByteLevelBPETokenizer(
								        vocab=lowerCAmelCase_					,     merges=lowerCAmelCase_					,     add_prefix_space=lowerCAmelCase_					,     trim_offsets=lowerCAmelCase_					,     )					,     bos_token=lowerCAmelCase_					,     eos_token=lowerCAmelCase_					,     unk_token=lowerCAmelCase_					,     **lowerCAmelCase_					,     )
								_snake_case     		=	add_prefix_space


							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_=None						):





								"""simple docstring"""






								_snake_case     		=	[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 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_ = None						):





								"""simple docstring"""






								_snake_case     		=	[self.sep_token_id]
								_snake_case     		=	[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]

