





"""simple docstring"""


__magic_name__					:				dict[str, float]	= {
    "kilogram": 1,
    "gram": pow(1_0, 3),
    "milligram": pow(1_0, 6),
    "metric-ton": pow(1_0, -3),
    "long-ton": 0.00_09_84_20_73,
    "short-ton": 0.00_11_02_31_22,
    "pound": 2.20_46_24_42_02,
    "stone": 0.15_74_73_17_28,
    "ounce": 35.2_73_99_07_23,
    "carrat": 5_0_0_0,
    "atomic-mass-unit": 6.0_22_13_66_52e26,
}

__magic_name__					:				dict[str, float]	= {
    "kilogram": 1,
    "gram": pow(1_0, -3),
    "milligram": pow(1_0, -6),
    "metric-ton": pow(1_0, 3),
    "long-ton": 10_16.0_46_08,
    "short-ton": 9_07.1_84,
    "pound": 0.45_35_92,
    "stone": 6.3_50_29,
    "ounce": 0.0_28_34_95,
    "carrat": 0.00_02,
    "atomic-mass-unit": 1.6_60_54_01_99e-27,
}

def     UpperCamelCase       (SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE       ,    SCREAMING_SNAKE_CASE    ):
						if to_type not in KILOGRAM_CHART or from_type not in WEIGHT_TYPE_CHART:
												UpperCamelCase							:		Tuple							      = (
												    f"""Invalid 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"""
												    f"""Supported values are: {", ".join(SCREAMING_SNAKE_CASE    )}"""
												)
												raise ValueError(SCREAMING_SNAKE_CASE    )
						return value * KILOGRAM_CHART[to_type] * WEIGHT_TYPE_CHART[from_type]


if __name__ == "__main__":
		import doctest

		doctest.testmod()










"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


__magic_name__					:				Any	= logging.get_logger(__name__)

__magic_name__					:				Dict	= {
    """uw-madison/yoso-4096""": """https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json""",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}






class        lowercase__ (      __SCREAMING_SNAKE_CASE  ):

			"""simple docstring"""
			__lowerCAmelCase    :							Optional[int]								=     """yoso"""







			def __init__(			self	,      _A=5_0_2_6_5	,      _A=7_6_8	,      _A=1_2	,      _A=1_2	,      _A=3_0_7_2	,      _A="gelu"	,      _A=0.1	,      _A=0.1	,      _A=4_0_9_6	,      _A=1	,      _A=0.02	,      _A=1e-1_2	,      _A="absolute"	,      _A=True	,      _A=9	,      _A=6_4	,      _A=None	,      _A=True	,      _A=True	,      _A=1	,      _A=0	,      _A=2	,      **_A	,      ):






									'''simple docstring'''







									super().__init__(pad_token_id=_A	,      bos_token_id=_A	,      eos_token_id=_A	,      **_A						)

									UpperCamelCase							:		Any							      = vocab_size
									UpperCamelCase							:		Any							      = max_position_embeddings
									UpperCamelCase							:		int							      = hidden_size
									UpperCamelCase							:		List[Any]							      = num_hidden_layers
									UpperCamelCase							:		Any							      = num_attention_heads
									UpperCamelCase							:		Optional[Any]							      = intermediate_size
									UpperCamelCase							:		Optional[int]							      = hidden_act
									UpperCamelCase							:		List[Any]							      = hidden_dropout_prob
									UpperCamelCase							:		int							      = attention_probs_dropout_prob
									UpperCamelCase							:		Any							      = initializer_range
									UpperCamelCase							:		Optional[Any]							      = type_vocab_size
									UpperCamelCase							:		Any							      = layer_norm_eps
									UpperCamelCase							:		List[Any]							      = position_embedding_type
									UpperCamelCase							:		Optional[Any]							      = use_expectation
									UpperCamelCase							:		Any							      = hash_code_len
									UpperCamelCase							:		Optional[int]							      = num_hash
									UpperCamelCase							:		List[Any]							      = conv_window
									UpperCamelCase							:		Tuple							      = use_fast_hash
									UpperCamelCase							:		Dict							      = lsh_backward



