
"""simple docstring"""



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


UpperCamelCase__          =	logging.get_logger(__name__)

UpperCamelCase__          =	{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}





class 				a			(					lowercase      ):
      UpperCamelCase							:   Optional[Any]           =     """biogpt"""



      def __init__(   self     ,	UpperCamelCase_=42_384     ,	UpperCamelCase_=1_024     ,	UpperCamelCase_=24     ,	UpperCamelCase_=16     ,	UpperCamelCase_=4_096     ,	UpperCamelCase_="gelu"     ,	UpperCamelCase_=0.1     ,	UpperCamelCase_=0.1     ,	UpperCamelCase_=1_024     ,	UpperCamelCase_=0.02     ,	UpperCamelCase_=1E-12     ,	UpperCamelCase_=True     ,	UpperCamelCase_=True     ,	UpperCamelCase_=0.0     ,	UpperCamelCase_=0.0     ,	UpperCamelCase_=1     ,	UpperCamelCase_=0     ,	UpperCamelCase_=2     ,	**UpperCamelCase_     ,	):
          UpperCAmelCase__	:      Any     							=					vocab_size
          UpperCAmelCase__	:      Dict     							=					max_position_embeddings
          UpperCAmelCase__	:      Dict     							=					hidden_size
          UpperCAmelCase__	:      List[Any]     							=					num_hidden_layers
          UpperCAmelCase__	:      str     							=					num_attention_heads
          UpperCAmelCase__	:      Optional[Any]     							=					intermediate_size
          UpperCAmelCase__	:      Any     							=					hidden_act
          UpperCAmelCase__	:      str     							=					hidden_dropout_prob
          UpperCAmelCase__	:      List[Any]     							=					attention_probs_dropout_prob
          UpperCAmelCase__	:      Any     							=					initializer_range
          UpperCAmelCase__	:      str     							=					layer_norm_eps
          UpperCAmelCase__	:      Optional[int]     							=					scale_embedding
          UpperCAmelCase__	:      Optional[int]     							=					use_cache
          UpperCAmelCase__	:      List[str]     							=					layerdrop
          UpperCAmelCase__	:      List[str]     							=					activation_dropout
          super().__init__(pad_token_id=UpperCamelCase_     ,	bos_token_id=UpperCamelCase_     ,	eos_token_id=UpperCamelCase_     ,	**UpperCamelCase_      )



"""simple docstring"""



def 					lowerCamelCase   (     _snake_case    ,_snake_case    ,_snake_case ):
    if len(_snake_case ) != len(_snake_case ):
        raise ValueError('The length of profit and weight must be same.' )
    if max_weight <= 0:
        raise ValueError('max_weight must greater than zero.' )
    if any(p < 0 for p in profit ):
        raise ValueError('Profit can not be negative.' )
    if any(w < 0 for w in weight ):
        raise ValueError('Weight can not be negative.' )

    # List created to store profit gained for the 1kg in case of each weight
    # respectively.  Calculate and append profit/weight for each element.
    UpperCAmelCase__	:      Any     							=					[p / w for p, w in zip(_snake_case    ,_snake_case )]

    # Creating a copy of the list and sorting profit/weight in ascending order
    UpperCAmelCase__	:      Union[str, Any]     							=					sorted(_snake_case )

    # declaring useful variables
    UpperCAmelCase__	:      Tuple     							=					len(_snake_case )
    UpperCAmelCase__	:      List[Any]     							=					0
    UpperCAmelCase__	:      Union[str, Any]     							=					0
    UpperCAmelCase__	:      Any     							=					0

    # loop till the total weight do not reach max limit e.g. 15 kg and till i<length
    while limit <= max_weight and i < length:
        # flag value for encountered greatest element in sorted_profit_by_weight
        UpperCAmelCase__	:      Tuple     							=					sorted_profit_by_weight[length - i - 1]
        UpperCAmelCase__	:      int     							=					profit_by_weight.index(_snake_case )
        UpperCAmelCase__	:      str     							=					-1

        # check if the weight encountered is less than the total weight
        # encountered before.
        if max_weight - limit >= weight[index]:
            limit += weight[index]
            # Adding profit gained for the given weight 1 ===
            # weight[index]/weight[index]
            gain += 1 * profit[index]
        else:
            # Since the weight encountered is greater than limit, therefore take the
            # required number of remaining kgs and calculate profit for it.
            # weight remaining / weight[index]
            gain += (max_weight - limit) / weight[index] * profit[index]
            break
        i += 1
    return gain


if __name__ == "__main__":
    print(
        'Input profits, weights, and then max_weight (all positive ints) separated by '
        'spaces.'
    )

    UpperCamelCase__          =	[int(x) for x in input('Input profits separated by spaces: ').split()]
    UpperCamelCase__          =	[int(x) for x in input('Input weights separated by spaces: ').split()]
    UpperCamelCase__          =	int(input('Max weight allowed: '))

    # Function Call
    calc_profit(profit, weight, max_weight)

