





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_lowerCAmelCase				:   str						       =						{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase				:   Any						       =						['''SqueezeBertTokenizerFast''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _lowerCAmelCase				:   List[Any]						       =						[
     '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''SqueezeBertForMaskedLM''',
     '''SqueezeBertForMultipleChoice''',
     '''SqueezeBertForQuestionAnswering''',
     '''SqueezeBertForSequenceClassification''',
     '''SqueezeBertForTokenClassification''',
     '''SqueezeBertModel''',
     '''SqueezeBertModule''',
     '''SqueezeBertPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_squeezebert import (
     SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     SqueezeBertConfig,
     SqueezeBertOnnxConfig,
 )
 from .tokenization_squeezebert import SqueezeBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_squeezebert import (
      SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      SqueezeBertForMaskedLM,
      SqueezeBertForMultipleChoice,
      SqueezeBertForQuestionAnswering,
      SqueezeBertForSequenceClassification,
      SqueezeBertForTokenClassification,
      SqueezeBertModel,
      SqueezeBertModule,
      SqueezeBertPreTrainedModel,
  )

else:
 import sys

 _lowerCAmelCase				:   List[Any]						       =						_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







def   __snake_case    (       _lowerCAmelCase			:			list					,					_lowerCAmelCase			:			list					,					_lowerCAmelCase			:			int						)			->    int:
   if len(_lowerCAmelCase						) != len(_lowerCAmelCase						):
      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.
   A_       :					Dict        =      [p / w for p, w in zip(_lowerCAmelCase					,					_lowerCAmelCase						)]

   # Creating a copy of the list and sorting profit/weight in ascending order
   A_       :					Optional[Any]        =      sorted(_lowerCAmelCase						)

   # declaring useful variables
   A_       :					List[Any]        =      len(_lowerCAmelCase						)
   A_       :					List[Any]        =      0
   A_       :					Any        =      0
   A_       :					List[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
      A_       :					List[Any]        =      sorted_profit_by_weight[length - i - 1]
      A_       :					List[Any]        =      profit_by_weight.index(_lowerCAmelCase						)
      A_       :					List[Any]        =      -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.'''
 )

 _lowerCAmelCase				:   int						       =						[int(x) for x in input('''Input profits separated by spaces: ''').split()]
 _lowerCAmelCase				:   Dict						       =						[int(x) for x in input('''Input weights separated by spaces: ''').split()]
 _lowerCAmelCase				:   Union[str, Any]						       =						int(input('''Max weight allowed: '''))

 # Function Call
 calc_profit(profit, weight, max_weight)
