
"""simple docstring"""



import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 				a			(					lowercase						,		unittest.TestCase      ):
      UpperCamelCase							:   Tuple           =     CLIPTokenizer
      UpperCamelCase							:   List[str]           =     CLIPTokenizerFast
      UpperCamelCase							:   Tuple           =     True
      UpperCamelCase							:   str           =     {}
      UpperCamelCase							:   Tuple           =     False



      def  __snake_case							(   self      ):
          super().setUp()

          # fmt: off
          UpperCAmelCase__	:      Any     							=					['l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
          # fmt: on
          UpperCAmelCase__	:      List[str]     							=					dict(zip(UpperCamelCase_     ,	range(len(UpperCamelCase_      )      )      )      )
          UpperCAmelCase__	:      List[Any]     							=					['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>']
          UpperCAmelCase__	:      Optional[Any]     							=					{'unk_token': '<unk>'}

          UpperCAmelCase__	:      List[Any]     							=					os.path.join(self.tmpdirname     ,	VOCAB_FILES_NAMES['vocab_file']      )
          UpperCAmelCase__	:      Union[str, Any]     							=					os.path.join(self.tmpdirname     ,	VOCAB_FILES_NAMES['merges_file']      )
          with open(self.vocab_file     ,	'w'     ,	encoding='utf-8'      ) as fp:
              fp.write(json.dumps(UpperCamelCase_      ) + '\n'      )
          with open(self.merges_file     ,	'w'     ,	encoding='utf-8'      ) as fp:
              fp.write('\n'.join(UpperCamelCase_      )      )



      def  __snake_case							(   self     ,	**UpperCamelCase_      ):
          kwargs.update(self.special_tokens_map      )
          return CLIPTokenizer.from_pretrained(self.tmpdirname     ,	**UpperCamelCase_      )



      def  __snake_case							(   self     ,	**UpperCamelCase_      ):
          kwargs.update(self.special_tokens_map      )
          return CLIPTokenizerFast.from_pretrained(self.tmpdirname     ,	**UpperCamelCase_      )



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      Any     							=					'lower newer'
          UpperCAmelCase__	:      Dict     							=					'lower newer'
          return input_text, output_text



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[Any]     							=					CLIPTokenizer(self.vocab_file     ,	self.merges_file     ,	**self.special_tokens_map      )
          UpperCAmelCase__	:      Optional[int]     							=					'lower newer'
          UpperCAmelCase__	:      int     							=					['lo', 'w', 'er</w>', 'n', 'e', 'w', 'er</w>']
          UpperCAmelCase__	:      Dict     							=					tokenizer.tokenize(UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

          UpperCAmelCase__	:      Union[str, Any]     							=					tokens + [tokenizer.unk_token]
          UpperCAmelCase__	:      int     							=					[10, 2, 16, 9, 3, 2, 16, 20]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase_      )     ,	UpperCamelCase_      )



      @require_ftfy
      def  __snake_case							(   self      ):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                  UpperCAmelCase__	:      List[str]     							=					self.tokenizer_class.from_pretrained(UpperCamelCase_     ,	**UpperCamelCase_      )
                  UpperCAmelCase__	:      Dict     							=					self.rust_tokenizer_class.from_pretrained(UpperCamelCase_     ,	**UpperCamelCase_      )

                  UpperCAmelCase__	:      int     							=					'A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'
                  UpperCAmelCase__	:      List[str]     							=					tokenizer_s.tokenize(UpperCamelCase_      )
                  UpperCAmelCase__	:      Optional[Any]     							=					tokenizer_r.tokenize(UpperCamelCase_      )

                  self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

                  # Test that the tokenization is identical on an example containing a character (Latin Small Letter A
                  # with Tilde) encoded in 2 different ways
                  UpperCAmelCase__	:      Tuple     							=					'xa\u0303y' + ' ' + 'x\xe3y'
                  UpperCAmelCase__	:      Dict     							=					tokenizer_s.tokenize(UpperCamelCase_      )
                  UpperCAmelCase__	:      List[str]     							=					tokenizer_r.tokenize(UpperCamelCase_      )

                  self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

                  # Test that the tokenization is identical on unicode of space type
                  UpperCAmelCase__	:      Tuple     							=					[
                      '\u0009',  # (horizontal tab, '\t')
                      '\u000B',  # (vertical tab)
                      '\u000C',  # (form feed)
                      '\u0020',  # (space, ' ')
                      '\u200E',  # (left-to-right mark):w
                      '\u200F',  # (right-to-left mark)
                  ]
                  for unicode_seq in spaces_unicodes:
                      UpperCAmelCase__	:      Dict     							=					tokenizer_s.tokenize(UpperCamelCase_      )
                      UpperCAmelCase__	:      List[Any]     							=					tokenizer_r.tokenize(UpperCamelCase_      )

                      self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

                  # Test that the tokenization is identical on unicode of line break type
                  UpperCAmelCase__	:      Optional[Any]     							=					[
                      '\u000A',  # (line feed, '\n')
                      '\r\n',  # (carriage return and line feed, '\r\n')
                      '\u000D',  # (carriage return, '\r')
                      '\r',  # (carriage return, '\r')
                      '\u000D',  # (carriage return, '\r')
                      '\u2028',  # (line separator)
                      '\u2029',  # (paragraph separator)
                      # "\u0085", # (next line)
                  ]

                  # The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
                  # it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
                  # space (and thus into an empty list).

                  for unicode_seq in line_break_unicodes:
                      UpperCAmelCase__	:      List[Any]     							=					tokenizer_s.tokenize(UpperCamelCase_      )
                      UpperCAmelCase__	:      str     							=					tokenizer_r.tokenize(UpperCamelCase_      )

                      self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )



      def  __snake_case							(   self      ):
          # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                  UpperCAmelCase__	:      str     							=					'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
                  UpperCAmelCase__	:      int     							=					F'''{text_of_1_token} {text_of_1_token}'''

                  UpperCAmelCase__	:      Dict     							=					self.rust_tokenizer_class.from_pretrained(
                      UpperCamelCase_     ,	use_fast=UpperCamelCase_     ,	)
                  UpperCAmelCase__	:      List[Any]     							=					tokenizer_r(UpperCamelCase_     ,	return_offsets_mapping=UpperCamelCase_     ,	add_special_tokens=UpperCamelCase_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(0, len(UpperCamelCase_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(len(UpperCamelCase_      ) + 1, len(UpperCamelCase_      ) + 1 + len(UpperCamelCase_      ))     ,	)

                  UpperCAmelCase__	:      Dict     							=					F''' {text}'''

                  UpperCAmelCase__	:      Dict     							=					self.rust_tokenizer_class.from_pretrained(
                      UpperCamelCase_     ,	use_fast=UpperCamelCase_     ,	)
                  UpperCAmelCase__	:      Tuple     							=					tokenizer_r(UpperCamelCase_     ,	return_offsets_mapping=UpperCamelCase_     ,	add_special_tokens=UpperCamelCase_      )
                  self.assertEqual(encoding.offset_mapping[0]     ,	(1, 1 + len(UpperCamelCase_      ))      )
                  self.assertEqual(
                      encoding.offset_mapping[1]     ,	(1 + len(UpperCamelCase_      ) + 1, 1 + len(UpperCamelCase_      ) + 1 + len(UpperCamelCase_      ))     ,	)



      def  __snake_case							(   self      ):
          # Test related to the breaking change introduced in transformers v4.17.0
          # We need to check that an error in raised when the user try to load a previous version of the tokenizer.
          with self.assertRaises(UpperCamelCase_      ) as context:
              self.rust_tokenizer_class.from_pretrained('robot-test/old-clip-tokenizer'      )

          self.assertTrue(
              context.exception.args[0].startswith(
                  'The `backend_tokenizer` provided does not match the expected format.'      )      )



      @require_ftfy
      def  __snake_case							(   self      ):
          super().test_tokenization_python_rust_equals()



      def  __snake_case							(   self      ):
          # CLIP always lower cases letters
          pass



"""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)

