


'''simple docstring'''






def  _snake_case       (					A			,   A			,   A			,   A	)						->   Dict:
							global f  # a global dp table for knapsack
							if f[i][j] < 0:
														if j < wt[i - 1]:
																					lowerCAmelCase__	       =     mf_knapsack(i - 1			,   __lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase	)
														else:
																					lowerCAmelCase__	       =     max(
																					    mf_knapsack(i - 1			,   __lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase	)			,   mf_knapsack(i - 1			,   __lowerCamelCase			,   __lowerCamelCase			,   j - wt[i - 1]	) + val[i - 1]			,   )
														lowerCAmelCase__	       =     val
							return f[i][j]


def  _snake_case       (					A			,   A			,   A			,   A	)						->   int:
							lowerCAmelCase__	       =     [[0] * (w + 1) for _ in range(n + 1	)]

							for i in range(1			,   n + 1	):
														for w_ in range(1			,   w + 1	):
																					if wt[i - 1] <= w_:
																												lowerCAmelCase__	       =     max(val[i - 1] + dp[i - 1][w_ - wt[i - 1]]			,   dp[i - 1][w_]	)
																					else:
																												lowerCAmelCase__	       =     dp[i - 1][w_]

							return dp[n][w_], dp


def  _snake_case       (					A			,   A			,   A	)						->   Dict:
							if not (isinstance(__lowerCamelCase			,   (list, tuple)	) and isinstance(__lowerCamelCase			,   (list, tuple)	)):
														raise ValueError(
														    '''Both the weights and values vectors must be either lists or tuples'''	)

							lowerCAmelCase__	       =     len(__lowerCamelCase	)
							if num_items != len(__lowerCamelCase	):
														lowerCAmelCase__	       =     (
														    "The number of weights must be the same as the number of values.\n"
														    F"""But got {num_items} weights and {len(__lowerCamelCase	)} values"""
														)
														raise ValueError(__lowerCamelCase	)
							for i in range(__lowerCamelCase	):
														if not isinstance(wt[i]			,   __lowerCamelCase	):
																					lowerCAmelCase__	       =     (
																					    "All weights must be integers but got weight of "
																					    F"""type {type(wt[i]	)} at index {i}"""
																					)
																					raise TypeError(__lowerCamelCase	)

							lowerCAmelCase__	       =     knapsack(__lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase	)
							lowerCAmelCase__	       =     set()
							_construct_solution(__lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase			,   __lowerCamelCase	)

							return optimal_val, example_optional_set


def  _snake_case       (					A			,   A			,   A			,   A			,   A	)						->   str:
							# for the current item i at a maximum weight j to be part of an optimal subset,
							# the optimal value at (i, j) must be greater than the optimal value at (i-1, j).
							# where i - 1 means considering only the previous items at the given maximum weight
							if i > 0 and j > 0:
														if dp[i - 1][j] == dp[i][j]:
																					_construct_solution(__lowerCamelCase			,   __lowerCamelCase			,   i - 1			,   __lowerCamelCase			,   __lowerCamelCase	)
														else:
																					optimal_set.add(__lowerCamelCase	)
																					_construct_solution(__lowerCamelCase			,   __lowerCamelCase			,   i - 1			,   j - wt[i - 1]			,   __lowerCamelCase	)


if __name__ == "__main__":
		__UpperCAmelCase       =							[3, 2, 4, 4]
		__UpperCAmelCase       =							[4, 3, 2, 3]
		__UpperCAmelCase       =							4
		__UpperCAmelCase       =							6
		__UpperCAmelCase       =							[[0] * (w + 1)] + [[0] + [-1] * (w + 1) for _ in range(n + 1)]
		__UpperCAmelCase    ,      __UpperCAmelCase       =							knapsack(w, wt, val, n)
		print(optimal_solution)
		print(mf_knapsack(n, wt, val, w))  # switched the n and w

		# testing the dynamic programming problem with example
		# the optimal subset for the above example are items 3 and 4
		__UpperCAmelCase    ,      __UpperCAmelCase       =							knapsack_with_example_solution(w, wt, val)
		assert optimal_solution == 8
		assert optimal_subset == {3, 4}
		print('''optimal_value = ''', optimal_solution)
		print('''An optimal subset corresponding to the optimal value''', optimal_subset)





'''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__    (							a__    ,    unittest.TestCase  ):





							'''simple docstring'''






							lowercase__      :       List[Any]     						=				CLIPTokenizer
							lowercase__      :       List[str]     						=				CLIPTokenizerFast
							lowercase__      :       Dict     						=				True
							lowercase__      :       Any     						=				{}
							lowercase__      :       Optional[int]     						=				False







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Any:
														super().setUp()

														# fmt: off
														lowerCAmelCase__	       =     ['''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
														lowerCAmelCase__	       =     dict(zip(lowerCamelCase_ ,   range(len(lowerCamelCase_       )       )       )       )
														lowerCAmelCase__	       =     ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''']
														lowerCAmelCase__	       =     {'''unk_token''': '''<unk>'''}

														lowerCAmelCase__	       =     os.path.join(self.tmpdirname ,   VOCAB_FILES_NAMES['''vocab_file''']       )
														lowerCAmelCase__	       =     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(lowerCamelCase_       ) + '''\n'''       )
														with open(self.merges_file ,   '''w''' ,   encoding='''utf-8'''       ) as fp:
																					fp.write('''\n'''.join(lowerCamelCase_       )       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   **lowerCamelCase_       )	->							Any:
														kwargs.update(self.special_tokens_map       )
														return CLIPTokenizer.from_pretrained(self.tmpdirname ,   **lowerCamelCase_       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   **lowerCamelCase_       )	->							int:
														kwargs.update(self.special_tokens_map       )
														return CLIPTokenizerFast.from_pretrained(self.tmpdirname ,   **lowerCamelCase_       )







							def   __SCREAMING_SNAKE_CASE							(		self ,   lowerCamelCase_       )	->							Any:
														lowerCAmelCase__	       =     '''lower newer'''
														lowerCAmelCase__	       =     '''lower newer'''
														return input_text, output_text







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Union[str, Any]:
														lowerCAmelCase__	       =     CLIPTokenizer(self.vocab_file ,   self.merges_file ,   **self.special_tokens_map       )
														lowerCAmelCase__	       =     '''lower newer'''
														lowerCAmelCase__	       =     ['''lo''', '''w''', '''er</w>''', '''n''', '''e''', '''w''', '''er</w>''']
														lowerCAmelCase__	       =     tokenizer.tokenize(lowerCamelCase_       )
														self.assertListEqual(lowerCamelCase_ ,   lowerCamelCase_       )

														lowerCAmelCase__	       =     tokens + [tokenizer.unk_token]
														lowerCAmelCase__	       =     [10, 2, 16, 9, 3, 2, 16, 20]
														self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCamelCase_       ) ,   lowerCamelCase_       )







							@require_ftfy
							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Tuple:
														for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																					with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""       ):
																												lowerCAmelCase__	       =     self.tokenizer_class.from_pretrained(lowerCamelCase_ ,   **lowerCamelCase_       )
																												lowerCAmelCase__	       =     self.rust_tokenizer_class.from_pretrained(lowerCamelCase_ ,   **lowerCamelCase_       )

																												lowerCAmelCase__	       =     '''A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d.'''
																												lowerCAmelCase__	       =     tokenizer_s.tokenize(lowerCamelCase_       )
																												lowerCAmelCase__	       =     tokenizer_r.tokenize(lowerCamelCase_       )

																												self.assertListEqual(lowerCamelCase_ ,   lowerCamelCase_       )

																												# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
																												# with Tilde) encoded in 2 different ways
																												lowerCAmelCase__	       =     '''xa\u0303y''' + ''' ''' + '''x\xe3y'''
																												lowerCAmelCase__	       =     tokenizer_s.tokenize(lowerCamelCase_       )
																												lowerCAmelCase__	       =     tokenizer_r.tokenize(lowerCamelCase_       )

																												self.assertListEqual(lowerCamelCase_ ,   lowerCamelCase_       )

																												# Test that the tokenization is identical on unicode of space type
																												lowerCAmelCase__	       =     [
																												    '''\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:
																																			lowerCAmelCase__	       =     tokenizer_s.tokenize(lowerCamelCase_       )
																																			lowerCAmelCase__	       =     tokenizer_r.tokenize(lowerCamelCase_       )

																																			self.assertListEqual(lowerCamelCase_ ,   lowerCamelCase_       )

																												# Test that the tokenization is identical on unicode of line break type
																												lowerCAmelCase__	       =     [
																												    '''\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:
																																			lowerCAmelCase__	       =     tokenizer_s.tokenize(lowerCamelCase_       )
																																			lowerCAmelCase__	       =     tokenizer_r.tokenize(lowerCamelCase_       )

																																			self.assertListEqual(lowerCamelCase_ ,   lowerCamelCase_       )







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							str:
														# 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})"""       ):
																												lowerCAmelCase__	       =     '''hello'''  # `hello` is a token in the vocabulary of `pretrained_name`
																												lowerCAmelCase__	       =     F"""{text_of_1_token} {text_of_1_token}"""

																												lowerCAmelCase__	       =     self.rust_tokenizer_class.from_pretrained(
																												    lowerCamelCase_ ,   use_fast=lowerCamelCase_ ,   )
																												lowerCAmelCase__	       =     tokenizer_r(lowerCamelCase_ ,   return_offsets_mapping=lowerCamelCase_ ,   add_special_tokens=lowerCamelCase_       )
																												self.assertEqual(encoding.offset_mapping[0] ,   (0, len(lowerCamelCase_       ))       )
																												self.assertEqual(
																												    encoding.offset_mapping[1] ,   (len(lowerCamelCase_       ) + 1, len(lowerCamelCase_       ) + 1 + len(lowerCamelCase_       )) ,   )

																												lowerCAmelCase__	       =     F""" {text}"""

																												lowerCAmelCase__	       =     self.rust_tokenizer_class.from_pretrained(
																												    lowerCamelCase_ ,   use_fast=lowerCamelCase_ ,   )
																												lowerCAmelCase__	       =     tokenizer_r(lowerCamelCase_ ,   return_offsets_mapping=lowerCamelCase_ ,   add_special_tokens=lowerCamelCase_       )
																												self.assertEqual(encoding.offset_mapping[0] ,   (1, 1 + len(lowerCamelCase_       ))       )
																												self.assertEqual(
																												    encoding.offset_mapping[1] ,   (1 + len(lowerCamelCase_       ) + 1, 1 + len(lowerCamelCase_       ) + 1 + len(lowerCamelCase_       )) ,   )







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Union[str, Any]:
														# 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(lowerCamelCase_       ) 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   __SCREAMING_SNAKE_CASE							(		self       )	->							List[Any]:
														super().test_tokenization_python_rust_equals()







							def   __SCREAMING_SNAKE_CASE							(		self       )	->							Any:
														# CLIP always lower cases letters
														pass