code: 
  
  
  import json
  import os
  import unittest
  
  from transformers import BartTokenizer, BartTokenizerFast, BatchEncoding
  from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_tokenizers, require_torch
  from transformers.utils import cached_property
  
  from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors
  
  
  
  
  
  
  
  @require_tokenizers
  class 					__lowercase					(       a_ ,       unittest.TestCase     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				Union[str, Any] 					=		BartTokenizer
  		UpperCamelCase    :				Any 					=		BartTokenizerFast
  		UpperCamelCase    :				int 					=		True
  		UpperCamelCase    :				Optional[int] 					=		filter_roberta_detectors
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   Any:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					super().setUp()
  					lowerCamelCase								=     [
  					    """l""",
  					    """o""",
  					    """w""",
  					    """e""",
  					    """r""",
  					    """s""",
  					    """t""",
  					    """i""",
  					    """d""",
  					    """n""",
  					    """\u0120""",
  					    """\u0120l""",
  					    """\u0120n""",
  					    """\u0120lo""",
  					    """\u0120low""",
  					    """er""",
  					    """\u0120lowest""",
  					    """\u0120newer""",
  					    """\u0120wider""",
  					    """<unk>""",
  					]
  					lowerCamelCase								=     dict(zip(A		,			range(len(A  )  )  )  )
  					lowerCamelCase								=     ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
  					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(A  ) + """\n"""  )
  					with open(self.merges_file		,			"""w"""		,			encoding="""utf-8"""  ) as fp:
  								fp.write("""\n""".join(A  )  )
  
  
  
  
  
  
  
  		def 				__A      (   self		,			**A  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					kwargs.update(self.special_tokens_map  )
  					return self.tokenizer_class.from_pretrained(self.tmpdirname		,			**A  )
  
  
  
  
  
  
  
  		def 				__A      (   self		,			**A  )     ->   Optional[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					kwargs.update(self.special_tokens_map  )
  					return self.rust_tokenizer_class.from_pretrained(self.tmpdirname		,			**A  )
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   Optional[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return "lower newer", "lower newer"
  
  
  
  
  
  
  
  		@cached_property
  		def 				__A      (   self  )     ->   Dict:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return BartTokenizer.from_pretrained("""facebook/bart-large"""  )
  
  
  
  
  
  
  
  		@cached_property
  		def 				__A      (   self  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return BartTokenizerFast.from_pretrained("""facebook/bart-large"""  )
  
  
  
  
  
  
  
  		@require_torch
  		def 				__A      (   self  )     ->   Any:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
  					lowerCamelCase								=     [0, 2_50, 2_51, 1_78_18, 13, 3_91_86, 19_38, 4, 2]
  
  					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
  								lowerCamelCase								=     tokenizer(A		,			max_length=len(A  )		,			padding=A		,			return_tensors="""pt"""  )
  								self.assertIsInstance(A		,			A  )
  
  								self.assertEqual((2, 9)		,			batch.input_ids.shape  )
  								self.assertEqual((2, 9)		,			batch.attention_mask.shape  )
  								lowerCamelCase								=     batch.input_ids.tolist()[0]
  								self.assertListEqual(A		,			A  )
  								# Test that special tokens are reset
  
  
  
  
  
  
  
  		@require_torch
  		def 				__A      (   self  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
  					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
  								lowerCamelCase								=     tokenizer(A		,			padding=A		,			return_tensors="""pt"""  )
  								# check if input_ids are returned and no labels
  								self.assertIn("""input_ids"""		,			A  )
  								self.assertIn("""attention_mask"""		,			A  )
  								self.assertNotIn("""labels"""		,			A  )
  								self.assertNotIn("""decoder_attention_mask"""		,			A  )
  
  
  
  
  
  
  
  		@require_torch
  		def 				__A      (   self  )     ->   Optional[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     [
  					    """Summary of the text.""",
  					    """Another summary.""",
  					]
  					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
  								lowerCamelCase								=     tokenizer(text_target=A		,			max_length=32		,			padding="""max_length"""		,			return_tensors="""pt"""  )
  								self.assertEqual(32		,			targets["""input_ids"""].shape[1]  )
  
  
  
  
  
  
  
  		@require_torch
  		def 				__A      (   self  )     ->   Optional[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
  								lowerCamelCase								=     tokenizer(
  								    ["""I am a small frog""" * 10_24, """I am a small frog"""]		,			padding=A		,			truncation=A		,			return_tensors="""pt"""  )
  								self.assertIsInstance(A		,			A  )
  								self.assertEqual(batch.input_ids.shape		,			(2, 10_24)  )
  
  
  
  
  
  
  
  		@require_torch
  		def 				__A      (   self  )     ->   Any:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""A long paragraph for summarization."""]
  					lowerCamelCase								=     [
  					    """Summary of the text.""",
  					]
  					for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
  								lowerCamelCase								=     tokenizer(A		,			return_tensors="""pt"""  )
  								lowerCamelCase								=     tokenizer(text_target=A		,			return_tensors="""pt"""  )
  								lowerCamelCase								=     inputs["""input_ids"""]
  								lowerCamelCase								=     targets["""input_ids"""]
  								self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()  )
  								self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()  )
  								self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()  )
  								self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()  )
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					pass
  
  
  
  
  
  
  
  		def 				__A      (   self  )     ->   List[Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
  								with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'  ):
  											lowerCamelCase								=     self.rust_tokenizer_class.from_pretrained(A		,			**A  )
  											lowerCamelCase								=     self.tokenizer_class.from_pretrained(A		,			**A  )
  											lowerCamelCase								=     """A, <mask> AllenNLP sentence."""
  											lowerCamelCase								=     tokenizer_r.encode_plus(A		,			add_special_tokens=A		,			return_token_type_ids=A  )
  											lowerCamelCase								=     tokenizer_p.encode_plus(A		,			add_special_tokens=A		,			return_token_type_ids=A  )
  
  											# token_type_ids should put 0 everywhere
  											self.assertEqual(sum(tokens_r["""token_type_ids"""]  )		,			sum(tokens_p["""token_type_ids"""]  )  )
  
  											# attention_mask should put 1 everywhere, so sum over length should be 1
  											self.assertEqual(
  											    sum(tokens_r["""attention_mask"""]  ) / len(tokens_r["""attention_mask"""]  )		,			sum(tokens_p["""attention_mask"""]  ) / len(tokens_p["""attention_mask"""]  )		,			)
  
  											lowerCamelCase								=     tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]  )
  											lowerCamelCase								=     tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]  )
  
  											# Rust correctly handles the space before the mask while python doesnt
  											self.assertSequenceEqual(tokens_p["""input_ids"""]		,			[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]  )
  											self.assertSequenceEqual(tokens_r["""input_ids"""]		,			[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]  )
  
  											self.assertSequenceEqual(
  											    A		,			["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]  )
  											self.assertSequenceEqual(
  											    A		,			["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]  )
style_context: 
  
  
  from __future__ import annotations
  
  from collections.abc import Callable
  from typing import Generic, TypeVar
  
  UpperCAmelCase      :						List[str]    =		TypeVar("T")
  UpperCAmelCase      :						Dict    =		TypeVar("U")
  
  
  
  
  
  
  
  class 					__lowercase					(       Generic[T, U]     ):
  
  
  
  		"""simple docstring"""
  
  		def __init__(   self		,			A		,			A  )     ->   Any:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     key
  					lowerCamelCase								=     val
  					lowerCamelCase								=     0
  					lowerCamelCase								=     None
  					lowerCamelCase								=     None
  
  
  
  
  
  
  
  		def __repr__(   self  )     ->   str:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return "Node: key: {}, val: {}, freq: {}, has next: {}, has prev: {}".format(
  					    self.key		,			self.val		,			self.freq		,			self.next is not None		,			self.prev is not None  )
  
  
  
  
  
  
  
  class 					__lowercase					(       Generic[T, U]     ):
  
  
  
  		"""simple docstring"""
  
  		def __init__(   self  )     ->   None:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     DoubleLinkedListNode(A		,			A  )
  					lowerCamelCase								=     DoubleLinkedListNode(A		,			A  )
  					lowerCamelCase		,		lowerCamelCase								=     self.rear, self.head
  
  
  
  
  
  
  
  		def __repr__(   self  )     ->   str:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     ["""DoubleLinkedList"""]
  					lowerCamelCase								=     self.head
  					while node.next is not None:
  								rep.append(str(A  )  )
  								lowerCamelCase								=     node.next
  					rep.append(str(self.rear  )  )
  					return ",\n    ".join(A  )
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   None:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     self.rear.prev
  
  					# All nodes other than self.head are guaranteed to have non-None previous
  					assert previous is not None
  
  					lowerCamelCase								=     node
  					lowerCamelCase								=     previous
  					lowerCamelCase								=     node
  					lowerCamelCase								=     self.rear
  					node.freq += 1
  					self._position_node(A  )
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   None:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					while node.prev is not None and node.prev.freq > node.freq:
  								# swap node with previous node
  								lowerCamelCase								=     node.prev
  
  								lowerCamelCase								=     previous_node.prev
  								lowerCamelCase								=     node.prev
  								lowerCamelCase								=     previous_node
  								lowerCamelCase								=     node
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   DoubleLinkedListNode[T, U] | None:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					if node.prev is None or node.next is None:
  								return None
  
  					lowerCamelCase								=     node.next
  					lowerCamelCase								=     node.prev
  					lowerCamelCase								=     None
  					lowerCamelCase								=     None
  					return node
  
  
  
  
  
  
  
  class 					__lowercase					(       Generic[T, U]     ):
  
  
  
  		"""simple docstring"""
  
  		UpperCamelCase    :				dict[Callable[[T], U], LFUCache[T, U]] 					=		{}
  
  
  
  
  
  
  
  		def __init__(   self		,			A  )     ->   Union[str, Any]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					lowerCamelCase								=     DoubleLinkedList()
  					lowerCamelCase								=     capacity
  					lowerCamelCase								=     0
  					lowerCamelCase								=     0
  					lowerCamelCase								=     0
  					lowerCamelCase								=     {}
  
  
  
  
  
  
  
  		def __repr__(   self  )     ->   str:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return (
  					    F'CacheInfo(hits={self.hits}, misses={self.miss}, '
  					    F'capacity={self.capacity}, current_size={self.num_keys})'
  					)
  
  
  
  
  
  
  
  		def __contains__(   self		,			A  )     ->   bool:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					return key in self.cache
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A  )     ->   U | None:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					if key in self.cache:
  								self.hits += 1
  								lowerCamelCase								=     self.cache[key]
  								lowerCamelCase								=     self.list.remove(self.cache[key]  )
  								assert node == value_node
  
  								# node is guaranteed not None because it is in self.cache
  								assert node is not None
  								self.list.add(A  )
  								return node.val
  					self.miss += 1
  					return None
  
  
  
  
  
  
  
  		def 				__A      (   self		,			A		,			A  )     ->   None:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					if key not in self.cache:
  								if self.num_keys >= self.capacity:
  											# delete first node when over capacity
  											lowerCamelCase								=     self.list.head.next
  
  											# guaranteed to have a non-None first node when num_keys > 0
  											# explain to type checker via assertions
  											assert first_node is not None
  											assert first_node.key is not None
  											assert self.list.remove(A  ) is not None
  											# first_node guaranteed to be in list
  
  											del self.cache[first_node.key]
  											self.num_keys -= 1
  								lowerCamelCase								=     DoubleLinkedListNode(A		,			A  )
  								self.list.add(self.cache[key]  )
  								self.num_keys += 1
  
  					else:
  								lowerCamelCase								=     self.list.remove(self.cache[key]  )
  								assert node is not None  # node guaranteed to be in list
  								lowerCamelCase								=     value
  								self.list.add(A  )
  
  
  
  
  
  
  
  		@classmethod
  		def 				__A      (   cls		,			A = 1_28  )     ->   Callable[[Callable[[T], U]], Callable[..., U]]:
  
  
  
  
  
  
  
  					'''simple docstring'''
  
  
  
  
  
  
  
  					def cache_decorator_inner(A  ) -> Callable[..., U]:
  								def cache_decorator_wrapper(*A  ) -> U:
  											if func not in cls.decorator_function_to_instance_map:
  														lowerCamelCase								=     LFUCache(A  )
  
  											lowerCamelCase								=     cls.decorator_function_to_instance_map[func].get(args[0]  )
  											if result is None:
  														lowerCamelCase								=     func(*A  )
  														cls.decorator_function_to_instance_map[func].put(args[0]		,			A  )
  											return result
  
  								def cache_info() -> LFUCache[T, U]:
  											return cls.decorator_function_to_instance_map[func]
  
  								setattr(A		,			"""cache_info"""		,			A  )  # noqa: B010
  
  								return cache_decorator_wrapper
  
  					return cache_decorator_inner
  
  
  if __name__ == "__main__":
  		import doctest
  
  		doctest.testmod()
  
  