


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>"""]  )



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()

