
from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

snake_case__  							=							TypeVar("""T""")
snake_case__  							=							TypeVar("""U""")







class 							UpperCAmelCase	(   Generic[T, U]					):

					def __init__(			self      :					Union[str, Any] ,      lowerCAmelCase      :					T | None ,      lowerCAmelCase      :					U | None					):
											lowercase       :    Union[str, Any]											=  key
											lowercase       :    int											=  val
											lowercase       :    int											=  0
											lowercase       :    DoubleLinkedListNode[T, U] | None											=  None
											lowercase       :    DoubleLinkedListNode[T, U] | None											=  None




					def __repr__(			self      :					List[str]					):
											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 							UpperCAmelCase	(   Generic[T, U]					):

					def __init__(			self      :					Any					):
											lowercase       :    DoubleLinkedListNode[T, U]											=  DoubleLinkedListNode(lowerCAmelCase ,      lowerCAmelCase					)
											lowercase       :    DoubleLinkedListNode[T, U]											=  DoubleLinkedListNode(lowerCAmelCase ,      lowerCAmelCase					)
											lowercase				,				lowercase       :    Union[str, Any]											=  self.rear, self.head

					def __repr__(			self      :					Optional[Any]					):
											lowercase       :    Tuple											=  ['''DoubleLinkedList''']
											lowercase       :    int											=  self.head
											while node.next is not None:
																	rep.append(str(lowerCAmelCase					)					)
																	lowercase       :    Tuple											=  node.next
											rep.append(str(self.rear					)					)
											return ",\n    ".join(lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					Tuple ,      lowerCAmelCase      :					DoubleLinkedListNode[T, U]					):
											lowercase       :    Any											=  self.rear.prev

											# All nodes other than self.head are guaranteed to have non-None previous
											assert previous is not None

											lowercase       :    List[Any]											=  node
											lowercase       :    Union[str, Any]											=  previous
											lowercase       :    str											=  node
											lowercase       :    Tuple											=  self.rear
											node.freq += 1
											self._position_node(lowerCAmelCase					)

					def        _lowerCAmelCase	(			self      :					Optional[int] ,      lowerCAmelCase      :					DoubleLinkedListNode[T, U]					):

											while node.prev is not None and node.prev.freq > node.freq:
																	# swap node with previous node
																	lowercase       :    Dict											=  node.prev

																	lowercase       :    List[str]											=  previous_node.prev
																	lowercase       :    Optional[Any]											=  node.prev
																	lowercase       :    Dict											=  previous_node
																	lowercase       :    Tuple											=  node




					def        _lowerCAmelCase	(			self      :					Any ,      lowerCAmelCase      :					DoubleLinkedListNode[T, U]					):

											if node.prev is None or node.next is None:
																	return None

											lowercase       :    Union[str, Any]											=  node.next
											lowercase       :    Union[str, Any]											=  node.prev
											lowercase       :    Tuple											=  None
											lowercase       :    Any											=  None
											return node







class 							UpperCAmelCase	(   Generic[T, U]					):
					a__: dict[Callable[[T], U], LFUCache[T, U]]			  =				{}

					def __init__(			self      :					Dict ,      lowerCAmelCase      :					int					):
											lowercase       :    DoubleLinkedList[T, U]											=  DoubleLinkedList()
											lowercase       :    Tuple											=  capacity
											lowercase       :    Optional[int]											=  0
											lowercase       :    Any											=  0
											lowercase       :    Any											=  0
											lowercase       :    dict[T, DoubleLinkedListNode[T, U]]											=  {}

					def __repr__(			self      :					Any					):
											return (
											    f'''CacheInfo(hits={self.hits}, misses={self.miss}, '''
											    f'''capacity={self.capacity}, current_size={self.num_keys})'''
											)

					def __contains__(			self      :					Tuple ,      lowerCAmelCase      :					T					):
											return key in self.cache

					def        _lowerCAmelCase	(			self      :					List[str] ,      lowerCAmelCase      :					T					):

											if key in self.cache:
																	self.hits += 1
																	lowercase       :    DoubleLinkedListNode[T, U]											=  self.cache[key]
																	lowercase       :    Tuple											=  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(lowerCAmelCase					)
																	return node.val
											self.miss += 1
											return None

					def        _lowerCAmelCase	(			self      :					Tuple ,      lowerCAmelCase      :					T ,      lowerCAmelCase      :					U					):

											if key not in self.cache:
																	if self.num_keys >= self.capacity:
																							# delete first node when over capacity
																							lowercase       :    int											=  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(lowerCAmelCase					) is not None
																							# first_node guaranteed to be in list

																							del self.cache[first_node.key]
																							self.num_keys -= 1
																	lowercase       :    List[str]											=  DoubleLinkedListNode(lowerCAmelCase ,      lowerCAmelCase					)
																	self.list.add(self.cache[key]					)
																	self.num_keys += 1

											else:
																	lowercase       :    Union[str, Any]											=  self.list.remove(self.cache[key]					)
																	assert node is not None  # node guaranteed to be in list
																	lowercase       :    Dict											=  value
																	self.list.add(lowerCAmelCase					)




					@classmethod
					def        _lowerCAmelCase	(			cls      :					type[LFUCache[T, U]] ,      lowerCAmelCase      :					int = 128					):

											def cache_decorator_inner(lowerCAmelCase      :					Callable[[T], U]					) -> Callable[..., U]:
																	def cache_decorator_wrapper(*lowerCAmelCase      :					T					) -> U:
																							if func not in cls.decorator_function_to_instance_map:
																													lowercase       :    List[Any]											=  LFUCache(lowerCAmelCase					)

																							lowercase       :    Tuple											=  cls.decorator_function_to_instance_map[func].get(args[0]					)
																							if result is None:
																													lowercase       :    str											=  func(*lowerCAmelCase					)
																													cls.decorator_function_to_instance_map[func].put(args[0] ,      lowerCAmelCase					)
																							return result

																	def cache_info() -> LFUCache[T, U]:
																							return cls.decorator_function_to_instance_map[func]

																	setattr(lowerCAmelCase ,      '''cache_info''' ,      lowerCAmelCase					)  # noqa: B010

																	return cache_decorator_wrapper

											return cache_decorator_inner


if __name__ == "__main__":
				import doctest

				doctest.testmod()




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


snake_case__  							=							{"""configuration_t5""": ["""T5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """T5Config""", """T5OnnxConfig"""]}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							["""T5Tokenizer"""]

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							["""T5TokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							[
				    """T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """T5EncoderModel""",
				    """T5ForConditionalGeneration""",
				    """T5Model""",
				    """T5PreTrainedModel""",
				    """load_tf_weights_in_t5""",
				    """T5ForQuestionAnswering""",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							[
				    """TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """TFT5EncoderModel""",
				    """TFT5ForConditionalGeneration""",
				    """TFT5Model""",
				    """TFT5PreTrainedModel""",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case__  							=							[
				    """FlaxT5EncoderModel""",
				    """FlaxT5ForConditionalGeneration""",
				    """FlaxT5Model""",
				    """FlaxT5PreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_ta import TaTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_ta_fast import TaTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_ta import (
								    T5_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TaEncoderModel,
								    TaForConditionalGeneration,
								    TaForQuestionAnswering,
								    TaModel,
								    TaPreTrainedModel,
								    load_tf_weights_in_ta,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_ta import (
								    TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFTaEncoderModel,
								    TFTaForConditionalGeneration,
								    TFTaModel,
								    TFTaPreTrainedModel,
								)

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_ta import (
								    FlaxTaEncoderModel,
								    FlaxTaForConditionalGeneration,
								    FlaxTaModel,
								    FlaxTaPreTrainedModel,
								)


else:
				import sys

				snake_case__  							=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


