"""simple docstring"""


from __future__ import annotations

from collections.abc import Iterator
from typing import Any




class  UpperCamelCase					:







       def __init__( self,							lowerCAmelCase__)      ->      Optional[int]:
            snake_case_					       =					data
            snake_case_					       =					None




class  UpperCamelCase					:







       def __init__( self)      ->      Dict:
            snake_case_					       =					None
            snake_case_					       =					None







       def __iter__( self)      ->      Iterator[Any]:
            snake_case_					       =					self.head
            while self.head:
                 yield node.data
                 snake_case_					       =					node.next
                 if node == self.head:
                      break







       def __len__( self)      ->      int:
            return sum(1 for _ in self)







       def __repr__( self)      ->      str:
            return "->".join(str(lowerCAmelCase__) for item in iter(self))







       def 		a_						( self,							lowerCAmelCase__)      ->      None:
            self.insert_nth(len(self),							lowerCAmelCase__)







       def 		a_						( self,							lowerCAmelCase__)      ->      None:
            self.insert_nth(0,							lowerCAmelCase__)







       def 		a_						( self,							lowerCAmelCase__,							lowerCAmelCase__)      ->      None:
            if index < 0 or index > len(self):
                 raise IndexError('list index out of range.')
            snake_case_					       =					Node(lowerCAmelCase__)
            if self.head is None:
                 snake_case_					       =					new_node  # first node points itself
                 snake_case_					       =					snake_case_					       =					new_node
            elif index == 0:  # insert at head
                 snake_case_					       =					self.head
                 snake_case_					       =					snake_case_					       =					new_node
            else:
                 snake_case_					       =					self.head
                 for _ in range(index - 1):
                      snake_case_					       =					temp.next
                 snake_case_					       =					temp.next
                 snake_case_					       =					new_node
                 if index == len(self) - 1:  # insert at tail
                      snake_case_					       =					new_node







       def 		a_						( self)      ->      str:
            return self.delete_nth(0)







       def 		a_						( self)      ->      Any:
            return self.delete_nth(len(self) - 1)







       def 		a_						( self,							lowerCAmelCase__ = 0)      ->      Any:
            if not 0 <= index < len(self):
                 raise IndexError('list index out of range.')
            snake_case_					       =					self.head
            if self.head == self.tail:  # just one node
                 snake_case_					       =					snake_case_					       =					None
            elif index == 0:  # delete head node
                 snake_case_					       =					self.tail.next.next
                 snake_case_					       =					self.head.next
            else:
                 snake_case_					       =					self.head
                 for _ in range(index - 1):
                      snake_case_					       =					temp.next
                 snake_case_					       =					temp.next
                 snake_case_					       =					temp.next.next
                 if index == len(self) - 1:  # delete at tail
                      snake_case_					       =					temp
            return delete_node.data







       def 		a_						( self)      ->      bool:
            return len(self) == 0







def 					UpperCAmelCase    (		)				->      None:
     snake_case_					       =					CircularLinkedList()
     assert len(UpperCAmelCase					) == 0
     assert circular_linked_list.is_empty() is True
     assert str(UpperCAmelCase					) == ""

     try:
          circular_linked_list.delete_front()
          raise AssertionError  # This should not happen
     except IndexError:
          assert True  # This should happen

     try:
          circular_linked_list.delete_tail()
          raise AssertionError  # This should not happen
     except IndexError:
          assert True  # This should happen

     try:
          circular_linked_list.delete_nth(-1					)
          raise AssertionError
     except IndexError:
          assert True

     try:
          circular_linked_list.delete_nth(0					)
          raise AssertionError
     except IndexError:
          assert True

     assert circular_linked_list.is_empty() is True
     for i in range(5					):
          assert len(UpperCAmelCase					) == i
          circular_linked_list.insert_nth(UpperCAmelCase						,					i + 1					)
     assert str(UpperCAmelCase					) == "->".join(str(UpperCAmelCase					) for i in range(1						,					6					)					)

     circular_linked_list.insert_tail(6					)
     assert str(UpperCAmelCase					) == "->".join(str(UpperCAmelCase					) for i in range(1						,					7					)					)
     circular_linked_list.insert_head(0					)
     assert str(UpperCAmelCase					) == "->".join(str(UpperCAmelCase					) for i in range(0						,					7					)					)

     assert circular_linked_list.delete_front() == 0
     assert circular_linked_list.delete_tail() == 6
     assert str(UpperCAmelCase					) == "->".join(str(UpperCAmelCase					) for i in range(1						,					6					)					)
     assert circular_linked_list.delete_nth(2					) == 3

     circular_linked_list.insert_nth(2						,					3					)
     assert str(UpperCAmelCase					) == "->".join(str(UpperCAmelCase					) for i in range(1						,					6					)					)

     assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
    import doctest

    doctest.testmod()








"""simple docstring"""




from typing import List, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_     :						Union[str, Any]						=					logging.get_logger(__name__)

lowerCamelCase_     :						Optional[Any]						=					{
    'huggingface/informer-tourism-monthly': (
        'https://huggingface.co/huggingface/informer-tourism-monthly/resolve/main/config.json'
    ),
    # See all Informer models at https://huggingface.co/models?filter=informer
}

class  _UpperCAmelCase  (   UpperCAmelCase__		):



      '''simple docstring'''
      lowercase_      : Tuple	    =   """informer"""
      lowercase_      : str	    =   {
          """hidden_size""": """d_model""",
          """num_attention_heads""": """encoder_attention_heads""",
          """num_hidden_layers""": """encoder_layers""",
      }

      def __init__(     self					,      snake_case_ = None					,      snake_case_ = None					,      snake_case_ = "student_t"					,      snake_case_ = "nll"					,      snake_case_ = 1					,      snake_case_ = None					,      snake_case_ = "mean"					,      snake_case_ = 0					,      snake_case_ = 0					,      snake_case_ = 0					,      snake_case_ = 0					,      snake_case_ = None					,      snake_case_ = None					,      snake_case_ = 6_4					,      snake_case_ = 3_2					,      snake_case_ = 3_2					,      snake_case_ = 2					,      snake_case_ = 2					,      snake_case_ = 2					,      snake_case_ = 2					,      snake_case_ = True					,      snake_case_ = "gelu"					,      snake_case_ = 0.05					,      snake_case_ = 0.1					,      snake_case_ = 0.1					,      snake_case_ = 0.1					,      snake_case_ = 0.1					,      snake_case_ = 1_0_0					,      snake_case_ = 0.02					,      snake_case_=True					,      snake_case_ = "prob"					,      snake_case_ = 5					,      snake_case_ = True					,      **snake_case_					,      ):

        """simple docstring"""

        A_  :       str										=  prediction_length
        A_  :       List[Any]										=  context_length or prediction_length
        A_  :       str										=  distribution_output
        A_  :       Dict										=  loss
        A_  :       Any										=  input_size
        A_  :       Union[str, Any]										=  num_time_features
        A_  :       Optional[Any]										=  lags_sequence if lags_sequence is not None else [1, 2, 3, 4, 5, 6, 7]
        A_  :       List[Any]										=  scaling
        A_  :       Tuple										=  num_dynamic_real_features
        A_  :       Any										=  num_static_real_features
        A_  :       str										=  num_static_categorical_features

        # set cardinality
        if cardinality and num_static_categorical_features > 0:
          if len(snake_case_  ) != num_static_categorical_features:
            raise ValueError(
                'The cardinality should be a list of the same length as `num_static_categorical_features`'  )
          A_  :       Optional[int]										=  cardinality
        else:
          A_  :       Optional[Any]										=  [0]

        # set embedding_dimension
        if embedding_dimension and num_static_categorical_features > 0:
          if len(snake_case_  ) != num_static_categorical_features:
            raise ValueError(
                'The embedding dimension should be a list of the same length as `num_static_categorical_features`'  )
          A_  :       Any										=  embedding_dimension
        else:
          A_  :       Optional[Any]										=  [min(5_0					,      (cat + 1) // 2  ) for cat in self.cardinality]

        A_  :       int										=  num_parallel_samples

        # Transformer architecture configuration
        A_  :       str										=  input_size * len(self.lags_sequence  ) + self._number_of_features
        A_  :       List[Any]										=  d_model
        A_  :       Dict										=  encoder_attention_heads
        A_  :       Dict										=  decoder_attention_heads
        A_  :       List[Any]										=  encoder_ffn_dim
        A_  :       Union[str, Any]										=  decoder_ffn_dim
        A_  :       int										=  encoder_layers
        A_  :       Any										=  decoder_layers

        A_  :       List[Any]										=  dropout
        A_  :       str										=  attention_dropout
        A_  :       Tuple										=  activation_dropout
        A_  :       List[str]										=  encoder_layerdrop
        A_  :       List[str]										=  decoder_layerdrop

        A_  :       str										=  activation_function
        A_  :       Optional[int]										=  init_std

        A_  :       List[Any]										=  use_cache

        # Informer
        A_  :       Tuple										=  attention_type
        A_  :       List[Any]										=  sampling_factor
        A_  :       Optional[int]										=  distil

        super().__init__(is_encoder_decoder=snake_case_					,      **snake_case_  )

      @property
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

        return (
            sum(self.embedding_dimension  )
            + self.num_dynamic_real_features
            + self.num_time_features
            + self.num_static_real_features
            + self.input_size * 2  # the log1p(abs(loc)) and log(scale) features
        )