
"""simple docstring"""



import copy

from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings


UpperCamelCase__          =	r'\n    [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n    can be used to control the model outputs. Read the documentation from [`PretrainedConfig`] for more information.\n\n    Args:\n        title_sep (`str`, *optional*, defaults to  `" / "`):\n            Separator inserted between the title and the text of the retrieved document when calling [`RagRetriever`].\n        doc_sep (`str`, *optional*, defaults to  `" // "`):\n            Separator inserted between the text of the retrieved document and the original input when calling\n            [`RagRetriever`].\n        n_docs (`int`, *optional*, defaults to 5):\n            Number of documents to retrieve.\n        max_combined_length (`int`, *optional*, defaults to 300):\n            Max length of contextualized input returned by [`~RagRetriever.__call__`].\n        retrieval_vector_size (`int`, *optional*, defaults to 768):\n            Dimensionality of the document embeddings indexed by [`RagRetriever`].\n        retrieval_batch_size (`int`, *optional*, defaults to 8):\n            Retrieval batch size, defined as the number of queries issues concurrently to the faiss index encapsulated\n            [`RagRetriever`].\n        dataset (`str`, *optional*, defaults to `"wiki_dpr"`):\n            A dataset identifier of the indexed dataset in HuggingFace Datasets (list all available datasets and ids\n            using `datasets.list_datasets()`).\n        dataset_split (`str`, *optional*, defaults to `"train"`)\n            Which split of the `dataset` to load.\n        index_name (`str`, *optional*, defaults to `"compressed"`)\n            The index name of the index associated with the `dataset`. One can choose between `"legacy"`, `"exact"` and\n            `"compressed"`.\n        index_path (`str`, *optional*)\n            The path to the serialized faiss index on disk.\n        passages_path (`str`, *optional*):\n            A path to text passages compatible with the faiss index. Required if using\n            [`~models.rag.retrieval_rag.LegacyIndex`]\n        use_dummy_dataset (`bool`, *optional*, defaults to `False`)\n            Whether to load a "dummy" variant of the dataset specified by `dataset`.\n        label_smoothing (`float`, *optional*, defaults to 0.0):\n            Only relevant if `return_loss` is set to `True`. Controls the `epsilon` parameter value for label smoothing\n            in the loss calculation. If set to 0, no label smoothing is performed.\n        do_marginalize (`bool`, *optional*, defaults to `False`):\n            If `True`, the logits are marginalized over all documents by making use of\n            `torch.nn.functional.log_softmax`.\n        reduce_loss (`bool`, *optional*, defaults to `False`):\n            Whether or not to reduce the NLL loss using the `torch.Tensor.sum` operation.\n        do_deduplication (`bool`, *optional*, defaults to `True`):\n            Whether or not to deduplicate the generations from different context documents for a given input. Has to be\n            set to `False` if used while training with distributed backend.\n        exclude_bos_score (`bool`, *optional*, defaults to `False`):\n            Whether or not to disregard the BOS token when computing the loss.\n        output_retrieved(`bool`, *optional*, defaults to `False`):\n            If set to `True`, `retrieved_doc_embeds`, `retrieved_doc_ids`, `context_input_ids` and\n            `context_attention_mask` are returned. See returned tensors for more detail.\n        use_cache (`bool`, *optional*, defaults to `True`):\n            Whether or not the model should return the last key/values attentions (not used by all models).\n        forced_eos_token_id (`int`, *optional*):\n            The id of the token to force as the last generated token when `max_length` is reached. Usually set to\n            `eos_token_id`.\n'





@add_start_docstrings(lowercase      )
class 				a			(					lowercase      ):
      UpperCamelCase							:   Tuple           =     """rag"""
      UpperCamelCase							:   str           =     True



      def __init__(   self     ,	UpperCamelCase_=None     ,	UpperCamelCase_=True     ,	UpperCamelCase_=None     ,	UpperCamelCase_=None     ,	UpperCamelCase_=None     ,	UpperCamelCase_=None     ,	UpperCamelCase_=None     ,	UpperCamelCase_=" / "     ,	UpperCamelCase_=" // "     ,	UpperCamelCase_=5     ,	UpperCamelCase_=300     ,	UpperCamelCase_=768     ,	UpperCamelCase_=8     ,	UpperCamelCase_="wiki_dpr"     ,	UpperCamelCase_="train"     ,	UpperCamelCase_="compressed"     ,	UpperCamelCase_=None     ,	UpperCamelCase_=None     ,	UpperCamelCase_=False     ,	UpperCamelCase_=False     ,	UpperCamelCase_=0.0     ,	UpperCamelCase_=True     ,	UpperCamelCase_=False     ,	UpperCamelCase_=False     ,	UpperCamelCase_=False     ,	UpperCamelCase_=True     ,	UpperCamelCase_=None     ,	**UpperCamelCase_     ,	):
          super().__init__(
              bos_token_id=UpperCamelCase_     ,	pad_token_id=UpperCamelCase_     ,	eos_token_id=UpperCamelCase_     ,	decoder_start_token_id=UpperCamelCase_     ,	forced_eos_token_id=UpperCamelCase_     ,	is_encoder_decoder=UpperCamelCase_     ,	prefix=UpperCamelCase_     ,	vocab_size=UpperCamelCase_     ,	**UpperCamelCase_     ,	)
          assert (
              "question_encoder" in kwargs and "generator" in kwargs
          ), "Config has to be initialized with question_encoder and generator config"
          UpperCAmelCase__	:      Union[str, Any]     							=					kwargs.pop('question_encoder'      )
          UpperCAmelCase__	:      Any     							=					question_encoder_config.pop('model_type'      )
          UpperCAmelCase__	:      Dict     							=					kwargs.pop('generator'      )
          UpperCAmelCase__	:      Optional[Any]     							=					decoder_config.pop('model_type'      )

          from ..auto.configuration_auto import AutoConfig

          UpperCAmelCase__	:      List[str]     							=					AutoConfig.for_model(UpperCamelCase_     ,	**UpperCamelCase_      )
          UpperCAmelCase__	:      int     							=					AutoConfig.for_model(UpperCamelCase_     ,	**UpperCamelCase_      )

          UpperCAmelCase__	:      Optional[int]     							=					reduce_loss
          UpperCAmelCase__	:      Optional[Any]     							=					label_smoothing
          UpperCAmelCase__	:      Any     							=					exclude_bos_score
          UpperCAmelCase__	:      str     							=					do_marginalize

          UpperCAmelCase__	:      Union[str, Any]     							=					title_sep
          UpperCAmelCase__	:      str     							=					doc_sep
          UpperCAmelCase__	:      Any     							=					n_docs
          UpperCAmelCase__	:      Dict     							=					max_combined_length

          UpperCAmelCase__	:      Optional[int]     							=					dataset
          UpperCAmelCase__	:      Any     							=					dataset_split
          UpperCAmelCase__	:      Optional[Any]     							=					index_name

          UpperCAmelCase__	:      Optional[Any]     							=					retrieval_vector_size
          UpperCAmelCase__	:      Dict     							=					retrieval_batch_size
          UpperCAmelCase__	:      str     							=					passages_path
          UpperCAmelCase__	:      int     							=					index_path
          UpperCAmelCase__	:      Any     							=					use_dummy_dataset

          UpperCAmelCase__	:      str     							=					output_retrieved

          UpperCAmelCase__	:      List[str]     							=					do_deduplication

          UpperCAmelCase__	:      Any     							=					use_cache

          if self.forced_eos_token_id is None:
              UpperCAmelCase__	:      str     							=					getattr(self.generator     ,	'forced_eos_token_id'     ,	UpperCamelCase_      )



      @classmethod
      def  __snake_case							(   cls     ,	UpperCamelCase_     ,	UpperCamelCase_     ,	**UpperCamelCase_      ):
          return cls(question_encoder=question_encoder_config.to_dict()     ,	generator=generator_config.to_dict()     ,	**UpperCamelCase_      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      str     							=					copy.deepcopy(self.__dict__      )
          UpperCAmelCase__	:      int     							=					self.question_encoder.to_dict()
          UpperCAmelCase__	:      Tuple     							=					self.generator.to_dict()
          UpperCAmelCase__	:      List[str]     							=					self.__class__.model_type
          return output



"""simple docstring"""



from typing import Any





class 				a			:



      def __init__(   self     ,	UpperCamelCase_      ):
          UpperCAmelCase__	:      Optional[Any]     							=					data
          UpperCAmelCase__	:      List[str]     							=					None



      def __repr__(   self      ):
          return F'''Node({self.data})'''





class 				a			:



      def __init__(   self      ):
          UpperCAmelCase__	:      Any     							=					None



      def __iter__(   self      ):
          UpperCAmelCase__	:      List[str]     							=					self.head
          while node:
              yield node.data
              UpperCAmelCase__	:      Optional[int]     							=					node.next



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



      def __repr__(   self      ):
          return "->".join([str(UpperCamelCase_      ) for item in self]      )



      def __getitem__(   self     ,	UpperCamelCase_      ):
          if not 0 <= index < len(self      ):
              raise ValueError('list index out of range.'      )
          for i, node in enumerate(self      ):
              if i == index:
                  return node
          return None



      def __setitem__(   self     ,	UpperCamelCase_     ,	UpperCamelCase_      ):
          if not 0 <= index < len(self      ):
              raise ValueError('list index out of range.'      )
          UpperCAmelCase__	:      List[str]     							=					self.head
          for _ in range(UpperCamelCase_      ):
              UpperCAmelCase__	:      Optional[Any]     							=					current.next
          UpperCAmelCase__	:      List[str]     							=					data



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          self.insert_nth(len(self      )     ,	UpperCamelCase_      )



      def  __snake_case							(   self     ,	UpperCamelCase_      ):
          self.insert_nth(0     ,	UpperCamelCase_      )



      def  __snake_case							(   self     ,	UpperCamelCase_     ,	UpperCamelCase_      ):
          if not 0 <= index <= len(self      ):
              raise IndexError('list index out of range'      )
          UpperCAmelCase__	:      str     							=					Node(UpperCamelCase_      )
          if self.head is None:
              UpperCAmelCase__	:      Tuple     							=					new_node
          elif index == 0:
              UpperCAmelCase__	:      Optional[int]     							=					self.head  # link new_node to head
              UpperCAmelCase__	:      Any     							=					new_node
          else:
              UpperCAmelCase__	:      Dict     							=					self.head
              for _ in range(index - 1      ):
                  UpperCAmelCase__	:      Tuple     							=					temp.next
              UpperCAmelCase__	:      int     							=					temp.next
              UpperCAmelCase__	:      Tuple     							=					new_node



      def  __snake_case							(   self      ):  # print every node data
          print(self      )



      def  __snake_case							(   self      ):
          return self.delete_nth(0      )



      def  __snake_case							(   self      ):  # delete from tail
          return self.delete_nth(len(self      ) - 1      )



      def  __snake_case							(   self     ,	UpperCamelCase_ = 0      ):
          if not 0 <= index <= len(self      ) - 1:  # test if index is valid
              raise IndexError('List index out of range.'      )
          UpperCAmelCase__	:      Union[str, Any]     							=					self.head  # default first node
          if index == 0:
              UpperCAmelCase__	:      Dict     							=					self.head.next
          else:
              UpperCAmelCase__	:      List[Any]     							=					self.head
              for _ in range(index - 1      ):
                  UpperCAmelCase__	:      Any     							=					temp.next
              UpperCAmelCase__	:      Dict     							=					temp.next
              UpperCAmelCase__	:      Tuple     							=					temp.next.next
          return delete_node.data



      def  __snake_case							(   self      ):
          return self.head is None



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[Any]     							=					None
          UpperCAmelCase__	:      str     							=					self.head

          while current:
              # Store the current node's next node.
              UpperCAmelCase__	:      Any     							=					current.next
              # Make the current node's next point backwards
              UpperCAmelCase__	:      Optional[int]     							=					prev
              # Make the previous node be the current node
              UpperCAmelCase__	:      List[Any]     							=					current
              # Make the current node the next node (to progress iteration)
              UpperCAmelCase__	:      int     							=					next_node
          # Return prev in order to put the head at the end
          UpperCAmelCase__	:      str     							=					prev




def 					lowerCamelCase   (     ):
    UpperCAmelCase__	:      Dict     							=					LinkedList()
    assert linked_list.is_empty() is True
    assert str(_snake_case ) == ""

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

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

    for i in range(10 ):
        assert len(_snake_case ) == i
        linked_list.insert_nth(_snake_case    ,i + 1 )
    assert str(_snake_case ) == "->".join(str(_snake_case ) for i in range(1    ,11 ) )

    linked_list.insert_head(0 )
    linked_list.insert_tail(11 )
    assert str(_snake_case ) == "->".join(str(_snake_case ) for i in range(0    ,12 ) )

    assert linked_list.delete_head() == 0
    assert linked_list.delete_nth(9 ) == 10
    assert linked_list.delete_tail() == 11
    assert len(_snake_case ) == 9
    assert str(_snake_case ) == "->".join(str(_snake_case ) for i in range(1    ,10 ) )

    assert all(linked_list[i] == i + 1 for i in range(0    ,9 ) ) is True

    for i in range(0    ,9 ):
        UpperCAmelCase__	:      Any     							=					-i
    assert all(linked_list[i] == -i for i in range(0    ,9 ) ) is True

    linked_list.reverse()
    assert str(_snake_case ) == "->".join(str(_snake_case ) for i in range(-8    ,1 ) )
def 					lowerCamelCase   (     ):
    UpperCAmelCase__	:      int     							=					[
        -9,
        100,
        Node(77345112 ),
        'dlrow olleH',
        7,
        5555,
        0,
        -192.55555,
        'Hello, world!',
        77.9,
        Node(10 ),
        None,
        None,
        12.20,
    ]
    UpperCAmelCase__	:      Dict     							=					LinkedList()

    for i in test_input:
        linked_list.insert_tail(_snake_case )

    # Check if it's empty or not
    assert linked_list.is_empty() is False
    assert (
        str(_snake_case ) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
        "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
    )

    # Delete the head
    UpperCAmelCase__	:      Any     							=					linked_list.delete_head()
    assert result == -9
    assert (
        str(_snake_case ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
        "Hello, world!->77.9->Node(10)->None->None->12.2"
    )

    # Delete the tail
    UpperCAmelCase__	:      Union[str, Any]     							=					linked_list.delete_tail()
    assert result == 12.2
    assert (
        str(_snake_case ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
        "Hello, world!->77.9->Node(10)->None->None"
    )

    # Delete a node in specific location in linked list
    UpperCAmelCase__	:      Dict     							=					linked_list.delete_nth(10 )
    assert result is None
    assert (
        str(_snake_case ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
        "Hello, world!->77.9->Node(10)->None"
    )

    # Add a Node instance to its head
    linked_list.insert_head(Node('Hello again, world!' ) )
    assert (
        str(_snake_case )
        == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
        "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
    )

    # Add None to its tail
    linked_list.insert_tail(_snake_case )
    assert (
        str(_snake_case )
        == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
        "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
    )

    # Reverse the linked list
    linked_list.reverse()
    assert (
        str(_snake_case )
        == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
        "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
    )
def 					lowerCamelCase   (     ):
    from doctest import testmod

    testmod()

    UpperCAmelCase__	:      Optional[Any]     							=					LinkedList()
    linked_list.insert_head(input('Inserting 1st at head ' ).strip() )
    linked_list.insert_head(input('Inserting 2nd at head ' ).strip() )
    print('\nPrint list:' )
    linked_list.print_list()
    linked_list.insert_tail(input('\nInserting 1st at tail ' ).strip() )
    linked_list.insert_tail(input('Inserting 2nd at tail ' ).strip() )
    print('\nPrint list:' )
    linked_list.print_list()
    print('\nDelete head' )
    linked_list.delete_head()
    print('Delete tail' )
    linked_list.delete_tail()
    print('\nPrint list:' )
    linked_list.print_list()
    print('\nReverse linked list' )
    linked_list.reverse()
    print('\nPrint list:' )
    linked_list.print_list()
    print('\nString representation of linked list:' )
    print(_snake_case )
    print('\nReading/changing Node data using indexing:' )
    print(F'''Element at Position 1: {linked_list[1]}''' )
    UpperCAmelCase__	:      List[Any]     							=					input('Enter New Value: ' ).strip()
    print('New list:' )
    print(_snake_case )
    print(F'''length of linked_list is : {len(_snake_case )}''' )


if __name__ == "__main__":
    main()

