



"""simple docstring"""
from typing import Any



class    SCREAMING_SNAKE_CASE__						:

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   List[str]:





    '''simple docstring'''




    UpperCAmelCase			:      str			=			data
    UpperCAmelCase			:      str			=			None




   def __repr__(     self		)						->   str:





    '''simple docstring'''




    return F"Node({self.data})"



class    SCREAMING_SNAKE_CASE__						:

   def __init__(     self		)						->   Dict:





    '''simple docstring'''




    UpperCAmelCase			:      Tuple			=			None

   def __iter__(     self		)						->   Any:





    '''simple docstring'''




    UpperCAmelCase			:      Dict			=			self.head
    while node:
     yield node.data
     UpperCAmelCase			:      Optional[Any]			=			node.next

   def __len__(     self		)						->   int:





    '''simple docstring'''




    return sum(1 for _ in self		)

   def __repr__(     self		)						->   str:





    '''simple docstring'''




    return "->".join([str(_SCREAMING_SNAKE_CASE		) for item in self]		)

   def __getitem__(     self   ,  _SCREAMING_SNAKE_CASE		)						->   Any:





    '''simple docstring'''




    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   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)						->   None:





    '''simple docstring'''




    if not 0 <= index < len(self		):
     raise ValueError("""list index out of range."""		)
    UpperCAmelCase			:      int			=			self.head
    for _ in range(_SCREAMING_SNAKE_CASE		):
     UpperCAmelCase			:      Optional[int]			=			current.next
    UpperCAmelCase			:      List[Any]			=			data

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   None:





    '''simple docstring'''




    self.insert_nth(len(self		)   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   None:





    '''simple docstring'''




    self.insert_nth(0   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)						->   None:





    '''simple docstring'''




    if not 0 <= index <= len(self		):
     raise IndexError("""list index out of range"""		)
    UpperCAmelCase			:      Tuple			=			Node(_SCREAMING_SNAKE_CASE		)
    if self.head is None:
     UpperCAmelCase			:      List[str]			=			new_node
    elif index == 0:
     UpperCAmelCase			:      Dict			=			self.head  # link new_node to head
     UpperCAmelCase			:      Any			=			new_node
    else:
     UpperCAmelCase			:      List[Any]			=			self.head
     for _ in range(index - 1		):
      UpperCAmelCase			:      Union[str, Any]			=			temp.next
     UpperCAmelCase			:      int			=			temp.next
     UpperCAmelCase			:      List[Any]			=			new_node

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   None:  # print every node data





    '''simple docstring'''




    print(self		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Any:





    '''simple docstring'''




    return self.delete_nth(0		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Any:  # delete from tail





    '''simple docstring'''




    return self.delete_nth(len(self		) - 1		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE = 0		)						->   Any:





    '''simple docstring'''




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

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   bool:





    '''simple docstring'''




    return self.head is None




   def 			SCREAMING_SNAKE_CASE  (     self		)						->   None:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			None
    UpperCAmelCase			:      str			=			self.head

    while current:
     # Store the current node's next node.
     UpperCAmelCase			:      Tuple			=			current.next
     # Make the current node's next point backwards
     UpperCAmelCase			:      Any			=			prev
     # Make the previous node be the current node
     UpperCAmelCase			:      Tuple			=			current
     # Make the current node the next node (to progress iteration)
     UpperCAmelCase			:      Any			=			next_node
    # Return prev in order to put the head at the end
    UpperCAmelCase			:      Any			=			prev

def    _snake_case		(		):
 UpperCAmelCase			:      List[str]			=			LinkedList()
 assert linked_list.is_empty() is True
 assert str(UpperCamelCase		) == ""

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

 linked_list.insert_head(0		)
 linked_list.insert_tail(11		)
 assert str(UpperCamelCase		) == "->".join(str(UpperCamelCase		) 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(UpperCamelCase		) == 9
 assert str(UpperCamelCase		) == "->".join(str(UpperCamelCase		) 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			:      Dict			=			-i
 assert all(linked_list[i] == -i for i in range(0    ,	9		)		) is True

 linked_list.reverse()
 assert str(UpperCamelCase		) == "->".join(str(UpperCamelCase		) for i in range(-8    ,	1		)		)

def    _snake_case		(		):
 UpperCAmelCase			:      Any			=			[
     -9,
     100,
     Node(77345112		),
     """dlrow olleH""",
     7,
     5555,
     0,
     -192.55555,
     """Hello, world!""",
     77.9,
     Node(10		),
     None,
     None,
     12.20,
 ]
 UpperCAmelCase			:      Optional[Any]			=			LinkedList()

 for i in test_input:
  linked_list.insert_tail(UpperCamelCase		)

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

 # Delete the tail
 UpperCAmelCase			:      List[Any]			=			linked_list.delete_tail()
 assert result == 12.2
 assert (
     str(UpperCamelCase		) == "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			:      Tuple			=			linked_list.delete_nth(10		)
 assert result is None
 assert (
     str(UpperCamelCase		) == "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(UpperCamelCase		)
     == "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(UpperCamelCase		)
 assert (
     str(UpperCamelCase		)
     == "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(UpperCamelCase		)
     == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
     "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
 )

def    _snake_case		(		):
 from doctest import testmod

 testmod()

 UpperCAmelCase			:      List[str]			=			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(UpperCamelCase		)
 print("""\nReading/changing Node data using indexing:"""		)
 print(F"Element at Position 1: {linked_list[1]}"		)
 UpperCAmelCase			:      str			=			input("""Enter New Value: """		).strip()
 print("""New list:"""		)
 print(UpperCamelCase		)
 print(F"length of linked_list is : {len(UpperCamelCase		)}"		)


if __name__ == "__main__":
      main()





"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional

from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


A:     Optional[int]										=	logging.get_logger(__name__)

A:     Union[str, Any]										=	{
    "EleutherAI/gpt-neo-1.3B": "https://huggingface.co/EleutherAI/gpt-neo-1.3B/resolve/main/config.json",
    # See all GPTNeo models at https://huggingface.co/models?filter=gpt_neo
}



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):
   __lowerCAmelCase						:     List[str]		=		'gpt_neo'
   __lowerCAmelCase						:     Any		=		['past_key_values']
   __lowerCAmelCase						:     int		=		{'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE=50257   ,  _SCREAMING_SNAKE_CASE=2048   ,  _SCREAMING_SNAKE_CASE=2048   ,  _SCREAMING_SNAKE_CASE=24   ,  _SCREAMING_SNAKE_CASE=[[["global", "local"], 12]]   ,  _SCREAMING_SNAKE_CASE=16   ,  _SCREAMING_SNAKE_CASE=None   ,  _SCREAMING_SNAKE_CASE=256   ,  _SCREAMING_SNAKE_CASE="gelu_new"   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.1   ,  _SCREAMING_SNAKE_CASE=1E-5   ,  _SCREAMING_SNAKE_CASE=0.02   ,  _SCREAMING_SNAKE_CASE=True   ,  _SCREAMING_SNAKE_CASE=50256   ,  _SCREAMING_SNAKE_CASE=50256   ,  **_SCREAMING_SNAKE_CASE   ,  )						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      int			=			vocab_size
    UpperCAmelCase			:      List[Any]			=			max_position_embeddings
    UpperCAmelCase			:      str			=			hidden_size
    UpperCAmelCase			:      Dict			=			num_layers
    UpperCAmelCase			:      List[Any]			=			num_heads
    UpperCAmelCase			:      Optional[Any]			=			intermediate_size
    UpperCAmelCase			:      Dict			=			window_size
    UpperCAmelCase			:      int			=			activation_function
    UpperCAmelCase			:      Tuple			=			resid_dropout
    UpperCAmelCase			:      int			=			embed_dropout
    UpperCAmelCase			:      Optional[int]			=			attention_dropout
    UpperCAmelCase			:      Optional[int]			=			classifier_dropout
    UpperCAmelCase			:      Any			=			layer_norm_epsilon
    UpperCAmelCase			:      Union[str, Any]			=			initializer_range
    UpperCAmelCase			:      List[str]			=			use_cache

    UpperCAmelCase			:      Union[str, Any]			=			bos_token_id
    UpperCAmelCase			:      str			=			eos_token_id

    UpperCAmelCase			:      Union[str, Any]			=			attention_types
    UpperCAmelCase			:      int			=			self.expand_attention_types_params(_SCREAMING_SNAKE_CASE		)

    if len(self.attention_layers		) != self.num_layers:
     raise ValueError(
         """Configuration for convolutional module is incorrect. """
         """It is required that `len(config.attention_layers)` == `config.num_layers` """
         F"but is `len(config.attention_layers) = {len(self.attention_layers		)}`, "
         F"`config.num_layers = {self.num_layers}`. "
         """`config.attention_layers` is prepared using `config.attention_types`. """
         """Please verify the value of `config.attention_types` argument."""		)

    super().__init__(bos_token_id=_SCREAMING_SNAKE_CASE   ,  eos_token_id=_SCREAMING_SNAKE_CASE   ,  **_SCREAMING_SNAKE_CASE		)




   @staticmethod
   def 			SCREAMING_SNAKE_CASE  (     _SCREAMING_SNAKE_CASE		)						->   Union[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			[]
    for item in attention_types:
     for _ in range(item[1]		):
      attentions.extend(item[0]		)
    return attentions

def    _snake_case		(		UpperCamelCase		:	Union[str, Any]    ,	UpperCamelCase		:	Union[str, Any]    ,	UpperCamelCase		:	Optional[Any]    ,	UpperCamelCase		:	Dict		):
 import torch

 UpperCAmelCase			:      Optional[Any]			=			input.size()
 UpperCAmelCase			:      int			=			len(UpperCamelCase		)
 UpperCAmelCase			:      Optional[Any]			=			shape[dimension]

 UpperCAmelCase			:      Union[str, Any]			=			torch.arange(0    ,	UpperCamelCase    ,	UpperCamelCase		)
 UpperCAmelCase			:      List[Any]			=			torch.div(sizedim - size    ,	UpperCamelCase    ,	rounding_mode="""floor"""		) + 1
 UpperCAmelCase			:      Optional[Any]			=			torch.arange(UpperCamelCase		) + low_indices[:min_length][:, None]

 UpperCAmelCase			:      List[Any]			=			[slice(UpperCamelCase		)] * rank
 UpperCAmelCase			:      Optional[Any]			=			indices
 UpperCAmelCase			:      Optional[Any]			=			input[s]

 UpperCAmelCase			:      List[Any]			=			list(range(0    ,	rank + 1		)		)
 perm.append(perm.pop(dimension + 1		)		)

 return sliced.permute(UpperCamelCase		)

def    _snake_case		(		UpperCamelCase		:	Tuple    ,	UpperCamelCase		:	Dict		):
 import torch

 UpperCAmelCase			:      List[str]			=			torch.arange(1    ,	UpperCamelCase		)
 UpperCAmelCase			:      Any			=			torch.remainder(UpperCamelCase    ,	UpperCamelCase		)
 UpperCAmelCase			:      Union[str, Any]			=			remainders == 0
 UpperCAmelCase			:      str			=			candidates[divisor_indices]
 UpperCAmelCase			:      Optional[int]			=			torch.max(UpperCamelCase		)
 return largest_divisor, torch.div(UpperCamelCase    ,	UpperCamelCase    ,	rounding_mode="""floor"""		)



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Mapping[str, Mapping[int, str]]:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			OrderedDict({"""input_ids""": {0: """batch""", 1: """sequence"""}}		)
    if self.use_past:
     self.fill_with_past_key_values_(_SCREAMING_SNAKE_CASE   ,  direction="""inputs"""		)
     UpperCAmelCase			:      str			=			{0: """batch""", 1: """past_sequence + sequence"""}
    else:
     UpperCAmelCase			:      List[str]			=			{0: """batch""", 1: """sequence"""}

    return common_inputs

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return self._config.num_heads

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE = -1   ,  _SCREAMING_SNAKE_CASE = -1   ,  _SCREAMING_SNAKE_CASE = False   ,  _SCREAMING_SNAKE_CASE = None   ,  )						->   Mapping[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			super(_SCREAMING_SNAKE_CASE   ,  self		).generate_dummy_inputs(
        _SCREAMING_SNAKE_CASE   ,  batch_size=_SCREAMING_SNAKE_CASE   ,  seq_length=_SCREAMING_SNAKE_CASE   ,  is_pair=_SCREAMING_SNAKE_CASE   ,  framework=_SCREAMING_SNAKE_CASE		)

    # We need to order the input in the way they appears in the forward()
    UpperCAmelCase			:      Dict			=			OrderedDict({"""input_ids""": common_inputs["""input_ids"""]}		)

    # Need to add the past_keys
    if self.use_past:
     if not is_torch_available():
      raise ValueError("""Cannot generate dummy past_keys inputs without PyTorch installed."""		)
     else:
      import torch

      UpperCAmelCase			,	UpperCAmelCase			:      List[Any]			=			common_inputs["""input_ids"""].shape
      # Not using the same length for past_key_values
      UpperCAmelCase			:      Any			=			seqlen + 2
      UpperCAmelCase			:      str			=			(
          batch,
          self.num_attention_heads,
          past_key_values_length,
          self._config.hidden_size // self.num_attention_heads,
      )
      UpperCAmelCase			:      Optional[int]			=			[
          (torch.zeros(_SCREAMING_SNAKE_CASE		), torch.zeros(_SCREAMING_SNAKE_CASE		)) for _ in range(self.num_layers		)
      ]

    UpperCAmelCase			:      List[str]			=			common_inputs["""attention_mask"""]
    if self.use_past:
     UpperCAmelCase			:      str			=			ordered_inputs["""attention_mask"""].dtype
     UpperCAmelCase			:      int			=			torch.cat(
         [ordered_inputs["""attention_mask"""], torch.ones(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE   ,  dtype=_SCREAMING_SNAKE_CASE		)]   ,  dim=1		)

    return ordered_inputs




   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return 13
