





"""simple docstring"""





from typing import Any
class 		SCREAMING_SNAKE_CASE_							:
				"""simple docstring"""




				def __init__(     self  :Tuple						,    __lowercase  :Any			):
											__lowerCamelCase      :      str         =data
											__lowerCamelCase      :      Any         =None




				def __repr__(     self  :Optional[Any]			):
											return f'Node({self.data})'

class 		SCREAMING_SNAKE_CASE_							:
				"""simple docstring"""




				def __init__(     self  :Optional[int]			):
											__lowerCamelCase      :      Union[str, Any]         =None




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




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




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




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




				def 					__lowercase  (     self  :Tuple						,    __lowercase  :Any			):
											self.insert_nth(len(self			)						,    __lowercase			)




				def 					__lowercase  (     self  :int						,    __lowercase  :Any			):
											self.insert_nth(0						,    __lowercase			)




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




				def 					__lowercase  (     self  :Tuple			):  # print every node data
											print(self			)




				def 					__lowercase  (     self  :List[str]			):
											return self.delete_nth(0			)




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




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




				def 					__lowercase  (     self  :Any			):
											return self.head is None




				def 					__lowercase  (     self  :Tuple			):
											__lowerCamelCase      :      Any         =None
											__lowerCamelCase      :      Optional[int]         =self.head

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



def 				lowerCAmelCase_			(      ):


							'''simple docstring'''







							__lowerCamelCase      :      Tuple         =LinkedList()
							assert linked_list.is_empty() is True
							assert str(SCREAMING_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(SCREAMING_SNAKE_CASE   ) == i
														linked_list.insert_nth(SCREAMING_SNAKE_CASE    ,						i + 1   )
							assert str(SCREAMING_SNAKE_CASE   ) == "->".join(str(SCREAMING_SNAKE_CASE   ) for i in range(1    ,						11   )   )

							linked_list.insert_head(0   )
							linked_list.insert_tail(11   )
							assert str(SCREAMING_SNAKE_CASE   ) == "->".join(str(SCREAMING_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(SCREAMING_SNAKE_CASE   ) == 9
							assert str(SCREAMING_SNAKE_CASE   ) == "->".join(str(SCREAMING_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   ):
														__lowerCamelCase      :      List[Any]         =-i
							assert all(linked_list[i] == -i for i in range(0    ,						9   )   ) is True

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



def 				lowerCAmelCase_			(      ):


							'''simple docstring'''







							__lowerCamelCase      :      Any         =[
							    -9,
							    100,
							    Node(77345112   ),
							    '''dlrow olleH''',
							    7,
							    5555,
							    0,
							    -192.55_555,
							    '''Hello, world!''',
							    77.9,
							    Node(10   ),
							    None,
							    None,
							    12.20,
							]
							__lowerCamelCase      :      str         =LinkedList()

							for i in test_input:
														linked_list.insert_tail(SCREAMING_SNAKE_CASE   )

							# Check if it's empty or not
							assert linked_list.is_empty() is False
							assert (
							    str(SCREAMING_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
							__lowerCamelCase      :      str         =linked_list.delete_head()
							assert result == -9
							assert (
							    str(SCREAMING_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
							__lowerCamelCase      :      Union[str, Any]         =linked_list.delete_tail()
							assert result == 12.2
							assert (
							    str(SCREAMING_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
							__lowerCamelCase      :      Union[str, Any]         =linked_list.delete_nth(10   )
							assert result is None
							assert (
							    str(SCREAMING_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(SCREAMING_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(SCREAMING_SNAKE_CASE   )
							assert (
							    str(SCREAMING_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(SCREAMING_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_			(      ):


							'''simple docstring'''







							from doctest import testmod

							testmod()

							__lowerCamelCase      :      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(SCREAMING_SNAKE_CASE   )
							print('''\nReading/changing Node data using indexing:'''   )
							print(F'Element at Position 1: {linked_list[1]}'   )
							__lowerCamelCase      :      Any         =input('''Enter New Value: '''   ).strip()
							print('''New list:'''   )
							print(SCREAMING_SNAKE_CASE   )
							print(F'length of linked_list is : {len(SCREAMING_SNAKE_CASE   )}'   )


if __name__ == "__main__":
							main()











"""simple docstring"""





from typing import Dict, List

from nltk.translate import gleu_score

import datasets
from datasets import MetricInfo


_UpperCamelCase							=      '\\n@misc{wu2016googles,\n      title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n      author={Yonghui Wu and Mike Schuster and Zhifeng Chen and Quoc V. Le and Mohammad Norouzi and Wolfgang Macherey\n              and Maxim Krikun and Yuan Cao and Qin Gao and Klaus Macherey and Jeff Klingner and Apurva Shah and Melvin\n              Johnson and Xiaobing Liu and Łukasz Kaiser and Stephan Gouws and Yoshikiyo Kato and Taku Kudo and Hideto\n              Kazawa and Keith Stevens and George Kurian and Nishant Patil and Wei Wang and Cliff Young and\n              Jason Smith and Jason Riesa and Alex Rudnick and Oriol Vinyals and Greg Corrado and Macduff Hughes\n              and Jeffrey Dean},\n      year={2016},\n      eprint={1609.08144},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL}\n}\n'

_UpperCamelCase							=      '\\nThe BLEU score has some undesirable properties when used for single\nsentences, as it was designed to be a corpus measure. We therefore\nuse a slightly different score for our RL experiments which we call\nthe \'GLEU score\'. For the GLEU score, we record all sub-sequences of\n1, 2, 3 or 4 tokens in output and target sequence (n-grams). We then\ncompute a recall, which is the ratio of the number of matching n-grams\nto the number of total n-grams in the target (ground truth) sequence,\nand a precision, which is the ratio of the number of matching n-grams\nto the number of total n-grams in the generated output sequence. Then\nGLEU score is simply the minimum of recall and precision. This GLEU\nscore\'s range is always between 0 (no matches) and 1 (all match) and\nit is symmetrical when switching output and target. According to\nour experiments, GLEU score correlates quite well with the BLEU\nmetric on a corpus level but does not have its drawbacks for our per\nsentence reward objective.\n'

_UpperCamelCase							=      '\\nComputes corpus-level Google BLEU (GLEU) score of translated segments against one or more references.\nInstead of averaging the sentence level GLEU scores (i.e. macro-average precision), Wu et al. (2016) sum up the matching\ntokens and the max of hypothesis and reference tokens for each sentence, then compute using the aggregate values.\n\nArgs:\n    predictions (list of str): list of translations to score.\n        Each translation should be tokenized into a list of tokens.\n    references (list of list of str): list of lists of references for each translation.\n        Each reference should be tokenized into a list of tokens.\n    min_len (int): The minimum order of n-gram this function should extract. Defaults to 1.\n    max_len (int): The maximum order of n-gram this function should extract. Defaults to 4.\n\nReturns:\n    \'google_bleu\': google_bleu score\n\nExamples:\n    Example 1:\n        >>> hyp1 = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'which\',\n        ...         \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'always\',\n        ...         \'disobeys\', \'the\', \'commands\', \'of\', \'the\', \'cat\']\n        >>> ref1a = [\'It\', \'is\', \'the\', \'guiding\', \'principle\', \'which\',\n        ...          \'guarantees\', \'the\', \'rubber\', \'duck\', \'forces\', \'never\',\n        ...          \'being\', \'under\', \'the\', \'command\', \'of\', \'the\', \'cat\']\n\n        >>> hyp2 = [\'he\', \'read\', \'the\', \'book\', \'because\', \'he\', \'was\',\n        ...         \'interested\', \'in\', \'world\', \'history\']\n        >>> ref2a = [\'he\', \'was\', \'interested\', \'in\', \'world\', \'history\',\n        ...          \'because\', \'he\', \'read\', \'the\', \'book\']\n\n        >>> list_of_references = [[ref1a], [ref2a]]\n        >>> hypotheses = [hyp1, hyp2]\n        >>> google_bleu = datasets.load_metric("google_bleu")\n        >>> results = google_bleu.compute(predictions=hypotheses, references=list_of_references)\n        >>> print(round(results["google_bleu"], 2))\n        0.44\n\n    Example 2:\n        >>> hyp1 = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'which\',\n        ...         \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'always\',\n        ...         \'disobeys\', \'the\', \'commands\', \'of\', \'the\', \'cat\']\n        >>> ref1a = [\'It\', \'is\', \'the\', \'guiding\', \'principle\', \'which\',\n        ...          \'guarantees\', \'the\', \'rubber\', \'duck\', \'forces\', \'never\',\n        ...          \'being\', \'under\', \'the\', \'command\', \'of\', \'the\', \'cat\']\n        >>> ref1b = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'that\',\n        ...          \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'will\', \'never\',\n        ...          \'heed\', \'the\', \'cat\', \'commands\']\n        >>> ref1c = [\'It\', \'is\', \'the\', \'practical\', \'guide\', \'for\', \'the\',\n        ...          \'rubber\', \'duck\', \'army\', \'never\', \'to\', \'heed\', \'the\', \'directions\',\n        ...          \'of\', \'the\', \'cat\']\n\n        >>> hyp2 = [\'he\', \'read\', \'the\', \'book\', \'because\', \'he\', \'was\',\n        ...         \'interested\', \'in\', \'world\', \'history\']\n        >>> ref2a = [\'he\', \'was\', \'interested\', \'in\', \'world\', \'history\',\n        ...          \'because\', \'he\', \'read\', \'the\', \'book\']\n\n        >>> list_of_references = [[ref1a, ref1b, ref1c], [ref2a]]\n        >>> hypotheses = [hyp1, hyp2]\n        >>> google_bleu = datasets.load_metric("google_bleu")\n        >>> results = google_bleu.compute(predictions=hypotheses, references=list_of_references)\n        >>> print(round(results["google_bleu"], 2))\n        0.61\n\n    Example 3:\n        >>> hyp1 = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'which\',\n        ...         \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'always\',\n        ...         \'disobeys\', \'the\', \'commands\', \'of\', \'the\', \'cat\']\n        >>> ref1a = [\'It\', \'is\', \'the\', \'guiding\', \'principle\', \'which\',\n        ...          \'guarantees\', \'the\', \'rubber\', \'duck\', \'forces\', \'never\',\n        ...          \'being\', \'under\', \'the\', \'command\', \'of\', \'the\', \'cat\']\n        >>> ref1b = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'that\',\n        ...          \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'will\', \'never\',\n        ...          \'heed\', \'the\', \'cat\', \'commands\']\n        >>> ref1c = [\'It\', \'is\', \'the\', \'practical\', \'guide\', \'for\', \'the\',\n        ...          \'rubber\', \'duck\', \'army\', \'never\', \'to\', \'heed\', \'the\', \'directions\',\n        ...          \'of\', \'the\', \'cat\']\n\n        >>> hyp2 = [\'he\', \'read\', \'the\', \'book\', \'because\', \'he\', \'was\',\n        ...         \'interested\', \'in\', \'world\', \'history\']\n        >>> ref2a = [\'he\', \'was\', \'interested\', \'in\', \'world\', \'history\',\n        ...          \'because\', \'he\', \'read\', \'the\', \'book\']\n\n        >>> list_of_references = [[ref1a, ref1b, ref1c], [ref2a]]\n        >>> hypotheses = [hyp1, hyp2]\n        >>> google_bleu = datasets.load_metric("google_bleu")\n        >>> results = google_bleu.compute(predictions=hypotheses, references=list_of_references, min_len=2)\n        >>> print(round(results["google_bleu"], 2))\n        0.53\n\n    Example 4:\n        >>> hyp1 = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'which\',\n        ...         \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'always\',\n        ...         \'disobeys\', \'the\', \'commands\', \'of\', \'the\', \'cat\']\n        >>> ref1a = [\'It\', \'is\', \'the\', \'guiding\', \'principle\', \'which\',\n        ...          \'guarantees\', \'the\', \'rubber\', \'duck\', \'forces\', \'never\',\n        ...          \'being\', \'under\', \'the\', \'command\', \'of\', \'the\', \'cat\']\n        >>> ref1b = [\'It\', \'is\', \'a\', \'guide\', \'to\', \'action\', \'that\',\n        ...          \'ensures\', \'that\', \'the\', \'rubber\', \'duck\', \'will\', \'never\',\n        ...          \'heed\', \'the\', \'cat\', \'commands\']\n        >>> ref1c = [\'It\', \'is\', \'the\', \'practical\', \'guide\', \'for\', \'the\',\n        ...          \'rubber\', \'duck\', \'army\', \'never\', \'to\', \'heed\', \'the\', \'directions\',\n        ...          \'of\', \'the\', \'cat\']\n\n        >>> hyp2 = [\'he\', \'read\', \'the\', \'book\', \'because\', \'he\', \'was\',\n        ...         \'interested\', \'in\', \'world\', \'history\']\n        >>> ref2a = [\'he\', \'was\', \'interested\', \'in\', \'world\', \'history\',\n        ...          \'because\', \'he\', \'read\', \'the\', \'book\']\n\n        >>> list_of_references = [[ref1a, ref1b, ref1c], [ref2a]]\n        >>> hypotheses = [hyp1, hyp2]\n        >>> google_bleu = datasets.load_metric("google_bleu")\n        >>> results = google_bleu.compute(predictions=hypotheses,references=list_of_references, min_len=2, max_len=6)\n        >>> print(round(results["google_bleu"], 2))\n        0.4\n'
@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION       ,  _KWARGS_DESCRIPTION   )
class 		SCREAMING_SNAKE_CASE_							(    datasets.Metric   ):
				"""simple docstring"""




				def 					__lowercase  (     self  :Optional[Any]			):
											return datasets.MetricInfo(
											    description=_DESCRIPTION						,    citation=_CITATION						,    inputs_description=_KWARGS_DESCRIPTION						,    features=datasets.Features(
											        {
											            '''predictions''': datasets.Sequence(datasets.Value('''string'''						,    id='''token'''			)						,    id='''sequence'''			),
											            '''references''': datasets.Sequence(
											                datasets.Sequence(datasets.Value('''string'''						,    id='''token'''			)						,    id='''sequence'''			)						,    id='''references'''			),
											        }			)						,    )




				def 					__lowercase  (     self  :Optional[Any]						,    __lowercase  :List[List[List[str]]]						,    __lowercase  :List[List[str]]						,    __lowercase  :int = 1						,    __lowercase  :int = 4						,    ):
											return {
											    "google_bleu": gleu_score.corpus_gleu(
											        list_of_references=__lowercase						,    hypotheses=__lowercase						,    min_len=__lowercase						,    max_len=__lowercase			)
											}




