





import absl  # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk  # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy  # noqa: F401 # Here to have a nice missing dependency error message early on
import six  # noqa: F401 # Here to have a nice missing dependency error message early on
from rouge_score import rouge_scorer, scoring

import datasets


_lowerCamelCase :    Any  							= '''\
@inproceedings{lin-2004-rouge,
    title = \"{ROUGE}: A Package for Automatic Evaluation of Summaries\",
    author = \"Lin, Chin-Yew\",
    booktitle = \"Text Summarization Branches Out\",
    month = jul,
    year = \"2004\",
    address = \"Barcelona, Spain\",
    publisher = \"Association for Computational Linguistics\",
    url = \"https://www.aclweb.org/anthology/W04-1013\",
    pages = \"74--81\",
}
'''

_lowerCamelCase :    Optional[int]  							= '''\
ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics and a software package used for
evaluating automatic summarization and machine translation software in natural language processing.
The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced) summary or translation.

Note that ROUGE is case insensitive, meaning that upper case letters are treated the same way as lower case letters.

This metrics is a wrapper around Google Research reimplementation of ROUGE:
https://github.com/google-research/google-research/tree/master/rouge
'''

_lowerCamelCase :    List[str]  							= '''
Calculates average rouge scores for a list of hypotheses and references
Args:
    predictions: list of predictions to score. Each prediction
        should be a string with tokens separated by spaces.
    references: list of reference for each prediction. Each
        reference should be a string with tokens separated by spaces.
    rouge_types: A list of rouge types to calculate.
        Valid names:
        `\"rouge{n}\"` (e.g. `\"rouge1\"`, `\"rouge2\"`) where: {n} is the n-gram based scoring,
        `\"rougeL\"`: Longest common subsequence based scoring.
        `\"rougeLSum\"`: rougeLsum splits text using `\"\n\"`.
        See details in https://github.com/huggingface/datasets/issues/617
    use_stemmer: Bool indicating whether Porter stemmer should be used to strip word suffixes.
    use_aggregator: Return aggregates if this is set to True
Returns:
    rouge1: rouge_1 (precision, recall, f1),
    rouge2: rouge_2 (precision, recall, f1),
    rougeL: rouge_l (precision, recall, f1),
    rougeLsum: rouge_lsum (precision, recall, f1)
Examples:

    >>> rouge = datasets.load_metric(\'rouge\')
    >>> predictions = [\"hello there\", \"general kenobi\"]
    >>> references = [\"hello there\", \"general kenobi\"]
    >>> results = rouge.compute(predictions=predictions, references=references)
    >>> print(list(results.keys()))
    [\'rouge1\', \'rouge2\', \'rougeL\', \'rougeLsum\']
    >>> print(results[\"rouge1\"])
    AggregateScore(low=Score(precision=1.0, recall=1.0, fmeasure=1.0), mid=Score(precision=1.0, recall=1.0, fmeasure=1.0), high=Score(precision=1.0, recall=1.0, fmeasure=1.0))
    >>> print(results[\"rouge1\"].mid.fmeasure)
    1.0
'''


@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION							,     _KWARGS_DESCRIPTION      )
class 						lowerCamelCase       (datasets.Metric      ):







							"""simple docstring"""




							def  A_     ( self     :					Optional[int]						)				->			str:





														"""simple docstring"""
														return datasets.MetricInfo(
														    description=_DESCRIPTION,			citation=_CITATION,			inputs_description=_KWARGS_DESCRIPTION,			features=datasets.Features(
														        {
														            "predictions": datasets.Value("string",			id="sequence"						),
														            "references": datasets.Value("string",			id="sequence"						),
														        }						),			codebase_urls=["https://github.com/google-research/google-research/tree/master/rouge"],			reference_urls=[
														        "https://en.wikipedia.org/wiki/ROUGE_(metric)",
														        "https://github.com/google-research/google-research/tree/master/rouge",
														    ],			)






							def  A_     ( self     :					Tuple,			_UpperCAmelCase     :					Tuple,			_UpperCAmelCase     :					Any,			_UpperCAmelCase     :					List[str]=None,			_UpperCAmelCase     :					List[Any]=True,			_UpperCAmelCase     :					List[str]=False						)				->			Any:





														"""simple docstring"""
														if rouge_types is None:
																					SCREAMING_SNAKE_CASE__       :      List[str]     =						["rouge1", "rouge2", "rougeL", "rougeLsum"]

														SCREAMING_SNAKE_CASE__       :      str     =						rouge_scorer.RougeScorer(rouge_types=UpperCAmelCase__,			use_stemmer=UpperCAmelCase__						)
														if use_aggregator:
																					SCREAMING_SNAKE_CASE__       :      List[Any]     =						scoring.BootstrapAggregator()
														else:
																					SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						[]

														for ref, pred in zip(UpperCAmelCase__,			UpperCAmelCase__						):
																					SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						scorer.score(UpperCAmelCase__,			UpperCAmelCase__						)
																					if use_aggregator:
																												aggregator.add_scores(UpperCAmelCase__						)
																					else:
																												scores.append(UpperCAmelCase__						)

														if use_aggregator:
																					SCREAMING_SNAKE_CASE__       :      Optional[int]     =						aggregator.aggregate()
														else:
																					SCREAMING_SNAKE_CASE__       :      Dict     =						{}
																					for key in scores[0]:
																												SCREAMING_SNAKE_CASE__       :      Dict     =						[score[key] for score in scores]

														return result













class 						lowerCamelCase       :







							"""simple docstring"""




							def __init__( self     :					int,			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					str						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      str     =						name
														SCREAMING_SNAKE_CASE__       :      Tuple     =						val






							def __str__( self     :					str						)				->			List[Any]:





														"""simple docstring"""
														return F'''{self.__class__.__name__}({self.name}, {self.val})'''






							def __lt__( self     :					str,			_UpperCAmelCase     :					Dict						)				->			Union[str, Any]:





														"""simple docstring"""
														return self.val < other.val


class 						lowerCamelCase       :







							"""simple docstring"""




							def __init__( self     :					Optional[Any],			_UpperCAmelCase     :					str						)				->			Tuple:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						{}
														SCREAMING_SNAKE_CASE__       :      str     =						{}
														SCREAMING_SNAKE_CASE__       :      Union[str, Any]     =						self.build_heap(_UpperCAmelCase						)






							def __getitem__( self     :					Union[str, Any],			_UpperCAmelCase     :					Any						)				->			Dict:





														"""simple docstring"""
														return self.get_value(_UpperCAmelCase						)






							def  A_     ( self     :					int,			_UpperCAmelCase     :					Optional[int]						)				->			Any:





														"""simple docstring"""
														return (idx - 1) // 2






							def  A_     ( self     :					Optional[Any],			_UpperCAmelCase     :					Any						)				->			Dict:





														"""simple docstring"""
														return idx * 2 + 1






							def  A_     ( self     :					str,			_UpperCAmelCase     :					List[str]						)				->			Union[str, Any]:





														"""simple docstring"""
														return idx * 2 + 2






							def  A_     ( self     :					Tuple,			_UpperCAmelCase     :					int						)				->			Optional[int]:





														"""simple docstring"""
														return self.heap_dict[key]






							def  A_     ( self     :					Optional[int],			_UpperCAmelCase     :					Dict						)				->			Optional[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      List[str]     =						len(_UpperCAmelCase						) - 1
														SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.get_parent_idx(_UpperCAmelCase						)

														for idx, i in enumerate(_UpperCAmelCase						):
																					SCREAMING_SNAKE_CASE__       :      Optional[int]     =						idx
																					SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						i.val

														for i in range(_UpperCAmelCase,			-1,			-1						):
																					self.sift_down(_UpperCAmelCase,			_UpperCAmelCase						)
														return array






							def  A_     ( self     :					List[Any],			_UpperCAmelCase     :					Dict,			_UpperCAmelCase     :					Tuple						)				->			Tuple:





														"""simple docstring"""
														while True:
																					SCREAMING_SNAKE_CASE__       :      str     =						self.get_left_child_idx(_UpperCAmelCase						)  # noqa: E741
																					SCREAMING_SNAKE_CASE__       :      Tuple     =						self.get_right_child_idx(_UpperCAmelCase						)

																					SCREAMING_SNAKE_CASE__       :      Tuple     =						idx
																					if l < len(_UpperCAmelCase						) and array[l] < array[idx]:
																												SCREAMING_SNAKE_CASE__       :      List[Any]     =						l
																					if r < len(_UpperCAmelCase						) and array[r] < array[smallest]:
																												SCREAMING_SNAKE_CASE__       :      int     =						r

																					if smallest != idx:
																												SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Any     =						array[smallest], array[idx]
																												(
																												    (
																												    SCREAMING_SNAKE_CASE__
																												)   ,(
																												    SCREAMING_SNAKE_CASE__
																												)   ,
																												)       :      Optional[Any]     =						(
																												    self.idx_of_element[array[smallest]],
																												    self.idx_of_element[array[idx]],
																												)
																												SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						smallest
																					else:
																												break






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					str						)				->			Any:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__       :      Any     =						self.get_parent_idx(_UpperCAmelCase						)
														while p >= 0 and self.heap[p] > self.heap[idx]:
																					SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Any     =						self.heap[idx], self.heap[p]
																					SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      int     =						(
																					    self.idx_of_element[self.heap[idx]],
																					    self.idx_of_element[self.heap[p]],
																					)
																					SCREAMING_SNAKE_CASE__       :      Dict     =						p
																					SCREAMING_SNAKE_CASE__       :      List[str]     =						self.get_parent_idx(_UpperCAmelCase						)






							def  A_     ( self     :					str						)				->			List[str]:





														"""simple docstring"""
														return self.heap[0]






							def  A_     ( self     :					Tuple						)				->			List[Any]:





														"""simple docstring"""
														SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      Optional[int]     =						self.heap[-1], self.heap[0]
														SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__       :      List[Any]     =						(
														    self.idx_of_element[self.heap[-1]],
														    self.idx_of_element[self.heap[0]],
														)

														SCREAMING_SNAKE_CASE__       :      Any     =						self.heap.pop()
														del self.idx_of_element[x]
														self.sift_down(0,			self.heap						)
														return x






							def  A_     ( self     :					Union[str, Any],			_UpperCAmelCase     :					str						)				->			Optional[Any]:





														"""simple docstring"""
														self.heap.append(_UpperCAmelCase						)
														SCREAMING_SNAKE_CASE__       :      str     =						len(self.heap						) - 1
														SCREAMING_SNAKE_CASE__       :      Optional[Any]     =						node.val
														self.sift_up(len(self.heap						) - 1						)






							def  A_     ( self     :					Optional[int]						)				->			int:





														"""simple docstring"""
														return len(self.heap						) == 0






							def  A_     ( self     :					Any,			_UpperCAmelCase     :					Tuple,			_UpperCAmelCase     :					str						)				->			Dict:





														"""simple docstring"""
														assert (
														    self.heap[self.idx_of_element[node]].val > new_value
														), "newValue must be less that current value"
														SCREAMING_SNAKE_CASE__       :      Tuple     =						new_value
														SCREAMING_SNAKE_CASE__       :      List[Any]     =						new_value
														self.sift_up(self.idx_of_element[node]						)


_lowerCamelCase :    Tuple  							= Node('''R''', -1)
_lowerCamelCase :    int  							= Node('''B''', 6)
_lowerCamelCase :    str  							= Node('''A''', 3)
_lowerCamelCase :    Optional[Any]  							= Node('''X''', 1)
_lowerCamelCase :    str  							= Node('''E''', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
_lowerCamelCase :    int  							= MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('''Min Heap - before decrease key''')
for i in my_min_heap.heap:
		print(i)

print('''Min Heap - After decrease key of node [B -> -17]''')
my_min_heap.decrease_key(b, -1_7)

# After
for i in my_min_heap.heap:
		print(i)

if __name__ == "__main__":
		import doctest

		doctest.testmod()






