



import argparse
import json
import re
import string
import sys
from collections import Counter





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					def remove_articles(_UpperCAmelCase				):
										return re.sub(R'\b(a|an|the)\b'       ,			' '       ,			_UpperCAmelCase				)

					def white_space_fix(_UpperCAmelCase				):
										return " ".join(text.split()				)

					def remove_punc(_UpperCAmelCase				):
										lowercase						   =       set(string.punctuation				)
										return "".join(ch for ch in text if ch not in exclude				)

					def lower(_UpperCAmelCase				):
										return text.lower()

					return white_space_fix(remove_articles(remove_punc(lower(_UpperCAmelCase				)				)				)				)





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					lowercase						   =       normalize_answer(_UpperCAmelCase				).split()
					lowercase						   =       normalize_answer(_UpperCAmelCase				).split()
					lowercase						   =       Counter(_UpperCAmelCase				) & Counter(_UpperCAmelCase				)
					lowercase						   =       sum(common.values()				)
					if num_same == 0:
										return 0
					lowercase						   =       1.0 * num_same / len(_UpperCAmelCase				)
					lowercase						   =       1.0 * num_same / len(_UpperCAmelCase				)
					lowercase						   =       (2 * precision * recall) / (precision + recall)
					return fa





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					return normalize_answer(_UpperCAmelCase				) == normalize_answer(_UpperCAmelCase				)





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					lowercase						   =       []
					for ground_truth in ground_truths:
										lowercase						   =       metric_fn(_UpperCAmelCase       ,			_UpperCAmelCase				)
										scores_for_ground_truths.append(_UpperCAmelCase				)
					return max(_UpperCAmelCase				)





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					lowercase						   =       lowercase						   =       lowercase						   =       0
					lowercase						   =       []
					for passage in dataset:
										for qa in passage["qas"]:
															total += 1
															if qa["id"] not in predictions:
																				lowercase						   =       f"""Unanswered question {qa['id']} will receive score 0."""
																				print(_UpperCAmelCase       ,			file=sys.stderr				)
																				continue

															lowercase						   =       [x['text'] for x in qa['answers']]
															lowercase						   =       predictions[qa['id']]

															lowercase						   =       metric_max_over_ground_truths(_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				)
															if int(_exact_match				) == 1:
																				correct_ids.append(qa['id']				)
															exact_match += _exact_match

															fa += metric_max_over_ground_truths(_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				)

					lowercase						   =       exact_match / total
					lowercase						   =       fa / total

					return {"exact_match": exact_match, "f1": fa}, correct_ids


if __name__ == "__main__":
		__magic_name__       =     '''1.0'''
		__magic_name__       =     argparse.ArgumentParser('''Official evaluation script for ReCoRD v1.0.''')
		parser.add_argument('''data_file''', help='''The dataset file in JSON format.''')
		parser.add_argument('''pred_file''', help='''The model prediction file in JSON format.''')
		parser.add_argument('''--output_correct_ids''', action='''store_true''', help='''Output the correctly answered query IDs.''')
		__magic_name__       =     parser.parse_args()

		with open(args.data_file) as data_file:
				__magic_name__       =     json.load(data_file)
				if dataset_json["version"] != expected_version:
						print(
						    F"""Evaluation expects v-{expected_version}, but got dataset with v-{dataset_json["version"]}""",
						    file=sys.stderr,
						)
				__magic_name__       =     dataset_json['''data''']

		with open(args.pred_file) as pred_file:
				__magic_name__       =     json.load(pred_file)

		__magic_name__  ,					__magic_name__       =     evaluate(dataset, predictions)

		if args.output_correct_ids:
				print(F"""Output {len(correct_ids)} correctly answered question IDs.""")
				with open('''correct_ids.json''', '''w''') as f:
						json.dump(correct_ids, f)











def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					if right <= left:
										return
					lowercase						   =       lowercase						   =       left
					lowercase						   =       right
					lowercase						   =       sorting[left]
					while i <= b:
										if sorting[i] < pivot:
															lowercase   ,      lowercase						   =       sorting[i], sorting[a]
															a += 1
															i += 1
										elif sorting[i] > pivot:
															lowercase   ,      lowercase						   =       sorting[i], sorting[b]
															b -= 1
										else:
															i += 1
					quick_sort_apartition(_UpperCAmelCase       ,			_UpperCAmelCase       ,			a - 1				)
					quick_sort_apartition(_UpperCAmelCase       ,			b + 1       ,			_UpperCAmelCase				)





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					if left < right:
										lowercase						   =       lomuto_partition(_UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				)
										quick_sort_lomuto_partition(_UpperCAmelCase       ,			_UpperCAmelCase       ,			pivot_index - 1				)
										quick_sort_lomuto_partition(_UpperCAmelCase       ,			pivot_index + 1       ,			_UpperCAmelCase				)





def 		__snake_case						(    _UpperCAmelCase       ,			_UpperCAmelCase       ,			_UpperCAmelCase				):
					"""simple docstring"""






					lowercase						   =       sorting[right]
					lowercase						   =       left
					for i in range(_UpperCAmelCase       ,			_UpperCAmelCase				):
										if sorting[i] < pivot:
															lowercase   ,      lowercase						   =       sorting[i], sorting[store_index]
															store_index += 1
					lowercase   ,      lowercase						   =       sorting[store_index], sorting[right]
					return store_index





def 		__snake_case						(    _UpperCAmelCase				):
					"""simple docstring"""






					if len(_UpperCAmelCase				) <= 1:
										return sorting
					return (
					    three_way_radix_quicksort([i for i in sorting if i < sorting[0]]				)
					    + [i for i in sorting if i == sorting[0]]
					    + three_way_radix_quicksort([i for i in sorting if i > sorting[0]]				)
					)


if __name__ == "__main__":
		import doctest

		doctest.testmod(verbose=True)

		__magic_name__       =     input('''Enter numbers separated by a comma:\n''').strip()
		__magic_name__       =     [int(item) for item in user_input.split(''',''')]
		quick_sort_apartition(unsorted, 0, len(unsorted) - 1)
		print(unsorted)






