

'''simple docstring'''




_a			:	int								=  [0.33, 0.44, 0.55, 0.44, 0.33]
_a			:	Any								=  3
_a			:	Any								=  5

# Buffer Space (with Parameters Space)
_a			:	Union[str, Any]								=  []
_a			:	Optional[Any]								=  []

# Machine Time
_a			:	Optional[Any]								=  0


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				Union[str, Any]  ):
		global buffer_space, params_space, machine_time, K, m, t

		# Choosing Dynamical Systems (All)
		for key, value in enumerate(SCREAMING_SNAKE_CASE_  ):
				# Evolution Parameter
				UpperCAmelCase  							=		float(seed / value  )

				# Control Theory: Orbit Change
				UpperCAmelCase  							=		(buffer_space[(key + 1) % m] + e) % 1

				# Control Theory: Trajectory Change
				UpperCAmelCase  							=		(params_space[key] + e) % 1 + 3

				# Modification (Transition Function) - Jumps
				UpperCAmelCase  							=		round(float(r * value * (1 - value)  )    ,				10  )
				UpperCAmelCase  							=		r  # Saving to Parameters Space

		# Logistic Map
		assert max(SCREAMING_SNAKE_CASE_  ) < 1
		assert max(SCREAMING_SNAKE_CASE_  ) < 4

		# Machine Time
		machine_time += 1


def  lowerCamelCase__						(  ):
		global buffer_space, params_space, machine_time, K, m, t

		# PRNG (Xorshift by George Marsaglia)
		def xorshift(SCREAMING_SNAKE_CASE :				str    ,				SCREAMING_SNAKE_CASE :				Union[str, Any]  ):
				x ^= y >> 13
				y ^= x << 17
				x ^= y >> 5
				return x

		# Choosing Dynamical Systems (Increment)
		UpperCAmelCase  							=		machine_time % m

		# Evolution (Time Length)
		for _ in range(0    ,				SCREAMING_SNAKE_CASE_  ):
				# Variables (Position + Parameters)
				UpperCAmelCase  							=		params_space[key]
				UpperCAmelCase  							=		buffer_space[key]

				# Modification (Transition Function) - Flow
				UpperCAmelCase  							=		round(float(r * value * (1 - value)  )    ,				10  )
				UpperCAmelCase  							=		(machine_time * 0.01 + r * 1.01) % 1 + 3

		# Choosing Chaotic Data
		UpperCAmelCase  							=		int(buffer_space[(key + 2) % m] * (10**10)  )
		UpperCAmelCase  							=		int(buffer_space[(key - 2) % m] * (10**10)  )

		# Machine Time
		machine_time += 1

		return xorshift(SCREAMING_SNAKE_CASE_    ,				SCREAMING_SNAKE_CASE_  ) % 0XFF_FFF_FFF


def  lowerCamelCase__						(  ):
		global buffer_space, params_space, machine_time, K, m, t

		UpperCAmelCase  							=		K
		UpperCAmelCase  							=		[0] * m
		UpperCAmelCase  							=		0


if __name__ == "__main__":
		# Initialization
		reset()

		# Pushing Data (Input)
		import random

		_a			:	List[Any]								=  random.sample(range(0Xff_ff_ff_ff), 100)
		for chunk in message:
				push(chunk)

		# for controlling
		_a			:	List[str]								=  ''

		# Pulling Data (Output)
		while inp in ("e", "E"):
				print(F'''{format(pull(), '#04x')}''')
				print(buffer_space)
				print(params_space)
				_a			:	Dict								=  input('(e)exit? ').strip()





'''simple docstring'''




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


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				List[str]  ):

  def remove_articles(SCREAMING_SNAKE_CASE :				Union[str, Any]  ):
    return re.sub(R'\b(a|an|the)\b'    ,				' '    ,				SCREAMING_SNAKE_CASE  )

  def white_space_fix(SCREAMING_SNAKE_CASE :				Union[str, Any]  ):
    return " ".join(text.split()  )

  def remove_punc(SCREAMING_SNAKE_CASE :				List[Any]  ):
    UpperCAmelCase  							=		set(string.punctuation  )
    return "".join(ch for ch in text if ch not in exclude  )

  def lower(SCREAMING_SNAKE_CASE :				Any  ):
    return text.lower()

  return white_space_fix(remove_articles(remove_punc(lower(SCREAMING_SNAKE_CASE  )  )  )  )


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				Tuple    ,				SCREAMING_SNAKE_CASE :				Dict  ):
  UpperCAmelCase  							=		normalize_answer(SCREAMING_SNAKE_CASE  ).split()
  UpperCAmelCase  							=		normalize_answer(SCREAMING_SNAKE_CASE  ).split()
  UpperCAmelCase  							=		Counter(SCREAMING_SNAKE_CASE  ) & Counter(SCREAMING_SNAKE_CASE  )
  UpperCAmelCase  							=		sum(common.values()  )
  if num_same == 0:
    return 0
  UpperCAmelCase  							=		1.0 * num_same / len(SCREAMING_SNAKE_CASE  )
  UpperCAmelCase  							=		1.0 * num_same / len(SCREAMING_SNAKE_CASE  )
  UpperCAmelCase  							=		(2 * precision * recall) / (precision + recall)
  return fa


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				str    ,				SCREAMING_SNAKE_CASE :				int  ):
  return normalize_answer(SCREAMING_SNAKE_CASE  ) == normalize_answer(SCREAMING_SNAKE_CASE  )


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				Dict    ,				SCREAMING_SNAKE_CASE :				Tuple    ,				SCREAMING_SNAKE_CASE :				Dict  ):
  UpperCAmelCase  							=		[]
  for ground_truth in ground_truths:
    UpperCAmelCase  							=		metric_fn(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE  )
    scores_for_ground_truths.append(SCREAMING_SNAKE_CASE  )
  return max(SCREAMING_SNAKE_CASE  )


def  lowerCamelCase__						(  SCREAMING_SNAKE_CASE :				Optional[Any]    ,				SCREAMING_SNAKE_CASE :				Optional[int]  ):
  UpperCAmelCase  							=		UpperCAmelCase  							=		UpperCAmelCase  							=		0
  for article in dataset:
    for paragraph in article["paragraphs"]:
      for qa in paragraph["qas"]:
        total += 1
        if qa["id"] not in predictions:
          UpperCAmelCase  							=		'Unanswered question ' + qa['id'] + ' will receive score 0.'
          print(SCREAMING_SNAKE_CASE    ,				file=sys.stderr  )
          continue
        UpperCAmelCase  							=		[x['text'] for x in qa['answers']]
        UpperCAmelCase  							=		predictions[qa['id']]
        exact_match += metric_max_over_ground_truths(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE  )
        fa += metric_max_over_ground_truths(SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE    ,				SCREAMING_SNAKE_CASE  )

  UpperCAmelCase  							=		100.0 * exact_match / total
  UpperCAmelCase  							=		100.0 * fa / total

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


if __name__ == "__main__":
  _a			:	Tuple								=  '1.1'
  _a			:	int								=  argparse.ArgumentParser(description='Evaluation for SQuAD ' + expected_version)
  parser.add_argument('dataset_file', help='Dataset file')
  parser.add_argument('prediction_file', help='Prediction File')
  _a			:	List[Any]								=  parser.parse_args()
  with open(args.dataset_file) as dataset_file:
    _a			:	Optional[int]								=  json.load(dataset_file)
    if dataset_json["version"] != expected_version:
      print(
          'Evaluation expects v-' + expected_version + ', but got dataset with v-' + dataset_json['version'],
          file=sys.stderr,
      )
    _a			:	Optional[Any]								=  dataset_json['data']
  with open(args.prediction_file) as prediction_file:
    _a			:	Optional[Any]								=  json.load(prediction_file)
  print(json.dumps(evaluate(dataset, predictions)))


