




import datasets

from .evaluate import (
    apply_no_ans_threshold,
    find_all_best_thresh,
    get_raw_scores,
    make_eval_dict,
    make_qid_to_has_ans,
    merge_eval,
)


__a  :					int          =  """\\n@inproceedings{Rajpurkar2016SQuAD10,\n  title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n  author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n  booktitle={EMNLP},\n  year={2016}\n}\n"""

__a  :					List[str]          =  """\nThis metric wrap the official scoring script for version 2 of the Stanford Question\nAnswering Dataset (SQuAD).\n\nStanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by\ncrowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span,\nfrom the corresponding reading passage, or the question might be unanswerable.\n\nSQuAD2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions\nwritten adversarially by crowdworkers to look similar to answerable ones.\nTo do well on SQuAD2.0, systems must not only answer questions when possible, but also\ndetermine when no answer is supported by the paragraph and abstain from answering.\n"""

__a  :					Tuple          =  """\nComputes SQuAD v2 scores (F1 and EM).\nArgs:\n    predictions: List of triple for question-answers to score with the following elements:\n        - the question-answer 'id' field as given in the references (see below)\n        - the text of the answer\n        - the probability that the question has no answer\n    references: List of question-answers dictionaries with the following key-values:\n            - 'id': id of the question-answer pair (see above),\n            - 'answers': a list of Dict {'text': text of the answer as a string}\n    no_answer_threshold: float\n        Probability threshold to decide that a question has no answer.\nReturns:\n    'exact': Exact match (the normalized answer exactly match the gold answer)\n    'f1': The F-score of predicted tokens versus the gold answer\n    'total': Number of score considered\n    'HasAns_exact': Exact match (the normalized answer exactly match the gold answer)\n    'HasAns_f1': The F-score of predicted tokens versus the gold answer\n    'HasAns_total': Number of score considered\n    'NoAns_exact': Exact match (the normalized answer exactly match the gold answer)\n    'NoAns_f1': The F-score of predicted tokens versus the gold answer\n    'NoAns_total': Number of score considered\n    'best_exact': Best exact match (with varying threshold)\n    'best_exact_thresh': No-answer probability threshold associated to the best exact match\n    'best_f1': Best F1 (with varying threshold)\n    'best_f1_thresh': No-answer probability threshold associated to the best F1\nExamples:\n\n    >>> predictions = [{'prediction_text': '1976', 'id': '56e10a3be3433e1400422b22', 'no_answer_probability': 0.}]\n    >>> references = [{'answers': {'answer_start': [97], 'text': ['1976']}, 'id': '56e10a3be3433e1400422b22'}]\n    >>> squad_v2_metric = datasets.load_metric(\"squad_v2\")\n    >>> results = squad_v2_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {'exact': 100.0, 'f1': 100.0, 'total': 1, 'HasAns_exact': 100.0, 'HasAns_f1': 100.0, 'HasAns_total': 1, 'best_exact': 100.0, 'best_exact_thresh': 0.0, 'best_f1': 100.0, 'best_f1_thresh': 0.0}\n"""




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


			"""simple docstring"""






			def 	_SCREAMING_SNAKE_CASE      (       self						)					-> Dict:

							'''simple docstring'''


							return datasets.MetricInfo(
							    description=_DESCRIPTION				,       citation=_CITATION				,       inputs_description=_KWARGS_DESCRIPTION				,       features=datasets.Features(
							        {
							            '''predictions''': {
							                '''id''': datasets.Value('''string'''						),
							                '''prediction_text''': datasets.Value('''string'''						),
							                '''no_answer_probability''': datasets.Value('''float32'''						),
							            },
							            '''references''': {
							                '''id''': datasets.Value('''string'''						),
							                '''answers''': datasets.features.Sequence(
							                    {'''text''': datasets.Value('''string'''						), '''answer_start''': datasets.Value('''int32'''						)}						),
							            },
							        }						)				,       codebase_urls=['''https://rajpurkar.github.io/SQuAD-explorer/''']				,       reference_urls=['''https://rajpurkar.github.io/SQuAD-explorer/''']				,       )





			def 	_SCREAMING_SNAKE_CASE      (       self				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__=1.0						)					-> int:

							'''simple docstring'''


							__lowercase			      =							{p['''id''']: p['''no_answer_probability'''] for p in predictions}
							__lowercase			      =							[{'''paragraphs''': [{'''qas''': references}]}]
							__lowercase			      =							{p['''id''']: p['''prediction_text'''] for p in predictions}

							__lowercase			      =							make_qid_to_has_ans(lowerCAmelCase__						)  # maps qid to True/False
							__lowercase			      =							[k for k, v in qid_to_has_ans.items() if v]
							__lowercase			      =							[k for k, v in qid_to_has_ans.items() if not v]

							__lowercase      ,					__lowercase			      =							get_raw_scores(lowerCAmelCase__				,       lowerCAmelCase__						)
							__lowercase			      =							apply_no_ans_threshold(lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__						)
							__lowercase			      =							apply_no_ans_threshold(lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__						)
							__lowercase			      =							make_eval_dict(lowerCAmelCase__				,       lowerCAmelCase__						)

							if has_ans_qids:
											__lowercase			      =							make_eval_dict(lowerCAmelCase__				,       lowerCAmelCase__				,       qid_list=lowerCAmelCase__						)
											merge_eval(lowerCAmelCase__				,       lowerCAmelCase__				,       '''HasAns'''						)
							if no_ans_qids:
											__lowercase			      =							make_eval_dict(lowerCAmelCase__				,       lowerCAmelCase__				,       qid_list=lowerCAmelCase__						)
											merge_eval(lowerCAmelCase__				,       lowerCAmelCase__				,       '''NoAns'''						)
							find_all_best_thresh(lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__				,       lowerCAmelCase__						)
							return dict(lowerCAmelCase__						)
import os
import sys

from . import rsa_key_generator as rkg

__a  :					Union[str, Any]          =  1_2_8
__a  :					List[str]          =  2_5_6





def     UpperCAmelCase						(   lowercase							,      lowercase = DEFAULT_BLOCK_SIZE							):







				"""simple docstring"""



				__lowercase			      =							message.encode('''ascii'''							)

				__lowercase			      =							[]
				for block_start in range(0							,      len(lowercase							)							,      lowercase							):
								__lowercase			      =							0
								for i in range(lowercase							,      min(block_start + block_size							,      len(lowercase							)							)							):
												block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
								block_ints.append(lowercase							)
				return block_ints





def     UpperCAmelCase						(   lowercase							,      lowercase							,      lowercase = DEFAULT_BLOCK_SIZE							):







				"""simple docstring"""



				__lowercase			      =							[]
				for block_int in block_ints:
								__lowercase			      =							[]
								for i in range(block_size - 1							,      -1							,      -1							):
												if len(lowercase							) + i < message_length:
																__lowercase			      =							block_int // (BYTE_SIZE**i)
																__lowercase			      =							block_int % (BYTE_SIZE**i)
																block_message.insert(0							,      chr(lowercase							)							)
								message.extend(lowercase							)
				return "".join(lowercase							)





def     UpperCAmelCase						(   lowercase							,      lowercase							,      lowercase = DEFAULT_BLOCK_SIZE							):







				"""simple docstring"""



				__lowercase			      =							[]
				__lowercase      ,					__lowercase			      =							key

				for block in get_blocks_from_text(lowercase							,      lowercase							):
								encrypted_blocks.append(pow(lowercase							,      lowercase							,      lowercase							)							)
				return encrypted_blocks





def     UpperCAmelCase						(   lowercase							,      lowercase							,      lowercase							,      lowercase = DEFAULT_BLOCK_SIZE							,      ):







				"""simple docstring"""



				__lowercase			      =							[]
				__lowercase      ,					__lowercase			      =							key
				for block in encrypted_blocks:
								decrypted_blocks.append(pow(lowercase							,      lowercase							,      lowercase							)							)
				return get_text_from_blocks(lowercase							,      lowercase							,      lowercase							)





def     UpperCAmelCase						(   lowercase							):







				"""simple docstring"""



				with open(lowercase							) as fo:
								__lowercase			      =							fo.read()
				__lowercase      ,					__lowercase      ,					__lowercase			      =							content.split(''','''							)
				return (int(lowercase							), int(lowercase							), int(lowercase							))





def     UpperCAmelCase						(   lowercase							,      lowercase							,      lowercase							,      lowercase = DEFAULT_BLOCK_SIZE							,      ):







				"""simple docstring"""



				__lowercase      ,					__lowercase      ,					__lowercase			      =							read_key_file(lowercase							)
				if key_size < block_size * 8:
								sys.exit(
								    '''ERROR: Block size is {} bits and key size is {} bits. The RSA cipher '''
								    '''requires the block size to be equal to or greater than the key size. '''
								    '''Either decrease the block size or use different keys.'''.format(
								        block_size * 8							,      lowercase							)							)

				__lowercase			      =							[str(lowercase							) for i in encrypt_message(lowercase							,      (n, e)							,      lowercase							)]

				__lowercase			      =							''','''.join(lowercase							)
				__lowercase			      =							F"{len(lowercase							)}_{block_size}_{encrypted_content}"
				with open(lowercase							,      '''w'''							) as fo:
								fo.write(lowercase							)
				return encrypted_content





def     UpperCAmelCase						(   lowercase							,      lowercase							):







				"""simple docstring"""



				__lowercase      ,					__lowercase      ,					__lowercase			      =							read_key_file(lowercase							)
				with open(lowercase							) as fo:
								__lowercase			      =							fo.read()
				__lowercase      ,					__lowercase      ,					__lowercase			      =							content.split('''_'''							)
				__lowercase			      =							int(lowercase							)
				__lowercase			      =							int(lowercase							)

				if key_size < block_size * 8:
								sys.exit(
								    '''ERROR: Block size is {} bits and key size is {} bits. The RSA cipher '''
								    '''requires the block size to be equal to or greater than the key size. '''
								    '''Did you specify the correct key file and encrypted file?'''.format(
								        block_size * 8							,      lowercase							)							)

				__lowercase			      =							[]
				for block in encrypted_message.split(''','''							):
								encrypted_blocks.append(int(lowercase							)							)

				return decrypt_message(lowercase							,      lowercase							,      (n, d)							,      lowercase							)





def     UpperCAmelCase						(   ):







				"""simple docstring"""



				__lowercase			      =							'''encrypted_file.txt'''
				__lowercase			      =							input(r'''Encrypt\Decrypt [e\d]: '''							)

				if response.lower().startswith('''e'''							):
								__lowercase			      =							'''encrypt'''
				elif response.lower().startswith('''d'''							):
								__lowercase			      =							'''decrypt'''

				if mode == "encrypt":
								if not os.path.exists('''rsa_pubkey.txt'''							):
												rkg.make_key_files('''rsa'''							,      1024							)

								__lowercase			      =							input('''\nEnter message: '''							)
								__lowercase			      =							'''rsa_pubkey.txt'''
								print(F"Encrypting and writing to {filename}..."							)
								__lowercase			      =							encrypt_and_write_to_file(lowercase							,      lowercase							,      lowercase							)

								print('''\nEncrypted text:'''							)
								print(lowercase							)

				elif mode == "decrypt":
								__lowercase			      =							'''rsa_privkey.txt'''
								print(F"Reading from {filename} and decrypting..."							)
								__lowercase			      =							read_from_file_and_decrypt(lowercase							,      lowercase							)
								print('''writing decryption to rsa_decryption.txt...'''							)
								with open('''rsa_decryption.txt'''							,      '''w'''							) as dec:
												dec.write(lowercase							)

								print('''\nDecryption:'''							)
								print(lowercase							)


if __name__ == "__main__":
		main()