from transformers import (
    DPRContextEncoderTokenizer,
    DPRContextEncoderTokenizerFast,
    DPRQuestionEncoderTokenizer,
    DPRQuestionEncoderTokenizerFast,
    DPRReaderOutput,
    DPRReaderTokenizer,
    DPRReaderTokenizerFast,
)
from transformers.testing_utils import require_tokenizers, slow
from transformers.tokenization_utils_base import BatchEncoding

from ..bert.test_tokenization_bert import BertTokenizationTest

@require_tokenizers
class 	_SCREAMING_SNAKE_CASE							(     _lowercase							):






		"""simple docstring"""







		A_						 =      DPRContextEncoderTokenizer
		A_						 =      DPRContextEncoderTokenizerFast
		A_						 =      True

@require_tokenizers
class 	_SCREAMING_SNAKE_CASE							(     _lowercase							):






		"""simple docstring"""







		A_						 =      DPRQuestionEncoderTokenizer
		A_						 =      DPRQuestionEncoderTokenizerFast
		A_						 =      True

@require_tokenizers
class 	_SCREAMING_SNAKE_CASE							(     _lowercase							):






		"""simple docstring"""







		A_						 =      DPRReaderTokenizer
		A_						 =      DPRReaderTokenizerFast
		A_						 =      True



		@slow
		def 				_a				(			self    :				List[Any]   ):






					"""simple docstring"""
					_snake_case              =      self.tokenizer_class.from_pretrained("bert-base-uncased"   )

					_snake_case              =      tokenizer.encode("question sequence"  ,					add_special_tokens=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      tokenizer.encode("title sequence"  ,					add_special_tokens=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      tokenizer.encode("text sequence " * 4  ,					add_special_tokens=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      [[101] + text_a + [102] + text_a + [102] + text_a]
					_snake_case              =      BatchEncoding({"input_ids": input_ids}   )

					_snake_case              =      [[0] * len(input_ids[0]   )]
					_snake_case              =      [[0] * len(input_ids[0]   )]
					_snake_case              =      [0]
					_snake_case              =      DPRReaderOutput(__SCREAMING_SNAKE_CASE  ,					__SCREAMING_SNAKE_CASE  ,					__SCREAMING_SNAKE_CASE   )

					_snake_case       , _snake_case              =      8, 9
					_snake_case              =      10
					_snake_case              =      10
					_snake_case              =      tokenizer.decode_best_spans(__SCREAMING_SNAKE_CASE  ,					__SCREAMING_SNAKE_CASE   )
					self.assertEqual(predicted_spans[0].start_index  ,					__SCREAMING_SNAKE_CASE   )
					self.assertEqual(predicted_spans[0].end_index  ,					__SCREAMING_SNAKE_CASE   )
					self.assertEqual(predicted_spans[0].doc_id  ,					0   )







		@slow
		def 				_a				(			self    :				Optional[int]   ):






					"""simple docstring"""
					_snake_case              =      self.tokenizer_class.from_pretrained("bert-base-uncased"   )

					_snake_case              =      tokenizer.encode("question sequence"  ,					add_special_tokens=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      tokenizer.encode("title sequence"  ,					add_special_tokens=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      tokenizer.encode("text sequence"  ,					add_special_tokens=__SCREAMING_SNAKE_CASE   )
					_snake_case              =      [101] + text_a + [102] + text_a + [102] + text_a
					_snake_case              =      tokenizer(questions=["question sequence"]  ,					titles=["title sequence"]  ,					texts=["text sequence"]   )
					self.assertIn("input_ids"  ,					__SCREAMING_SNAKE_CASE   )
					self.assertIn("attention_mask"  ,					__SCREAMING_SNAKE_CASE   )
					self.assertListEqual(encoded_input["input_ids"][0]  ,					__SCREAMING_SNAKE_CASE   )


from math import gcd






def    UpperCAmelCase__(						lowerCamelCase_ = 12000  ):



			"""simple docstring"""





			_snake_case              =      0
			for d in range(max_d + 1  ):
						for n in range(d // 3 + 1							,	(d + 1) // 2  ):
									if gcd(lowerCamelCase_							,	lowerCamelCase_  ) == 1:
												fractions_number += 1
			return fractions_number


if __name__ == "__main__":
			print(F"{solution() = }")

