
import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors







@require_tokenizers
class        lowercase      (	lowercase_						,     unittest.TestCase     ):
		__lowercase : Optional[int]			  =       MvpTokenizer
		__lowercase : Optional[int]			  =       MvpTokenizerFast
		__lowercase : Optional[int]			  =       True
		__lowercase : Tuple			  =       filter_roberta_detectors



		def __UpperCamelCase				(				self )						->      str:
				"""simple docstring"""
				super().setUp()
				UpperCamelCase						=  [
				    'l',
				    'o',
				    'w',
				    'e',
				    'r',
				    's',
				    't',
				    'i',
				    'd',
				    'n',
				    '\u0120',
				    '\u0120l',
				    '\u0120n',
				    '\u0120lo',
				    '\u0120low',
				    'er',
				    '\u0120lowest',
				    '\u0120newer',
				    '\u0120wider',
				    '<unk>',
				]
				UpperCamelCase						=  dict(zip(A_       ,   range(len(A_ ) ) ) )
				UpperCamelCase						=  ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
				UpperCamelCase						=  {'unk_token': '<unk>'}

				UpperCamelCase						=  os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES['vocab_file'] )
				UpperCamelCase						=  os.path.join(self.tmpdirname       ,   VOCAB_FILES_NAMES['merges_file'] )
				with open(self.vocab_file       ,   'w'       ,   encoding='utf-8' ) as fp:
						fp.write(json.dumps(A_ ) + '\n' )
				with open(self.merges_file       ,   'w'       ,   encoding='utf-8' ) as fp:
						fp.write('\n'.join(A_ ) )



		def __UpperCamelCase				(				self       ,   **A_ )						->      Any:
				"""simple docstring"""
				kwargs.update(self.special_tokens_map )
				return self.tokenizer_class.from_pretrained(self.tmpdirname       ,   **A_ )



		def __UpperCamelCase				(				self       ,   **A_ )						->      str:
				"""simple docstring"""
				kwargs.update(self.special_tokens_map )
				return self.rust_tokenizer_class.from_pretrained(self.tmpdirname       ,   **A_ )



		def __UpperCamelCase				(				self       ,   A_ )						->      List[str]:
				"""simple docstring"""
				return "lower newer", "lower newer"



		@cached_property
		def __UpperCamelCase				(				self )						->      int:
				"""simple docstring"""
				return MvpTokenizer.from_pretrained('RUCAIBox/mvp' )



		@cached_property
		def __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				return MvpTokenizerFast.from_pretrained('RUCAIBox/mvp' )



		@require_torch
		def __UpperCamelCase				(				self )						->      str:
				"""simple docstring"""
				UpperCamelCase						=  ['A long paragraph for summarization.', 'Another paragraph for summarization.']
				UpperCamelCase						=  [0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						UpperCamelCase						=  tokenizer(A_       ,   max_length=len(A_ )       ,   padding=A_       ,   return_tensors='pt' )
						self.assertIsInstance(A_       ,   A_ )

						self.assertEqual((2, 9)       ,   batch.input_ids.shape )
						self.assertEqual((2, 9)       ,   batch.attention_mask.shape )
						UpperCamelCase						=  batch.input_ids.tolist()[0]
						self.assertListEqual(A_       ,   A_ )
						# Test that special tokens are reset



		@require_torch
		def __UpperCamelCase				(				self )						->      str:
				"""simple docstring"""
				UpperCamelCase						=  ['A long paragraph for summarization.', 'Another paragraph for summarization.']
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						UpperCamelCase						=  tokenizer(A_       ,   padding=A_       ,   return_tensors='pt' )
						# check if input_ids are returned and no labels
						self.assertIn('input_ids'       ,   A_ )
						self.assertIn('attention_mask'       ,   A_ )
						self.assertNotIn('labels'       ,   A_ )
						self.assertNotIn('decoder_attention_mask'       ,   A_ )



		@require_torch
		def __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				UpperCamelCase						=  [
				    'Summary of the text.',
				    'Another summary.',
				]
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						UpperCamelCase						=  tokenizer(text_target=A_       ,   max_length=32       ,   padding='max_length'       ,   return_tensors='pt' )
						self.assertEqual(32       ,   targets['input_ids'].shape[1] )



		@require_torch
		def __UpperCamelCase				(				self )						->      Union[str, Any]:
				"""simple docstring"""
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						UpperCamelCase						=  tokenizer(
						    ['I am a small frog' * 1_024, 'I am a small frog']       ,   padding=A_       ,   truncation=A_       ,   return_tensors='pt' )
						self.assertIsInstance(A_       ,   A_ )
						self.assertEqual(batch.input_ids.shape       ,   (2, 1_024) )



		@require_torch
		def __UpperCamelCase				(				self )						->      Optional[int]:
				"""simple docstring"""
				UpperCamelCase						=  ['A long paragraph for summarization.']
				UpperCamelCase						=  [
				    'Summary of the text.',
				]
				for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
						UpperCamelCase						=  tokenizer(A_       ,   text_target=A_       ,   return_tensors='pt' )
						UpperCamelCase						=  inputs['input_ids']
						UpperCamelCase						=  inputs['labels']
						self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item() )
						self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item() )
						self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item() )
						self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item() )



		def __UpperCamelCase				(				self )						->      Any:
				"""simple docstring"""
				pass



		def __UpperCamelCase				(				self )						->      str:
				"""simple docstring"""
				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
						with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})''' ):
								UpperCamelCase						=  self.rust_tokenizer_class.from_pretrained(A_       ,   **A_ )
								UpperCamelCase						=  self.tokenizer_class.from_pretrained(A_       ,   **A_ )
								UpperCamelCase						=  'A, <mask> AllenNLP sentence.'
								UpperCamelCase						=  tokenizer_r.encode_plus(A_       ,   add_special_tokens=A_       ,   return_token_type_ids=A_ )
								UpperCamelCase						=  tokenizer_p.encode_plus(A_       ,   add_special_tokens=A_       ,   return_token_type_ids=A_ )

								# token_type_ids should put 0 everywhere
								self.assertEqual(sum(tokens_r['token_type_ids'] )       ,   sum(tokens_p['token_type_ids'] ) )

								# attention_mask should put 1 everywhere, so sum over length should be 1
								self.assertEqual(
								    sum(tokens_r['attention_mask'] ) / len(tokens_r['attention_mask'] )       ,   sum(tokens_p['attention_mask'] ) / len(tokens_p['attention_mask'] )       ,   )

								UpperCamelCase						=  tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'] )
								UpperCamelCase						=  tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids'] )

								# Rust correctly handles the space before the mask while python doesnt
								self.assertSequenceEqual(tokens_p['input_ids']       ,   [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2] )
								self.assertSequenceEqual(tokens_r['input_ids']       ,   [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2] )

								self.assertSequenceEqual(
								    A_       ,   ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'] )
								self.assertSequenceEqual(
								    A_       ,   ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'] )


from collections.abc import Callable


def    A (      lowercase					, lowercase					, lowercase				)     ->						float:
		'''simple docstring'''

		UpperCamelCase						=  a
		UpperCamelCase						=  b
		if function(lowercase				) == 0:  # one of the a or b is a root for the function
				return a
		elif function(lowercase				) == 0:
				return b
		elif (
		    function(lowercase				) * function(lowercase				) > 0
		):  # if none of these are root and they are both positive or negative,
				# then this algorithm can't find the root
				raise ValueError('could not find root in given interval.'				)
		else:
				UpperCamelCase						=  start + (end - start) / 2.0
				while abs(start - mid				) > 10**-7:  # until precisely equals to 10^-7
						if function(lowercase				) == 0:
								return mid
						elif function(lowercase				) * function(lowercase				) < 0:
								UpperCamelCase						=  mid
						else:
								UpperCamelCase						=  mid
						UpperCamelCase						=  start + (end - start) / 2.0
				return mid


def    A (      lowercase				)     ->						float:
		'''simple docstring'''

		return x**3 - 2 * x - 5


if __name__ == "__main__":
					print(bisection(f, 1, 1_000))

					import doctest

					doctest.testmod()
