



"""simple docstring"""

import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
     from transformers.models.rag.configuration_rag import RagConfig
     from transformers.models.rag.tokenization_rag import RagTokenizer




@require_faiss
@require_torch
class        _UpperCAmelCase       (			lowerCAmelCase__):

 def 						_snake_case					(     self		:       Tuple				):
     snake_case_ :     List[Any]				=	tempfile.mkdtemp()
     snake_case_ :     Tuple				=	8

     # DPR tok
     snake_case_ :     Tuple				=	[
         '''[UNK]''',
         '''[CLS]''',
         '''[SEP]''',
         '''[PAD]''',
         '''[MASK]''',
         '''want''',
         '''##want''',
         '''##ed''',
         '''wa''',
         '''un''',
         '''runn''',
         '''##ing''',
         ''',''',
         '''low''',
         '''lowest''',
     ]
     snake_case_ :     Tuple				=	os.path.join(self.tmpdirname  ,     '''dpr_tokenizer'''				)
     os.makedirs(lowercase_  ,     exist_ok=lowercase_				)
     snake_case_ :     List[str]				=	os.path.join(lowercase_  ,     DPR_VOCAB_FILES_NAMES['''vocab_file''']				)
     with open(self.vocab_file  ,     '''w'''  ,     encoding='''utf-8'''				) as vocab_writer:
         vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]				)				)

     # BART tok
     snake_case_ :     Tuple				=	[
         '''l''',
         '''o''',
         '''w''',
         '''e''',
         '''r''',
         '''s''',
         '''t''',
         '''i''',
         '''d''',
         '''n''',
         '''\u0120''',
         '''\u0120l''',
         '''\u0120n''',
         '''\u0120lo''',
         '''\u0120low''',
         '''er''',
         '''\u0120lowest''',
         '''\u0120newer''',
         '''\u0120wider''',
         '''<unk>''',
     ]
     snake_case_ :     Union[str, Any]				=	dict(zip(lowercase_  ,     range(len(lowercase_				)				)				)				)
     snake_case_ :     Union[str, Any]				=	['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
     snake_case_ :     List[str]				=	{'''unk_token''': '''<unk>'''}

     snake_case_ :     Any				=	os.path.join(self.tmpdirname  ,     '''bart_tokenizer'''				)
     os.makedirs(lowercase_  ,     exist_ok=lowercase_				)
     snake_case_ :     Optional[int]				=	os.path.join(lowercase_  ,     BART_VOCAB_FILES_NAMES['''vocab_file''']				)
     snake_case_ :     int				=	os.path.join(lowercase_  ,     BART_VOCAB_FILES_NAMES['''merges_file''']				)
     with open(self.vocab_file  ,     '''w'''  ,     encoding='''utf-8'''				) as fp:
         fp.write(json.dumps(lowercase_				) + '''\n'''				)
     with open(self.merges_file  ,     '''w'''  ,     encoding='''utf-8'''				) as fp:
         fp.write('''\n'''.join(lowercase_				)				)

 def 						_snake_case					(     self		:       str				):
     return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname  ,     '''dpr_tokenizer'''				)				)

 def 						_snake_case					(     self		:       List[str]				):
     return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname  ,     '''bart_tokenizer'''				)				)

 def 						_snake_case					(     self		:       int				):
     shutil.rmtree(self.tmpdirname				)

 @require_tokenizers
 def 						_snake_case					(     self		:       Any				):
     snake_case_ :     Optional[int]				=	os.path.join(self.tmpdirname  ,     '''rag_tokenizer'''				)
     snake_case_ :     List[str]				=	RagConfig(question_encoder=DPRConfig().to_dict()  ,     generator=BartConfig().to_dict()				)
     snake_case_ :     Tuple				=	RagTokenizer(question_encoder=self.get_dpr_tokenizer()  ,     generator=self.get_bart_tokenizer()				)
     rag_config.save_pretrained(lowercase_				)
     rag_tokenizer.save_pretrained(lowercase_				)
     snake_case_ :     Optional[Any]				=	RagTokenizer.from_pretrained(lowercase_  ,     config=lowercase_				)
     self.assertIsInstance(new_rag_tokenizer.question_encoder  ,     lowercase_				)
     self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()  ,     rag_tokenizer.question_encoder.get_vocab()				)
     self.assertIsInstance(new_rag_tokenizer.generator  ,     lowercase_				)
     self.assertEqual(new_rag_tokenizer.generator.get_vocab()  ,     rag_tokenizer.generator.get_vocab()				)

 @slow
 def 						_snake_case					(     self		:       int				):
     snake_case_ :     Tuple				=	RagTokenizer.from_pretrained('''facebook/rag-token-nq'''				)
     snake_case_ :     List[str]				=	[
         '''who got the first nobel prize in physics''',
         '''when is the next deadpool movie being released''',
         '''which mode is used for short wave broadcast service''',
         '''who is the owner of reading football club''',
         '''when is the next scandal episode coming out''',
         '''when is the last time the philadelphia won the superbowl''',
         '''what is the most current adobe flash player version''',
         '''how many episodes are there in dragon ball z''',
         '''what is the first step in the evolution of the eye''',
         '''where is gall bladder situated in human body''',
         '''what is the main mineral in lithium batteries''',
         '''who is the president of usa right now''',
         '''where do the greasers live in the outsiders''',
         '''panda is a national animal of which country''',
         '''what is the name of manchester united stadium''',
     ]
     snake_case_ :     Optional[Any]				=	tokenizer(lowercase_				)
     self.assertIsNotNone(lowercase_				)






 @slow
 def 						_snake_case					(     self		:       Tuple				):
     snake_case_ :     int				=	RagTokenizer.from_pretrained('''facebook/rag-sequence-nq'''				)
     snake_case_ :     Any				=	[
         '''who got the first nobel prize in physics''',
         '''when is the next deadpool movie being released''',
         '''which mode is used for short wave broadcast service''',
         '''who is the owner of reading football club''',
         '''when is the next scandal episode coming out''',
         '''when is the last time the philadelphia won the superbowl''',
         '''what is the most current adobe flash player version''',
         '''how many episodes are there in dragon ball z''',
         '''what is the first step in the evolution of the eye''',
         '''where is gall bladder situated in human body''',
         '''what is the main mineral in lithium batteries''',
         '''who is the president of usa right now''',
         '''where do the greasers live in the outsiders''',
         '''panda is a national animal of which country''',
         '''what is the name of manchester united stadium''',
     ]
     snake_case_ :     Optional[int]				=	tokenizer(lowercase_				)
     self.assertIsNotNone(lowercase_				)










"""simple docstring"""

from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403




def __lowercase			(							_a		,			_a		,			_a = "x"		,			_a = 10**-10		,			_a = 1		,			):
    snake_case_ :     Any				=	symbols(_a    )
    snake_case_ :     int				=	lambdify(_a		,			_a    )
    snake_case_ :     Optional[Any]				=	lambdify(_a		,			diff(_a		,			_a    )    )

    snake_case_ :     Optional[Any]				=	starting_point

    while True:
        if diff_function(_a    ) != 0:
            snake_case_ :     Optional[int]				=	prev_guess - multiplicity * func(_a    ) / diff_function(
                _a    )
        else:
            raise ZeroDivisionError('''Could not find root'''    ) from None

        # Precision is checked by comparing the difference of consecutive guesses
        if abs(next_guess - prev_guess    ) < precision:
            return next_guess

        snake_case_ :     int				=	next_guess


# Let's Execute
if __name__ == "__main__":
     # Find root of trigonometric function
     # Find value of pi
     print(f'The root of sin(x) = 0 is {newton_raphson("sin(x)", 2)}')

     # Find root of polynomial
     # Find fourth Root of 5
     print(f'The root of x**4 - 5 = 0 is {newton_raphson("x**4 -5", 0.4 +5j)}')

     # Find value of e
     print(
         '''The root of log(y) - 1 = 0 is ''',
         f'{newton_raphson("log(y) - 1", 2, variable="y")}',
     )

     # Exponential Roots
     print(
         '''The root of exp(x) - 1 = 0 is''',
         f'{newton_raphson("exp(x) - 1", 10, precision=0.005)}',
     )

     # Find root of cos(x)
     print(f'The root of cos(x) = 0 is {newton_raphson("cos(x)", 0)}')





