

"""simple docstring"""


import logging
import random

import ray

from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex


__A						       =      logging.getLogger(__name__)





class    snake_case     :

				def __init__(     self							:    List[str])->       str:



						'''simple docstring'''


						__lowerCAmelCase:	List[Any]   				=      False

				def 							lowercase_					(     self							:    List[Any]					,  UpperCamelCase__							:    Any					,  UpperCamelCase__							:    Any					,  UpperCamelCase__							:    Optional[int]					,  UpperCamelCase__							:    Union[str, Any])->       List[str]:



						'''simple docstring'''


						if not self.initialized:
								__lowerCAmelCase:	List[Any]   				=      RagRetriever(
								    UpperCamelCase__					,  question_encoder_tokenizer=UpperCamelCase__					,  generator_tokenizer=UpperCamelCase__					,  index=UpperCamelCase__					,  init_retrieval=UpperCamelCase__					,  )
								__lowerCAmelCase:	Any   				=      True

				def 							lowercase_					(     self							:    str)->       int:



						'''simple docstring'''


						self.retriever.index.init_index()




				def 							lowercase_					(     self							:    Any					,  UpperCamelCase__							:    Optional[Any]					,  UpperCamelCase__							:    int)->       Dict:



						'''simple docstring'''


						__lowerCAmelCase				,			__lowerCAmelCase:	Tuple   				=      self.retriever._main_retrieve(UpperCamelCase__					,  UpperCamelCase__)
						return doc_ids, retrieved_doc_embeds





class    snake_case     (    __snake_case  ):

				def __init__(     self							:    int					,  UpperCamelCase__							:    str					,  UpperCamelCase__							:    Any					,  UpperCamelCase__							:    Dict					,  UpperCamelCase__							:    Union[str, Any]					,  UpperCamelCase__							:    Dict=None)->       Optional[Any]:



						'''simple docstring'''


						if index is not None and index.is_initialized() and len(UpperCamelCase__) > 0:
								raise ValueError(
								    "When using Ray for distributed fine-tuning, "
								    "you'll need to provide the paths instead, "
								    "as the dataset and the index are loaded "
								    "separately. More info in examples/rag/use_own_knowledge_dataset.py ")
						super().__init__(
						    UpperCamelCase__					,  question_encoder_tokenizer=UpperCamelCase__					,  generator_tokenizer=UpperCamelCase__					,  index=UpperCamelCase__					,  init_retrieval=UpperCamelCase__					,  )
						__lowerCAmelCase:	Dict   				=      retrieval_workers
						if len(self.retrieval_workers) > 0:
								ray.get(
								    [
								        worker.create_rag_retriever.remote(UpperCamelCase__					,  UpperCamelCase__					,  UpperCamelCase__					,  UpperCamelCase__)
								        for worker in self.retrieval_workers
								    ])

				def 							lowercase_					(     self							:    Tuple)->       Union[str, Any]:



						'''simple docstring'''


						logger.info("initializing retrieval")

						if len(self.retrieval_workers) > 0:
								ray.get([worker.init_retrieval.remote() for worker in self.retrieval_workers])
						else:
								# Non-distributed training. Load index into this same process.
								self.index.init_index()

				def 							lowercase_					(     self							:    List[str]					,  UpperCamelCase__							:    Optional[Any]					,  UpperCamelCase__							:    Optional[Any])->       Union[str, Any]:



						'''simple docstring'''


						if len(self.retrieval_workers) > 0:
								# Select a random retrieval actor.
								__lowerCAmelCase:	Any   				=      self.retrieval_workers[random.randint(0					,  len(self.retrieval_workers) - 1)]
								__lowerCAmelCase				,			__lowerCAmelCase:	Optional[Any]   				=      ray.get(random_worker.retrieve.remote(UpperCamelCase__					,  UpperCamelCase__))
						else:
								__lowerCAmelCase				,			__lowerCAmelCase:	Optional[int]   				=      self._main_retrieve(UpperCamelCase__					,  UpperCamelCase__)
						return retrieved_doc_embeds, doc_ids, self.index.get_doc_dicts(UpperCamelCase__)

				@classmethod
				def 							lowercase_					(     cls							:    int					,  UpperCamelCase__							:    Any					,  UpperCamelCase__							:    Any=None					,  **UpperCamelCase__							:    Union[str, Any])->       Optional[int]:



						'''simple docstring'''


						return super(UpperCamelCase__					,  cls).get_tokenizers(UpperCamelCase__					,  UpperCamelCase__					,  **UpperCamelCase__)




				@classmethod
				def 							lowercase_					(     cls							:    Any					,  UpperCamelCase__							:    List[Any]					,  UpperCamelCase__							:    Optional[Any]					,  UpperCamelCase__							:    Optional[int]=None					,  **UpperCamelCase__							:    List[str])->       Dict:



						'''simple docstring'''


						__lowerCAmelCase:	Optional[Any]   				=      kwargs.pop("config"					,  UpperCamelCase__) or RagConfig.from_pretrained(UpperCamelCase__					,  **UpperCamelCase__)
						__lowerCAmelCase:	Dict   				=      RagTokenizer.from_pretrained(UpperCamelCase__					,  config=UpperCamelCase__)
						__lowerCAmelCase:	Optional[Any]   				=      rag_tokenizer.question_encoder
						__lowerCAmelCase:	List[Any]   				=      rag_tokenizer.generator
						if indexed_dataset is not None:
								__lowerCAmelCase:	List[Any]   				=      "custom"
								__lowerCAmelCase:	Any   				=      CustomHFIndex(config.retrieval_vector_size					,  UpperCamelCase__)
						else:
								__lowerCAmelCase:	Tuple   				=      cls._build_index(UpperCamelCase__)
						return cls(
						    UpperCamelCase__					,  question_encoder_tokenizer=UpperCamelCase__					,  generator_tokenizer=UpperCamelCase__					,  retrieval_workers=UpperCamelCase__					,  index=UpperCamelCase__					,  )





"""simple docstring"""


from __future__ import annotations

from decimal import Decimal
from math import *  # noqa: F403

from sympy import diff






def    a__   (   __SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE ,			__SCREAMING_SNAKE_CASE = 1_0**-1_0			)     ->     float:
		__lowerCAmelCase:	Union[str, Any]   				=      a
		while True:
				__lowerCAmelCase:	Optional[int]   				=      Decimal(__SCREAMING_SNAKE_CASE			) - (
				    Decimal(eval(__SCREAMING_SNAKE_CASE			)			) / Decimal(eval(str(diff(__SCREAMING_SNAKE_CASE			)			)			)			)  # noqa: S307
				)
				# This number dictates the accuracy of the answer
				if abs(eval(__SCREAMING_SNAKE_CASE			)			) < precision:  # noqa: S307
						return float(__SCREAMING_SNAKE_CASE			)


# 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
			print(F'''The root of x**2 - 5*x + 2 = 0 is {newton_raphson("x**2 - 5*x + 2", 0.4)}''')
			# Find Square Root of 5
			print(F'''The root of log(x) - 1 = 0 is {newton_raphson("log(x) - 1", 2)}''')
			# Exponential Roots
			print(F'''The root of exp(x) - 1 = 0 is {newton_raphson("exp(x) - 1", 0)}''')


