





'''simple docstring'''

import os
import warnings
from typing import List, Optional

from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig


__lowerCamelCase			:			List[str]									=      logging.get_logger(__name__)

class    UpperCAmelCase			:




		def __init__(self   :						Optional[int]				,      A__   :						Optional[int]				,      A__   :						Union[str, Any]					)       ->			Any:
						lowercase    =			question_encoder
						lowercase    =			generator
						lowercase    =			self.question_encoder




		def 					UpperCAmelCase__ (self   :						Tuple				,      A__   :						Optional[Any]					)       ->			Any:



						if os.path.isfile(__lowerCAmelCase					):
										raise ValueError(f'Provided path ({save_directory}) should be a directory, not a file'					)
						os.makedirs(__lowerCAmelCase				,      exist_ok=__lowerCAmelCase					)
						lowercase    =			os.path.join(__lowerCAmelCase				,      "question_encoder_tokenizer"					)
						lowercase    =			os.path.join(__lowerCAmelCase				,      "generator_tokenizer"					)
						self.question_encoder.save_pretrained(__lowerCAmelCase					)
						self.generator.save_pretrained(__lowerCAmelCase					)




		@classmethod
		def 					UpperCAmelCase__ (cls   :						Optional[Any]				,      A__   :						List[str]				,      **A__   :						Dict					)       ->			Optional[int]:
						from ..auto.tokenization_auto import AutoTokenizer

						lowercase    =			kwargs.pop("config"				,      __lowerCAmelCase					)

						if config is None:
										lowercase    =			RagConfig.from_pretrained(__lowerCAmelCase					)

						lowercase    =			AutoTokenizer.from_pretrained(
						    __lowerCAmelCase				,      config=config.question_encoder				,      subfolder="question_encoder_tokenizer"					)
						lowercase    =			AutoTokenizer.from_pretrained(
						    __lowerCAmelCase				,      config=config.generator				,      subfolder="generator_tokenizer"					)
						return cls(question_encoder=__lowerCAmelCase				,      generator=__lowerCAmelCase					)




		def __call__(self   :						str				,      *A__   :						Optional[Any]				,      **A__   :						Union[str, Any]					)       ->			List[str]:
						return self.current_tokenizer(*__lowerCAmelCase				,      **__lowerCAmelCase					)




		def 					UpperCAmelCase__ (self   :						Optional[Any]				,      *A__   :						Optional[int]				,      **A__   :						Tuple					)       ->			Tuple:
						return self.generator.batch_decode(*__lowerCAmelCase				,      **__lowerCAmelCase					)




		def 					UpperCAmelCase__ (self   :						int				,      *A__   :						Dict				,      **A__   :						Union[str, Any]					)       ->			Optional[Any]:
						return self.generator.decode(*__lowerCAmelCase				,      **__lowerCAmelCase					)




		def 					UpperCAmelCase__ (self   :						Optional[int]					)       ->			List[Any]:
						lowercase    =			self.question_encoder




		def 					UpperCAmelCase__ (self   :						str					)       ->			Tuple:
						lowercase    =			self.generator





		def 					UpperCAmelCase__ (self   :						List[str]				,      A__   :						Optional[Any]				,      A__   :						Dict = None				,      A__   :						Any = None				,      A__   :						int = None				,      A__   :						List[str] = "longest"				,      A__   :						Optional[int] = None				,      A__   :						Union[str, Any] = True				,      **A__   :						str				,      )       ->			int:
						warnings.warn(
						    "`prepare_seq2seq_batch` is deprecated and will be removed in version 5 of 🤗 Transformers. Use the "
						    "regular `__call__` method to prepare your inputs and the tokenizer under the `with_target_tokenizer` "
						    "context manager to prepare your targets. See the documentation of your specific tokenizer for more "
						    "details"				,      __lowerCAmelCase				,      )
						if max_length is None:
										lowercase    =			self.current_tokenizer.model_max_length
						lowercase    =			self(
						    __lowerCAmelCase				,      add_special_tokens=__lowerCAmelCase				,      return_tensors=__lowerCAmelCase				,      max_length=__lowerCAmelCase				,      padding=__lowerCAmelCase				,      truncation=__lowerCAmelCase				,      **__lowerCAmelCase				,      )
						if tgt_texts is None:
										return model_inputs
						# Process tgt_texts
						if max_target_length is None:
										lowercase    =			self.current_tokenizer.model_max_length
						lowercase    =			self(
						    text_target=__lowerCAmelCase				,      add_special_tokens=__lowerCAmelCase				,      return_tensors=__lowerCAmelCase				,      padding=__lowerCAmelCase				,      max_length=__lowerCAmelCase				,      truncation=__lowerCAmelCase				,      **__lowerCAmelCase				,      )
						lowercase    =			labels["input_ids"]
						return model_inputs





"""simple docstring"""






from copy import deepcopy





class 					_A		:

      def __init__(		self						,			__lowerCAmelCase = None						,			__lowerCAmelCase = None		):







            """simple docstring"""



            if arr is None and size is not None:
                  lowercase								=      size
                  lowercase								=      [0] * size
            elif arr is not None:
                  self.init(__lowerCAmelCase		)
            else:
                  raise ValueError("""Either arr or size must be specified"""		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      len(__lowerCAmelCase		)
            lowercase								=      deepcopy(__lowerCAmelCase		)
            for i in range(1						,			self.size		):
                  lowercase								=      self.next_(__lowerCAmelCase		)
                  if j < self.size:
                        self.tree[j] += self.tree[i]

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      self.tree[:]
            for i in range(self.size - 1						,			0						,			-1		):
                  lowercase								=      self.next_(__lowerCAmelCase		)
                  if j < self.size:
                        arr[j] -= arr[i]
            return arr

      @staticmethod
      def 							A__			(		__lowerCAmelCase		):







            """simple docstring"""



            return index + (index & (-index))

      @staticmethod
      def 							A__			(		__lowerCAmelCase		):







            """simple docstring"""



            return index - (index & (-index))

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            if index == 0:
                  self.tree[0] += value
                  return
            while index < self.size:
                  self.tree[index] += value
                  lowercase								=      self.next_(__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            self.add(__lowerCAmelCase						,			value - self.get(__lowerCAmelCase		)		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            if right == 0:
                  return 0
            lowercase								=      self.tree[0]
            right -= 1  # make right inclusive
            while right > 0:
                  result += self.tree[right]
                  lowercase								=      self.prev(__lowerCAmelCase		)
            return result

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.prefix(__lowerCAmelCase		) - self.prefix(__lowerCAmelCase		)

      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            return self.query(__lowerCAmelCase						,			index + 1		)







      def 							A__			(		self						,			__lowerCAmelCase		):







            """simple docstring"""



            value -= self.tree[0]
            if value < 0:
                  return -1

            lowercase								=      1  # Largest power of 2 <= size
            while j * 2 < self.size:
                  j *= 2

            lowercase								=      0

            while j > 0:
                  if i + j < self.size and self.tree[i + j] <= value:
                        value -= self.tree[i + j]
                        i += j
                  j //= 2
            return i


if __name__ == "__main__":
       import doctest

       doctest.testmod()



