



'''simple docstring'''




import json
import os
import subprocess
import sys
import warnings
from argparse import ArgumentParser
from contextlib import AbstractContextManager
from typing import Dict, List, Optional

import requests

from ..utils import logging
from . import BaseTransformersCLICommand


a  :     str       =       logging.get_logger(__name__)  # pylint: disable=invalid-name


a  :     Tuple       =       """lfs-multipart-upload"""

class      UpperCamelCase_					(				lowercase__     ):





	@staticmethod
	def 					_lowercase(    A       )     ->     str:
								UpperCAmelCase	:						Union[str, Any]					=						parser.add_parser(
								    """lfs-enable-largefiles"""						,						help=(
								        """Deprecated: use `huggingface-cli` instead. Configure your repository to enable upload of files > 5GB."""
								    )						,						)
								enable_parser.add_argument("""path"""						,						type=lowerCAmelCase__						,						help="""Local path to repository you want to configure."""       )
								enable_parser.set_defaults(func=lambda A       : LfsEnableCommand(lowerCAmelCase__       )       )

								UpperCAmelCase	:						int					=						parser.add_parser(
								    lowerCAmelCase__						,						help=(
								        """Deprecated: use `huggingface-cli` instead. """
								        """Command will get called by git-lfs, do not call it directly."""
								    )						,						)
								upload_parser.set_defaults(func=lambda A       : LfsUploadCommand(lowerCAmelCase__       )       )




class      UpperCamelCase_					:





	def __init__(    self						,						A       )     ->     int:
								UpperCAmelCase	:						int					=						args






	def 					_lowercase(    self       )     ->     Dict:
								warnings.warn(
								    """Managing repositories through transformers-cli is deprecated. Please use `huggingface-cli` instead."""       )
								UpperCAmelCase	:						Tuple					=						os.path.abspath(self.args.path       )
								if not os.path.isdir(lowerCAmelCase__       ):
															print("""This does not look like a valid git repo."""       )
															exit(1       )
								subprocess.run(
								    """git config lfs.customtransfer.multipart.path transformers-cli""".split()						,						check=lowerCAmelCase__						,						cwd=lowerCAmelCase__       )
								subprocess.run(
								    f'''git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}'''.split()						,						check=lowerCAmelCase__						,						cwd=lowerCAmelCase__						,						)
								print("""Local repo set up for largefiles"""       )




def  __lowerCamelCase    (   _lowercase						) ->     str:
							UpperCAmelCase	:						Dict					=						json.dumps(lowercase_						) + """\n"""
							sys.stdout.write(lowercase_						)
							sys.stdout.flush()



def  __lowerCamelCase    (   ) ->     Optional[Dict]:
							UpperCAmelCase	:						Tuple					=						json.loads(sys.stdin.readline().strip()						)

							if "terminate" in (msg.get("""type"""						), msg.get("""event"""						)):
														# terminate message received
														return None

							if msg.get("""event"""						) not in ("download", "upload"):
														logger.critical("""Received unexpected message"""						)
														sys.exit(1						)

							return msg

class      UpperCamelCase_					(				lowercase__     ):





	def __init__(    self						,						A						,						A						,						A       )     ->     Tuple:
								UpperCAmelCase	:						Union[str, Any]					=						filepath
								UpperCAmelCase	:						Optional[int]					=						seek_from
								UpperCAmelCase	:						int					=						read_limit
								UpperCAmelCase	:						int					=						0





	def __enter__(    self       )     ->     int:
								UpperCAmelCase	:						Union[str, Any]					=						open(self.filepath						,						"""rb"""       )
								self.f.seek(self.seek_from       )
								return self





	def __len__(    self       )     ->     List[Any]:
								UpperCAmelCase	:						int					=						os.fstat(self.f.fileno()       ).st_size
								return min(self.read_limit						,						total_length - self.seek_from       )





	def 					_lowercase(    self						,						A=-1       )     ->     Dict:
								if self.n_seen >= self.read_limit:
															return b""
								UpperCAmelCase	:						Optional[int]					=						self.read_limit - self.n_seen
								UpperCAmelCase	:						Union[str, Any]					=						self.f.read(remaining_amount if n < 0 else min(lowerCAmelCase__						,						lowerCAmelCase__       )       )
								self.n_seen += len(lowerCAmelCase__       )
								return data





	def __iter__(    self       )     ->     Tuple:
								yield self.read(n=4 * 1024 * 1024       )






	def __exit__(    self						,						*A       )     ->     Tuple:
								self.f.close()




class      UpperCamelCase_					:





	def __init__(    self						,						A       )     ->     int:
								UpperCAmelCase	:						Optional[int]					=						args






	def 					_lowercase(    self       )     ->     Any:
								UpperCAmelCase	:						Tuple					=						json.loads(sys.stdin.readline().strip()       )
								if not (init_msg.get("""event"""       ) == "init" and init_msg.get("""operation"""       ) == "upload"):
															write_msg({"""error""": {"""code""": 32, """message""": """Wrong lfs init operation"""}}       )
															sys.exit(1       )

								# The transfer process should use the information it needs from the
								# initiation structure, and also perform any one-off setup tasks it
								# needs to do. It should then respond on stdout with a simple empty
								# confirmation structure, as follows:
								write_msg({}       )

								# After the initiation exchange, git-lfs will send any number of
								# transfer requests to the stdin of the transfer process, in a serial sequence.
								while True:
															UpperCAmelCase	:						Tuple					=						read_msg()
															if msg is None:
																						# When all transfers have been processed, git-lfs will send
																						# a terminate event to the stdin of the transfer process.
																						# On receiving this message the transfer process should
																						# clean up and terminate. No response is expected.
																						sys.exit(0       )

															UpperCAmelCase	:						str					=						msg["""oid"""]
															UpperCAmelCase	:						int					=						msg["""path"""]
															UpperCAmelCase	:						Optional[int]					=						msg["""action"""]["""href"""]
															UpperCAmelCase	:						List[Any]					=						msg["""action"""]["""header"""]
															UpperCAmelCase	:						Optional[int]					=						int(header.pop("""chunk_size"""       )       )
															UpperCAmelCase	:						Tuple					=						list(header.values()       )

															UpperCAmelCase	:						List[str]					=						[]
															for i, presigned_url in enumerate(lowerCAmelCase__       ):
																						with FileSlice(lowerCAmelCase__						,						seek_from=i * chunk_size						,						read_limit=lowerCAmelCase__       ) as data:
																													UpperCAmelCase	:						Tuple					=						requests.put(lowerCAmelCase__						,						data=lowerCAmelCase__       )
																													r.raise_for_status()
																													parts.append(
																													    {
																													        """etag""": r.headers.get("""etag"""       ),
																													        """partNumber""": i + 1,
																													    }       )
																													# In order to support progress reporting while data is uploading / downloading,
																													# the transfer process should post messages to stdout
																													write_msg(
																													    {
																													        """event""": """progress""",
																													        """oid""": oid,
																													        """bytesSoFar""": (i + 1) * chunk_size,
																													        """bytesSinceLast""": chunk_size,
																													    }       )
																													# Not precise but that's ok.

															UpperCAmelCase	:						Any					=						requests.post(
															    lowerCAmelCase__						,						json={
															        """oid""": oid,
															        """parts""": parts,
															    }						,						)
															r.raise_for_status()

															write_msg({"""event""": """complete""", """oid""": oid}       )









import logging
import random

import ray

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


__UpperCAmelCase      =				logging.getLogger(__name__)
class 	a_:



     """simple docstring"""



     def __init__(		self					:	Any)							->	Optional[int]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		False





     def     __UpperCamelCase						(		self					:	Dict  ,  lowerCAmelCase__					:	Union[str, Any]  ,  lowerCAmelCase__					:	List[Any]  ,  lowerCAmelCase__					:	Optional[Any]  ,  lowerCAmelCase__					:	List[Any])							->	Optional[Any]:

      """simple docstring"""
      if not self.initialized:
       SCREAMING_SNAKE_CASE				    =		RagRetriever(
           lowerCAmelCase__  ,  question_encoder_tokenizer=lowerCAmelCase__  ,  generator_tokenizer=lowerCAmelCase__  ,  index=lowerCAmelCase__  ,  init_retrieval=lowerCAmelCase__  ,  )
       SCREAMING_SNAKE_CASE				    =		True





     def     __UpperCamelCase						(		self					:	List[str])							->	Any:

      """simple docstring"""
      self.retriever.index.init_index()





     def     __UpperCamelCase						(		self					:	int)							->	Dict:

      """simple docstring"""
      # delete the old self.retriever object before assigning the new index
      del self.retriever
      SCREAMING_SNAKE_CASE				    =		False





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

      """simple docstring"""
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		self.retriever._main_retrieve(lowerCAmelCase__  ,  lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		self.retriever.index.get_doc_dicts(lowerCAmelCase__)
      return doc_ids, retrieved_doc_embeds, doc_dicts

class 	a_(		lowercase__	):



     """simple docstring"""



     def __init__(		self					:	List[str]  ,  lowerCAmelCase__					:	Tuple  ,  lowerCAmelCase__					:	Any  ,  lowerCAmelCase__					:	Union[str, Any]  ,  lowerCAmelCase__					:	Optional[Any]  ,  lowerCAmelCase__					:	Optional[Any]=None)							->	Tuple:

      """simple docstring"""
      if index is not None and index.is_initialized() and len(lowerCAmelCase__) > 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__(
          lowerCAmelCase__  ,  question_encoder_tokenizer=lowerCAmelCase__  ,  generator_tokenizer=lowerCAmelCase__  ,  index=lowerCAmelCase__  ,  init_retrieval=lowerCAmelCase__  ,  )

      SCREAMING_SNAKE_CASE				    =		retrieval_workers
      SCREAMING_SNAKE_CASE				    =		question_encoder_tokenizer
      SCREAMING_SNAKE_CASE				    =		generator_tokenizer
      if len(self.retrieval_workers) > 0:
       ray.get(
           [
               worker.create_rag_retriever.remote(lowerCAmelCase__  ,  lowerCAmelCase__  ,  lowerCAmelCase__  ,  lowerCAmelCase__)
               for worker in self.retrieval_workers
           ])





     def     __UpperCamelCase						(		self					:	Any)							->	Dict:

      """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     __UpperCamelCase						(		self					:	Optional[int]  ,  lowerCAmelCase__					:	List[str]  ,  lowerCAmelCase__					:	Union[str, Any])							->	List[str]:

      """simple docstring"""
      if len(self.retrieval_workers) > 0:
       # Select a random retrieval actor.
       SCREAMING_SNAKE_CASE				    =		self.retrieval_workers[random.randint(0  ,  len(self.retrieval_workers) - 1)]
       SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		ray.get(
           random_worker.retrieve.remote(lowerCAmelCase__  ,  lowerCAmelCase__))
      else:
       SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		self._main_retrieve(lowerCAmelCase__  ,  lowerCAmelCase__)
       SCREAMING_SNAKE_CASE				    =		self.index.get_doc_dicts(lowerCAmelCase__)
      return retrieved_doc_embeds, doc_ids, doc_dicts





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

      """simple docstring"""
      return super(lowerCAmelCase__  ,  cls).get_tokenizers(lowerCAmelCase__  ,  lowerCAmelCase__  ,  **lowerCAmelCase__)





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

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		kwargs.pop('config'  ,  lowerCAmelCase__) or RagConfig.from_pretrained(lowerCAmelCase__  ,  **lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		RagTokenizer.from_pretrained(lowerCAmelCase__  ,  config=lowerCAmelCase__)
      SCREAMING_SNAKE_CASE				    =		rag_tokenizer.question_encoder
      SCREAMING_SNAKE_CASE				    =		rag_tokenizer.generator

      if indexed_dataset is not None:
       SCREAMING_SNAKE_CASE				    =		'custom'
       SCREAMING_SNAKE_CASE				    =		CustomHFIndex(config.retrieval_vector_size  ,  lowerCAmelCase__)
      else:
       SCREAMING_SNAKE_CASE				    =		cls._build_index(lowerCAmelCase__)

      return cls(
          lowerCAmelCase__  ,  question_encoder_tokenizer=lowerCAmelCase__  ,  generator_tokenizer=lowerCAmelCase__  ,  retrieval_workers=lowerCAmelCase__  ,  index=lowerCAmelCase__  ,  )





     def     __UpperCamelCase						(		self					:	List[Any])							->	Union[str, Any]:

      """simple docstring"""
      logger.info('re-loading the new dataset with embeddings')
      # access from the training loop

      ray.get([worker.clear_object.remote() for worker in self.retrieval_workers])

      # build the index object again
      SCREAMING_SNAKE_CASE				    =		self._build_index(self.config)

      ray.get(
          [
              worker.create_rag_retriever.remote(
                  self.config  ,  self.question_encoder_tokenizer  ,  self.generator_tokenizer  ,  lowerCAmelCase__)
              for worker in self.retrieval_workers
          ])




