





'''simple docstring'''







import logging
import random

import ray

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


_lowercase       						=			logging.getLogger(__name__)
class 			_lowercase						:







     def __init__( self    ) ->	Dict:
      snake_case				=			False







     def     UpperCamelCase			( self    ,   A__    ,   A__    ,   A__    ,   A__    ) ->	int:
      if not self.initialized:
       snake_case				=			RagRetriever(
           A__    ,   question_encoder_tokenizer=A__    ,   generator_tokenizer=A__    ,   index=A__    ,   init_retrieval=A__    ,   )
       snake_case				=			True







     def     UpperCamelCase			( self    ) ->	Dict:
      self.retriever.index.init_index()







     def     UpperCamelCase			( self    ,   A__    ,   A__    ) ->	List[Any]:
      snake_case				,		snake_case				=			self.retriever._main_retrieve(A__    ,   A__    )
      return doc_ids, retrieved_doc_embeds




class 			_lowercase						(       __a					):







     def __init__( self    ,   A__    ,   A__    ,   A__    ,   A__    ,   A__=None    ) ->	int:
      if index is not None and index.is_initialized() and len(A__    ) > 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__(
          A__    ,   question_encoder_tokenizer=A__    ,   generator_tokenizer=A__    ,   index=A__    ,   init_retrieval=A__    ,   )
      snake_case				=			retrieval_workers
      if len(self.retrieval_workers    ) > 0:
       ray.get(
           [
               worker.create_rag_retriever.remote(A__    ,   A__    ,   A__    ,   A__    )
               for worker in self.retrieval_workers
           ]    )







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







     @classmethod
     def     UpperCamelCase			( cls    ,   A__    ,   A__=None    ,   **A__    ) ->	List[str]:
      return super(A__    ,   cls    ).get_tokenizers(A__    ,   A__    ,   **A__    )







     @classmethod
     def     UpperCamelCase			( cls    ,   A__    ,   A__    ,   A__=None    ,   **A__    ) ->	Union[str, Any]:
      snake_case				=			kwargs.pop('''config'''    ,   A__    ) or RagConfig.from_pretrained(A__    ,   **A__    )
      snake_case				=			RagTokenizer.from_pretrained(A__    ,   config=A__    )
      snake_case				=			rag_tokenizer.question_encoder
      snake_case				=			rag_tokenizer.generator
      if indexed_dataset is not None:
       snake_case				=			'''custom'''
       snake_case				=			CustomHFIndex(config.retrieval_vector_size    ,   A__    )
      else:
       snake_case				=			cls._build_index(A__    )
      return cls(
          A__    ,   question_encoder_tokenizer=A__    ,   generator_tokenizer=A__    ,   retrieval_workers=A__    ,   index=A__    ,   )








'''simple docstring'''







import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 			_lowercase						(       __a				,		unittest.TestCase					):
     _UpperCAmelCase										=					CodeGenTokenizer
     _UpperCAmelCase										=					CodeGenTokenizerFast
     _UpperCAmelCase										=					True
     _UpperCAmelCase										=					{'''add_prefix_space''': True}
     _UpperCAmelCase										=					False







     def     UpperCamelCase			( self    ) ->	Tuple:
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      snake_case				=			[
          '''l''',
          '''o''',
          '''w''',
          '''e''',
          '''r''',
          '''s''',
          '''t''',
          '''i''',
          '''d''',
          '''n''',
          '''\u0120''',
          '''\u0120l''',
          '''\u0120n''',
          '''\u0120lo''',
          '''\u0120low''',
          '''er''',
          '''\u0120lowest''',
          '''\u0120newer''',
          '''\u0120wider''',
          '''<unk>''',
          '''<|endoftext|>''',
      ]
      snake_case				=			dict(zip(A__    ,   range(len(A__    )    )    )    )
      snake_case				=			['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
      snake_case				=			{'''unk_token''': '''<unk>'''}

      snake_case				=			os.path.join(self.tmpdirname    ,   VOCAB_FILES_NAMES['''vocab_file''']    )
      snake_case				=			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__    ) ->	Union[str, Any]:
      kwargs.update(self.special_tokens_map    )
      return CodeGenTokenizer.from_pretrained(self.tmpdirname    ,   **A__    )







     def     UpperCamelCase			( self    ,   **A__    ) ->	Union[str, Any]:
      kwargs.update(self.special_tokens_map    )
      return CodeGenTokenizerFast.from_pretrained(self.tmpdirname    ,   **A__    )







     def     UpperCamelCase			( self    ,   A__    ) ->	Tuple:
      snake_case				=			'''lower newer'''
      snake_case				=			'''lower newer'''
      return input_text, output_text







     def     UpperCamelCase			( self    ) ->	List[Any]:
      snake_case				=			CodeGenTokenizer(self.vocab_file    ,   self.merges_file    ,   **self.special_tokens_map    )
      snake_case				=			'''lower newer'''
      snake_case				=			['''\u0120low''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
      snake_case				=			tokenizer.tokenize(A__    ,   add_prefix_space=A__    )
      self.assertListEqual(A__    ,   A__    )

      snake_case				=			tokens + [tokenizer.unk_token]
      snake_case				=			[14, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A__    )    ,   A__    )







     def     UpperCamelCase			( self    ) ->	Optional[int]:
      if not self.test_rust_tokenizer:
       return

      snake_case				=			self.get_tokenizer()
      snake_case				=			self.get_rust_tokenizer(add_prefix_space=A__    )

      snake_case				=			'''lower newer'''

      # Testing tokenization
      snake_case				=			tokenizer.tokenize(A__    ,   add_prefix_space=A__    )
      snake_case				=			rust_tokenizer.tokenize(A__    )
      self.assertListEqual(A__    ,   A__    )

      # Testing conversion to ids without special tokens
      snake_case				=			tokenizer.encode(A__    ,   add_special_tokens=A__    ,   add_prefix_space=A__    )
      snake_case				=			rust_tokenizer.encode(A__    ,   add_special_tokens=A__    )
      self.assertListEqual(A__    ,   A__    )

      # Testing conversion to ids with special tokens
      snake_case				=			self.get_rust_tokenizer(add_prefix_space=A__    )
      snake_case				=			tokenizer.encode(A__    ,   add_prefix_space=A__    )
      snake_case				=			rust_tokenizer.encode(A__    )
      self.assertListEqual(A__    ,   A__    )

      # Testing the unknown token
      snake_case				=			tokens + [rust_tokenizer.unk_token]
      snake_case				=			[14, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(A__    )    ,   A__    )







     def     UpperCamelCase			( self    ,   *A__    ,   **A__    ) ->	List[str]:
      # It's very difficult to mix/test pretokenization with byte-level
      # And get both CodeGen and Roberta to work at the same time (mostly an issue of adding a space before the string)
      pass







     def     UpperCamelCase			( self    ,   A__=15    ) ->	Tuple:
      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""    ):
        snake_case				=			self.rust_tokenizer_class.from_pretrained(A__    ,   **A__    )

        # Simple input
        snake_case				=			'''This is a simple input'''
        snake_case				=			['''This is a simple input 1''', '''This is a simple input 2''']
        snake_case				=			('''This is a simple input''', '''This is a pair''')
        snake_case				=			[
            ('''This is a simple input 1''', '''This is a simple input 2'''),
            ('''This is a simple pair 1''', '''This is a simple pair 2'''),
        ]

        # Simple input tests
        self.assertRaises(A__    ,   tokenizer_r.encode    ,   A__    ,   max_length=A__    ,   padding='''max_length'''    )

        # Simple input
        self.assertRaises(A__    ,   tokenizer_r.encode_plus    ,   A__    ,   max_length=A__    ,   padding='''max_length'''    )

        # Simple input
        self.assertRaises(
            A__    ,   tokenizer_r.batch_encode_plus    ,   A__    ,   max_length=A__    ,   padding='''max_length'''    ,   )

        # Pair input
        self.assertRaises(A__    ,   tokenizer_r.encode    ,   A__    ,   max_length=A__    ,   padding='''max_length'''    )

        # Pair input
        self.assertRaises(A__    ,   tokenizer_r.encode_plus    ,   A__    ,   max_length=A__    ,   padding='''max_length'''    )

        # Pair input
        self.assertRaises(
            A__    ,   tokenizer_r.batch_encode_plus    ,   A__    ,   max_length=A__    ,   padding='''max_length'''    ,   )







     def     UpperCamelCase			( self    ) ->	Tuple:
      snake_case				=			CodeGenTokenizer.from_pretrained(self.tmpdirname    ,   pad_token='''<pad>'''    )

      # Simple input
      snake_case				=			'''This is a simple input'''
      snake_case				=			['''This is a simple input looooooooong''', '''This is a simple input''']
      snake_case				=			('''This is a simple input''', '''This is a pair''')
      snake_case				=			[
          ('''This is a simple input loooooong''', '''This is a simple input'''),
          ('''This is a simple pair loooooong''', '''This is a simple pair'''),
      ]

      snake_case				=			tokenizer.pad_token_id

      snake_case				=			tokenizer(A__    ,   padding='''max_length'''    ,   max_length=30    ,   return_tensors='''np'''    )
      snake_case				=			tokenizer(A__    ,   padding=A__    ,   truncate=A__    ,   return_tensors='''np'''    )
      snake_case				=			tokenizer(*A__    ,   padding='''max_length'''    ,   max_length=60    ,   return_tensors='''np'''    )
      snake_case				=			tokenizer(A__    ,   padding=A__    ,   truncate=A__    ,   return_tensors='''np'''    )

      # s
      # test single string max_length padding
      self.assertEqual(out_s['''input_ids'''].shape[-1]    ,   30    )
      self.assertTrue(pad_token_id in out_s['''input_ids''']    )
      self.assertTrue(0 in out_s['''attention_mask''']    )

      # s2
      # test automatic padding
      self.assertEqual(out_sa['''input_ids'''].shape[-1]    ,   33    )
      # long slice doesn't have padding
      self.assertFalse(pad_token_id in out_sa['''input_ids'''][0]    )
      self.assertFalse(0 in out_sa['''attention_mask'''][0]    )
      # short slice does have padding
      self.assertTrue(pad_token_id in out_sa['''input_ids'''][1]    )
      self.assertTrue(0 in out_sa['''attention_mask'''][1]    )

      # p
      # test single pair max_length padding
      self.assertEqual(out_p['''input_ids'''].shape[-1]    ,   60    )
      self.assertTrue(pad_token_id in out_p['''input_ids''']    )
      self.assertTrue(0 in out_p['''attention_mask''']    )

      # p2
      # test automatic padding pair
      self.assertEqual(out_pa['''input_ids'''].shape[-1]    ,   52    )
      # long slice pair doesn't have padding
      self.assertFalse(pad_token_id in out_pa['''input_ids'''][0]    )
      self.assertFalse(0 in out_pa['''attention_mask'''][0]    )
      # short slice pair does have padding
      self.assertTrue(pad_token_id in out_pa['''input_ids'''][1]    )
      self.assertTrue(0 in out_pa['''attention_mask'''][1]    )







     def     UpperCamelCase			( self    ) ->	str:
      snake_case				=			'''$$$'''
      snake_case				=			CodeGenTokenizer.from_pretrained(self.tmpdirname    ,   bos_token=A__    ,   add_bos_token=A__    )

      snake_case				=			'''This is a simple input'''
      snake_case				=			['''This is a simple input 1''', '''This is a simple input 2''']

      snake_case				=			tokenizer.bos_token_id

      snake_case				=			tokenizer(A__    )
      snake_case				=			tokenizer(A__    )

      self.assertEqual(out_s.input_ids[0]    ,   A__    )
      self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids    )    )

      snake_case				=			tokenizer.decode(out_s.input_ids    )
      snake_case				=			tokenizer.batch_decode(out_sa.input_ids    )

      self.assertEqual(decode_s.split()[0]    ,   A__    )
      self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa    )    )







     @slow
     def     UpperCamelCase			( self    ) ->	Any:
      snake_case				=			CodeGenTokenizer.from_pretrained('''Salesforce/codegen-350M-mono'''    )

      snake_case				=			'''\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#'''
      snake_case				=			'''\nif len_a > len_b:      result = a\nelse:      result = b'''

      snake_case				=			tokenizer.encode(A__    )
      snake_case				=			['''^#''', re.escape('''<|endoftext|>'''    ), '''^\'\'\'''', '''^"""''', '''\n\n\n''']
      snake_case				=			tokenizer.decode(A__    ,   truncate_before_pattern=A__    )
      self.assertEqual(A__    ,   A__    )







     def     UpperCamelCase			( self    ) ->	Union[str, Any]:
      pass

