code: 
  
  
  
  
  
  '''simple docstring'''
  
  
  import argparse
  import glob
  import inspect
  import os
  import re
  import unittest
  
  from get_test_info import get_test_classes
  
  from tests.test_pipeline_mixin import pipeline_test_mapping
  
  
  _lowerCamelCase				:	List[str]				    =       {}
  for task, _ in pipeline_test_mapping.items():
  				_lowerCamelCase				:	str				    =       {'pt': None, 'tf': None}
  
  
  # DO **NOT** add item to this set (unless the reason is approved)
  _lowerCamelCase				:	List[str]				    =       {
      'tests/models/esm/test_modeling_esmfold.py',  # The pipeline test mapping is added to `test_modeling_esm.py`
  }
  
  
  
  
  def    __a (     UpperCAmelCase    )      ->List[str]:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	if "ModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
  		return "pt"
  	elif "TFModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
  		return "tf"
  	elif "FlaxModelTesterMixin" in [x.__name__ for x in test_class.__bases__]:
  		return "flax"
  	else:
  		return None
  
  
  
  
  def    __a (     UpperCAmelCase       ,			UpperCAmelCase    )      ->List[Any]:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	if PIPELINE_TEST_MAPPING[task].get(UpperCAmelCase       ,			UpperCAmelCase    ) is not None:
  		return PIPELINE_TEST_MAPPING[task][framework]
  
  	A							  =      pipeline_test_mapping[task]["""test"""]
  	A							  =      None
  
  	if framework == "pt":
  		A							  =      getattr(UpperCAmelCase       ,			"""model_mapping"""       ,			UpperCAmelCase    )
  	elif framework == "tf":
  		A							  =      getattr(UpperCAmelCase       ,			"""tf_model_mapping"""       ,			UpperCAmelCase    )
  
  	if mapping is not None:
  		A							  =      dict(mapping.items()    )
  
  	# cache the results
  	A							  =      mapping
  	return mapping
  
  
  
  
  def    __a (     UpperCAmelCase       ,			UpperCAmelCase    )      ->Dict:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      get_framework(UpperCAmelCase    )
  	if framework is None:
  		return None
  	A							  =      get_mapping_for_task(UpperCAmelCase       ,			UpperCAmelCase    )
  	if mapping is None:
  		return None
  
  	A							  =      list({model_class.config_class for model_class in test_class.all_model_classes}    )
  	if len(UpperCAmelCase    ) != 1:
  		raise ValueError("""There should be exactly one configuration class from `test_class.all_model_classes`."""    )
  
  	# This could be a list/tuple of model classes, but it's rare.
  	A							  =      mapping.get(config_classes[0]       ,			UpperCAmelCase    )
  	if isinstance(UpperCAmelCase       ,			(tuple, list)    ):
  		A							  =      sorted(UpperCAmelCase       ,			key=lambda UpperCAmelCase    : x.__name__    )
  
  	return model_class
  
  
  
  
  def    __a (     UpperCAmelCase    )      ->str:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      [(task, get_model_for_pipeline_test(UpperCAmelCase       ,			UpperCAmelCase    )) for task in pipeline_test_mapping]
  	A							  =      sorted([(task, model) for task, model in mapping if model is not None]       ,			key=lambda UpperCAmelCase    : x[0]    )
  
  	return dict(UpperCAmelCase    )
  
  
  
  
  def    __a (     UpperCAmelCase    )      ->Optional[Any]:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      get_framework(UpperCAmelCase    )
  	if framework == "pt":
  		A							  =      """torch"""
  	A							  =      """{}"""
  
  	A							  =      get_pipeline_model_mapping(UpperCAmelCase    )
  	if len(UpperCAmelCase    ) == 0:
  		return ""
  
  	A							  =      []
  	for task, model_classes in mapping.items():
  		if isinstance(UpperCAmelCase       ,			(tuple, list)    ):
  			# A list/tuple of model classes
  			A							  =      """(""" + """, """.join([x.__name__ for x in model_classes]    ) + """)"""
  		else:
  			# A single model class
  			A							  =      model_classes.__name__
  		texts.append(f"""\"{task}\": {value}"""    )
  	A							  =      """{""" + """, """.join(UpperCAmelCase    ) + """}"""
  	A							  =      f"""pipeline_model_mapping = {text} if is_{framework}_available() else {default_value}"""
  
  	return text
  
  
  
  
  def    __a (     UpperCAmelCase    )      ->List[Any]:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      {"""ModelTesterMixin""", """TFModelTesterMixin""", """FlaxModelTesterMixin"""}
  	if not issubclass(UpperCAmelCase       ,			unittest.TestCase    ):
  		return False
  	return len(base_class_names.intersection([x.__name__ for x in test_class.__bases__]    )    ) > 0
  
  
  
  
  def    __a (     UpperCAmelCase    )      ->Any:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      [x for x in get_test_classes(UpperCAmelCase    ) if is_valid_test_class(UpperCAmelCase    )]
  
  	A							  =      None
  	for test_class in test_classes:
  		# If a test class has defined `pipeline_model_mapping`, let's take it
  		if getattr(UpperCAmelCase       ,			"""pipeline_model_mapping"""       ,			UpperCAmelCase    ) is not None:
  			A							  =      test_class
  			break
      # Take the test class with the shortest name (just a heuristic)
  	if target_test_class is None and len(UpperCAmelCase    ) > 0:
  		A							  =      sorted(UpperCAmelCase       ,			key=lambda UpperCAmelCase    : (len(x.__name__    ), x.__name__)    )[0]
  
  	return target_test_class
  
  
  
  
  def    __a (     UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )      ->int:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      start_idx
  	for idx, line in enumerate(lines[start_idx:]    ):
  		A							  =      len(UpperCAmelCase    ) - len(line.lstrip()    )
  		if idx == 0 or indent > indent_level or (indent == indent_level and line.strip() == ")"):
  			A							  =      start_idx + idx
  		elif idx > 0 and indent <= indent_level:
  			# Outside the definition block of `pipeline_model_mapping`
  			break
  
  	return end_idx
  
  
  
  
  def    __a (     UpperCAmelCase       ,			UpperCAmelCase=False    )      ->Dict:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	if getattr(UpperCAmelCase       ,			"""pipeline_model_mapping"""       ,			UpperCAmelCase    ) is not None:
  		if not overwrite:
  			return "", -1
  
  	A							  =      get_pipeline_model_mapping_string(UpperCAmelCase    )
  	if len(UpperCAmelCase    ) == 0:
  		return "", -1
  	A							  =      line_to_add + """\n"""
  
  	# The code defined the class `test_class`
  	A  ,    A							  =      inspect.getsourcelines(UpperCAmelCase    )
  	# `inspect` gives the code for an object, including decorator(s) if any.
  	# We (only) need the exact line of the class definition.
  	for idx, line in enumerate(UpperCAmelCase    ):
  		if line.lstrip().startswith("""class """    ):
  			A							  =      class_lines[idx:]
  			class_start_line_no += idx
  			break
  	A							  =      class_start_line_no + len(UpperCAmelCase    ) - 1
  
  	# The index in `class_lines` that starts the definition of `all_model_classes`, `all_generative_model_classes` or
  	# `pipeline_model_mapping`. This assumes they are defined in such order, and we take the start index of the last
  	# block that appears in a `test_class`.
  	A							  =      None
  	# The indent level of the line at `class_lines[start_idx]` (if defined)
  	A							  =      0
  	# To record if `pipeline_model_mapping` is found in `test_class`.
  	A							  =      None
  	for idx, line in enumerate(UpperCAmelCase    ):
  		if line.strip().startswith("""all_model_classes = """    ):
  			A							  =      len(UpperCAmelCase    ) - len(line.lstrip()    )
  			A							  =      idx
  		elif line.strip().startswith("""all_generative_model_classes = """    ):
  			A							  =      len(UpperCAmelCase    ) - len(line.lstrip()    )
  			A							  =      idx
  		elif line.strip().startswith("""pipeline_model_mapping = """    ):
  			A							  =      len(UpperCAmelCase    ) - len(line.lstrip()    )
  			A							  =      idx
  			A							  =      line
  			break
  
  	if start_idx is None:
  		return "", -1
  	# Find the ending index (inclusive) of the above found block.
  	A							  =      find_block_ending(UpperCAmelCase       ,			UpperCAmelCase       ,			UpperCAmelCase    )
  
  	# Extract `is_xxx_available()` from existing blocks: some models require specific libraries like `timm` and use
  	# `is_timm_available()` instead of `is_torch_available()`.
  	# Keep leading and trailing whitespaces
  	A							  =      re.compile(R"""\s(is_\S+?_available\(\))\s"""    )
  	for line in class_lines[start_idx : end_idx + 1]:
  		A							  =      r.search(UpperCAmelCase    )
  		if backend_condition is not None:
  			# replace the leading and trailing whitespaces to the space character " ".
  			A							  =      """ """ + backend_condition[0][1:-1] + """ """
  			A							  =      r.sub(UpperCAmelCase       ,			UpperCAmelCase    )
  			break
  
  	if def_line is None:
  		# `pipeline_model_mapping` is not defined. The target index is set to the ending index (inclusive) of
  		# `all_model_classes` or `all_generative_model_classes`.
  		A							  =      end_idx
  	else:
  		# `pipeline_model_mapping` is defined. The target index is set to be one **BEFORE** its start index.
  		A							  =      start_idx - 1
  		# mark the lines of the currently existing `pipeline_model_mapping` to be removed.
  		for idx in range(UpperCAmelCase       ,			end_idx + 1    ):
  			# These lines are going to be removed before writing to the test file.
  			A							  =      None  # noqa
  
      # Make sure the test class is a subclass of `PipelineTesterMixin`.
  	A							  =      [x.__name__ for x in test_class.__bases__]
  	if "PipelineTesterMixin" not in parent_classes:
  		# Put `PipelineTesterMixin` just before `unittest.TestCase`
  		A							  =      [x for x in parent_classes if x != """TestCase"""] + ["""PipelineTesterMixin"""]
  		if "TestCase" in parent_classes:
  			# Here we **assume** the original string is always with `unittest.TestCase`.
  			_parent_classes.append("""unittest.TestCase"""    )
  		A							  =      """, """.join(_parent_classes    )
  		for idx, line in enumerate(UpperCAmelCase    ):
  			# Find the ending of the declaration of `test_class`
  			if line.strip().endswith("""):"""    ):
  				# mark the lines of the declaration of `test_class` to be removed
  				for _idx in range(idx + 1    ):
  					A							  =      None  # noqa
  				break
          # Add the new, one-line, class declaration for `test_class`
  		A							  =      f"""class {test_class.__name__}({parent_classes}):\n"""
  
  	# Add indentation
  	A							  =      """ """ * indent_level + line_to_add
  	# Insert `pipeline_model_mapping` to `class_lines`.
  	# (The line at `target_idx` should be kept by definition!)
  	A							  =      class_lines[: target_idx + 1] + [line_to_add] + class_lines[target_idx + 1 :]
  	# Remove the lines that are marked to be removed
  	A							  =      [x for x in class_lines if x is not None]
  
  	# Move from test class to module (in order to write to the test file)
  	A							  =      inspect.getsourcelines(inspect.getmodule(UpperCAmelCase    )    )[0]
  	# Be careful with the 1-off between line numbers and array indices
  	A							  =      module_lines[: class_start_line_no - 1] + class_lines + module_lines[class_end_line_no:]
  	A							  =      """""".join(UpperCAmelCase    )
  
  	A							  =      inspect.getsourcefile(UpperCAmelCase    )
  	with open(UpperCAmelCase       ,			"""w"""       ,			encoding="""UTF-8"""       ,			newline="""\n"""    ) as fp:
  		fp.write(UpperCAmelCase    )
  
  	return line_to_add
  
  
  
  
  def    __a (     UpperCAmelCase       ,			UpperCAmelCase=False    )      ->str:
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  
  
  	A							  =      find_test_class(UpperCAmelCase    )
  	if test_class:
  		add_pipeline_model_mapping(UpperCAmelCase       ,			overwrite=UpperCAmelCase    )
  
  
  if __name__ == "__main__":
  				_lowerCamelCase				:	str				    =       argparse.ArgumentParser()
  				parser.add_argument(
  				    '--test_file', type=str, help='A path to the test file, starting with the repository\'s `tests` directory.'
  				)
  				parser.add_argument(
  				    '--all',
  				    action='store_true',
  				    help='If to check and modify all test files.',
  				)
  				parser.add_argument(
  				    '--overwrite',
  				    action='store_true',
  				    help='If to overwrite a test class if it has already defined `pipeline_model_mapping`.',
  				)
  				_lowerCamelCase				:	List[str]				    =       parser.parse_args()
  
  				if not args.all and not args.test_file:
  								raise ValueError('Please specify either `test_file` or pass `--all` to check/modify all test files.')
  				elif args.all and args.test_file:
  								raise ValueError('Only one of `--test_file` and `--all` could be specified.')
  
  				_lowerCamelCase				:	str				    =       []
  				if args.test_file:
  								_lowerCamelCase				:	Tuple				    =       [args.test_file]
  				else:
  								_lowerCamelCase				:	List[Any]				    =       os.path.join('tests', 'models', '**', 'test_modeling_*.py')
  								for test_file in glob.glob(pattern):
  												# `Flax` is not concerned at this moment
  												if not test_file.startswith('test_modeling_flax_'):
  																test_files.append(test_file)
  
  				for test_file in test_files:
  								if test_file in TEST_FILE_TO_IGNORE:
  												print(f"[SKIPPED] {test_file} is skipped as it is in `TEST_FILE_TO_IGNORE` in the file {__file__}.")
  												continue
  								add_pipeline_model_mapping_to_test_file(test_file, overwrite=args.overwrite)
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  
  import logging
  import random
  
  import ray
  
  from transformers import RagConfig, RagRetriever, RagTokenizer
  from transformers.models.rag.retrieval_rag import CustomHFIndex
  
  
  _lowerCamelCase				:	Tuple				    =       logging.getLogger(__name__)
  
  
  
  class 							__UpperCAmelCase  :
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		def __init__(self						:      Union[str, Any]      ):
  			A							  =      False
  
  
  
  
  
  
  
  		def        A     (self						:      Any      ,      _lowerCAmelCase						:      str      ,      _lowerCAmelCase						:      List[str]      ,      _lowerCAmelCase						:      str      ,      _lowerCAmelCase						:      Any      ):
  			if not self.initialized:
  				A							  =      RagRetriever(
  				    _lowerCAmelCase      ,      question_encoder_tokenizer=_lowerCAmelCase      ,      generator_tokenizer=_lowerCAmelCase      ,      index=_lowerCAmelCase      ,      init_retrieval=_lowerCAmelCase      ,      )
  				A							  =      True
  
  
  
  
  
  
  
  		def        A     (self						:      Optional[int]      ):
  			self.retriever.index.init_index()
  
  
  
  
  
  
  
  		def        A     (self						:      Optional[int]      ):
  			# delete the old self.retriever object before assigning the new index
  			del self.retriever
  			A							  =      False
  
  
  
  
  
  
  
  		def        A     (self						:      List[str]      ,      _lowerCAmelCase						:      int      ,      _lowerCAmelCase						:      List[str]      ):
  			A  ,    A							  =      self.retriever._main_retrieve(_lowerCAmelCase      ,      _lowerCAmelCase      )
  			A							  =      self.retriever.index.get_doc_dicts(_lowerCAmelCase      )
  			return doc_ids, retrieved_doc_embeds, doc_dicts
  
  
  
  
  
  
  class 							__UpperCAmelCase  (       A__						):
  
  
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		def __init__(self						:      Tuple      ,      _lowerCAmelCase						:      int      ,      _lowerCAmelCase						:      int      ,      _lowerCAmelCase						:      List[str]      ,      _lowerCAmelCase						:      Tuple      ,      _lowerCAmelCase						:      str=None      ):
  			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      ,      )
  
  			A							  =      retrieval_workers
  			A							  =      question_encoder_tokenizer
  			A							  =      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        A     (self						:      List[Any]      ):
  			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        A     (self						:      str      ,      _lowerCAmelCase						:      Dict      ,      _lowerCAmelCase						:      Tuple      ):
  			if len(self.retrieval_workers      ) > 0:
  				# Select a random retrieval actor.
  				A							  =      self.retrieval_workers[random.randint(0      ,      len(self.retrieval_workers      ) - 1      )]
  				A  ,    A  ,    A							  =      ray.get(
  				    random_worker.retrieve.remote(_lowerCAmelCase      ,      _lowerCAmelCase      )      )
  			else:
  				A  ,    A							  =      self._main_retrieve(_lowerCAmelCase      ,      _lowerCAmelCase      )
  				A							  =      self.index.get_doc_dicts(_lowerCAmelCase      )
  			return retrieved_doc_embeds, doc_ids, doc_dicts
  
  
  
  
  
  
  
  		@classmethod
  		def        A     (cls						:      Union[str, Any]      ,      _lowerCAmelCase						:      int      ,      _lowerCAmelCase						:      Optional[Any]=None      ,      **_lowerCAmelCase						:      Union[str, Any]      ):
  			return super(_lowerCAmelCase      ,      cls      ).get_tokenizers(_lowerCAmelCase      ,      _lowerCAmelCase      ,      **_lowerCAmelCase      )
  
  
  
  
  
  
  
  		@classmethod
  		def        A     (cls						:      List[Any]      ,      _lowerCAmelCase						:      Optional[int]      ,      _lowerCAmelCase						:      List[str]      ,      _lowerCAmelCase						:      str=None      ,      **_lowerCAmelCase						:      List[str]      ):
  			A							  =      kwargs.pop("""config"""      ,      _lowerCAmelCase      ) or RagConfig.from_pretrained(_lowerCAmelCase      ,      **_lowerCAmelCase      )
  			A							  =      RagTokenizer.from_pretrained(_lowerCAmelCase      ,      config=_lowerCAmelCase      )
  			A							  =      rag_tokenizer.question_encoder
  			A							  =      rag_tokenizer.generator
  
  			if indexed_dataset is not None:
  				A							  =      """custom"""
  				A							  =      CustomHFIndex(config.retrieval_vector_size      ,      _lowerCAmelCase      )
  			else:
  				A							  =      cls._build_index(_lowerCAmelCase      )
  
  			return cls(
  			    _lowerCAmelCase      ,      question_encoder_tokenizer=_lowerCAmelCase      ,      generator_tokenizer=_lowerCAmelCase      ,      retrieval_workers=_lowerCAmelCase      ,      index=_lowerCAmelCase      ,      )
  
  
  
  
  
  
  
  		def        A     (self						:      List[Any]      ):
  			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
  			A							  =      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
  			    ]      )
  
  