
'''simple docstring'''







from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class UpperCAmelCase__      (					lowercase__      ):





  """simple docstring"""

  __UpperCAmelCase							:							Tuple    					=   ['''image_processor''', '''tokenizer''']
  __UpperCAmelCase							:							Any    					=   '''BlipImageProcessor'''
  __UpperCAmelCase							:							Dict    					=   '''AutoTokenizer'''


  def __init__(						self :	str				,_a :	str				,_a :	Any			):


     '''simple docstring'''






     _a							:      int     =  False
     super().__init__(__a				,__a			)
     _a							:      int     =  self.image_processor


  def __call__(						self :	int				,_a :	ImageInput = None				,_a :	Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None				,_a :	bool = True				,_a :	Union[bool, str, PaddingStrategy] = False				,_a :	Union[bool, str, TruncationStrategy] = None				,_a :	Optional[int] = None				,_a :	int = 0				,_a :	Optional[int] = None				,_a :	Optional[bool] = None				,_a :	bool = False				,_a :	bool = False				,_a :	bool = False				,_a :	bool = False				,_a :	bool = False				,_a :	bool = True				,_a :	Optional[Union[str, TensorType]] = None				,**_a :	Dict				,):


     '''simple docstring'''






     if images is None and text is None:
        raise ValueError('You have to specify either images or text.'			)

     # Get only text
     if images is None:
        _a							:      int     =  self.tokenizer
        _a							:      int     =  self.tokenizer(
            text=__a				,add_special_tokens=__a				,padding=__a				,truncation=__a				,max_length=__a				,stride=__a				,pad_to_multiple_of=__a				,return_attention_mask=__a				,return_overflowing_tokens=__a				,return_special_tokens_mask=__a				,return_offsets_mapping=__a				,return_token_type_ids=__a				,return_length=__a				,verbose=__a				,return_tensors=__a				,**__a				,)
        return text_encoding

     # add pixel_values
     _a							:      int     =  self.image_processor(__a				,return_tensors=__a			)

     if text is not None:
        _a							:      Dict     =  self.tokenizer(
            text=__a				,add_special_tokens=__a				,padding=__a				,truncation=__a				,max_length=__a				,stride=__a				,pad_to_multiple_of=__a				,return_attention_mask=__a				,return_overflowing_tokens=__a				,return_special_tokens_mask=__a				,return_offsets_mapping=__a				,return_token_type_ids=__a				,return_length=__a				,verbose=__a				,return_tensors=__a				,**__a				,)
     else:
        _a							:      str     =  None

     if text_encoding is not None:
        encoding_image_processor.update(__a			)

     return encoding_image_processor


  def     __lowercase						(						self :	Any				,*_a :	Optional[Any]				,**_a :	Dict			):


     '''simple docstring'''






     return self.tokenizer.batch_decode(*__a				,**__a			)


  def     __lowercase						(						self :	int				,*_a :	Tuple				,**_a :	Dict			):


     '''simple docstring'''






     return self.tokenizer.decode(*__a				,**__a			)


  @property
  # Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
  def     __lowercase						(						self :	Dict			):


     '''simple docstring'''






     _a							:      int     =  self.tokenizer.model_input_names
     _a							:      int     =  self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)




'''simple docstring'''


import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")





def    lowerCAmelCase       (		UpperCamelCase__					: Dict							):


	"""simple docstring"""
	__UpperCAmelCase      					=      test_file.split(os.path.sep							)
	if components[0:2] != ["tests", "models"]:
		raise ValueError(
		    '''`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '''
		    f"""{test_file} instead."""							)
	__UpperCAmelCase      					=      components[-1]
	if not test_fn.endswith('''py'''							):
		raise ValueError(f"""`test_file` should be a python file. Got {test_fn} instead."""							)
	if not test_fn.startswith('''test_modeling_'''							):
		raise ValueError(
		    f"""`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead."""							)

	__UpperCAmelCase      					=      components[:-1] + [test_fn.replace('''.py'''     ,       ''''''							)]
	__UpperCAmelCase      					=      '''.'''.join(UpperCamelCase__							)

	return test_module_path





def    lowerCAmelCase       (		UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_module_path(UpperCamelCase__							)
	__UpperCAmelCase      					=      importlib.import_module(UpperCamelCase__							)

	return test_module





def    lowerCAmelCase       (		UpperCamelCase__					: Tuple							):


	"""simple docstring"""
	__UpperCAmelCase      					=      []
	__UpperCAmelCase      					=      get_test_module(UpperCamelCase__							)
	for attr in dir(UpperCamelCase__							):
		if attr.endswith('''ModelTester'''							):
			tester_classes.append(getattr(UpperCamelCase__     ,       UpperCamelCase__							)							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: List[Any]							):


	"""simple docstring"""
	__UpperCAmelCase      					=      []
	__UpperCAmelCase      					=      get_test_module(UpperCamelCase__							)
	for attr in dir(UpperCamelCase__							):
		__UpperCAmelCase      					=      getattr(UpperCamelCase__     ,       UpperCamelCase__							)
		# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
		# `all_model_classes` is not empty (which also excludes other special classes).
		__UpperCAmelCase      					=      getattr(UpperCamelCase__     ,       '''all_model_classes'''     ,       []							)
		if len(UpperCamelCase__							) > 0:
			test_classes.append(UpperCamelCase__							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: str							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      set()
	for test_class in test_classes:
		model_classes.update(test_class.all_model_classes							)

	# sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: Any							):


	"""simple docstring"""
	__UpperCAmelCase      					=      test_class()
	if hasattr(UpperCamelCase__     ,       '''setUp'''							):
		test.setUp()

	__UpperCAmelCase      					=      None
	if hasattr(UpperCamelCase__     ,       '''model_tester'''							):
		# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
		if test.model_tester is not None:
			__UpperCAmelCase      					=      test.model_tester.__class__

	return model_tester





def    lowerCAmelCase       (		UpperCamelCase__					: Dict     ,       UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes(UpperCamelCase__							)

	__UpperCAmelCase      					=      []
	for test_class in test_classes:
		if model_class in test_class.all_model_classes:
			target_test_classes.append(UpperCamelCase__							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: Tuple     ,       UpperCamelCase__					: Any							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes_for_model(UpperCamelCase__     ,       UpperCamelCase__							)

	__UpperCAmelCase      					=      []
	for test_class in test_classes:
		__UpperCAmelCase      					=      get_model_tester_from_test_class(UpperCamelCase__							)
		if tester_class is not None:
			tester_classes.append(UpperCamelCase__							)

    # sort with class names
	return sorted(UpperCamelCase__     ,       key=lambda UpperCamelCase__							: x.__name__							)





def    lowerCAmelCase       (		UpperCamelCase__					: int							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_test_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      {test_class: get_model_tester_from_test_class(UpperCamelCase__							) for test_class in test_classes}
	return test_tester_mapping





def    lowerCAmelCase       (		UpperCamelCase__					: str							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_model_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      {
	    model_class: get_test_classes_for_model(UpperCamelCase__     ,       UpperCamelCase__							) for model_class in model_classes
	}
	return model_test_mapping





def    lowerCAmelCase       (		UpperCamelCase__					: Optional[int]							):


	"""simple docstring"""
	__UpperCAmelCase      					=      get_model_classes(UpperCamelCase__							)
	__UpperCAmelCase      					=      {
	    model_class: get_tester_classes_for_model(UpperCamelCase__     ,       UpperCamelCase__							) for model_class in model_classes
	}
	return model_to_tester_mapping





def    lowerCAmelCase       (		UpperCamelCase__					: Tuple							):


	"""simple docstring"""
	if isinstance(UpperCamelCase__     ,       UpperCamelCase__							):
		return o
	elif isinstance(UpperCamelCase__     ,       UpperCamelCase__							):
		return o.__name__
	elif isinstance(UpperCamelCase__     ,       (list, tuple)							):
		return [to_json(UpperCamelCase__							) for x in o]
	elif isinstance(UpperCamelCase__     ,       UpperCamelCase__							):
		return {to_json(UpperCamelCase__							): to_json(UpperCamelCase__							) for k, v in o.items()}
	else:
		return o
