


"""simple docstring"""



import os
from typing import List, Optional, Union

from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
from ..auto import AutoTokenizer







class _lowerCAmelCase							( __UpperCamelCase      ):
   __UpperCAmelCase					:			Union[str, Any]				    =    ["image_processor", "tokenizer"]
   __UpperCAmelCase					:			List[str]				    =    "BlipImageProcessor"
   __UpperCAmelCase					:			int				    =    "AutoTokenizer"







   def __init__(      self		,      UpperCamelCase__		,      UpperCamelCase__		,      UpperCamelCase__		)      ->						List[str]:

       '''simple docstring'''




       super().__init__(snake_case__		,      snake_case__		)

       # add QFormer tokenizer
       snake_case       : Any    =       qformer_tokenizer







   def __call__(      self		,      UpperCamelCase__ = None		,      UpperCamelCase__ = None		,      UpperCamelCase__ = True		,      UpperCamelCase__ = False		,      UpperCamelCase__ = None		,      UpperCamelCase__ = None		,      UpperCamelCase__ = 0		,      UpperCamelCase__ = None		,      UpperCamelCase__ = None		,      UpperCamelCase__ = False		,      UpperCamelCase__ = False		,      UpperCamelCase__ = False		,      UpperCamelCase__ = False		,      UpperCamelCase__ = False		,      UpperCamelCase__ = True		,      UpperCamelCase__ = None		,      **UpperCamelCase__		,      )      ->						Optional[int]:

       '''simple docstring'''




       if images is None and text is None:
           raise ValueError("You have to specify at least images or text."		)

       snake_case       : List[str]    =       BatchFeature()

       if text is not None:
           snake_case       : List[str]    =       self.tokenizer(
               text=snake_case__		,      add_special_tokens=snake_case__		,      padding=snake_case__		,      truncation=snake_case__		,      max_length=snake_case__		,      stride=snake_case__		,      pad_to_multiple_of=snake_case__		,      return_attention_mask=snake_case__		,      return_overflowing_tokens=snake_case__		,      return_special_tokens_mask=snake_case__		,      return_offsets_mapping=snake_case__		,      return_token_type_ids=snake_case__		,      return_length=snake_case__		,      verbose=snake_case__		,      return_tensors=snake_case__		,      **snake_case__		,      )
           encoding.update(snake_case__		)
           snake_case       : Any    =       self.qformer_tokenizer(
               text=snake_case__		,      add_special_tokens=snake_case__		,      padding=snake_case__		,      truncation=snake_case__		,      max_length=snake_case__		,      stride=snake_case__		,      pad_to_multiple_of=snake_case__		,      return_attention_mask=snake_case__		,      return_overflowing_tokens=snake_case__		,      return_special_tokens_mask=snake_case__		,      return_offsets_mapping=snake_case__		,      return_token_type_ids=snake_case__		,      return_length=snake_case__		,      verbose=snake_case__		,      return_tensors=snake_case__		,      **snake_case__		,      )
           snake_case       : Any    =       qformer_text_encoding.pop("input_ids"		)
           snake_case       : Dict    =       qformer_text_encoding.pop("attention_mask"		)

       if images is not None:
           snake_case       : Optional[int]    =       self.image_processor(snake_case__		,      return_tensors=snake_case__		)
           encoding.update(snake_case__		)

       return encoding







   def 					lowerCamelCase						(      self		,      *UpperCamelCase__		,      **UpperCamelCase__		)      ->						Dict:

       '''simple docstring'''




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







   def 					lowerCamelCase						(      self		,      *UpperCamelCase__		,      **UpperCamelCase__		)      ->						int:

       '''simple docstring'''




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







   @property
   # Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
   def 					lowerCamelCase						(      self		)      ->						Union[str, Any]:

       '''simple docstring'''




       snake_case       : Optional[int]    =       self.tokenizer.model_input_names
       snake_case       : List[str]    =       self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		,      **UpperCamelCase__		)      ->						int:

       '''simple docstring'''




       if os.path.isfile(snake_case__		):
           raise ValueError(F'Provided path ({save_directory}) should be a directory, not a file'		)
       os.makedirs(snake_case__		,      exist_ok=snake_case__		)
       snake_case       : Union[str, Any]    =       os.path.join(snake_case__		,      "qformer_tokenizer"		)
       self.qformer_tokenizer.save_pretrained(snake_case__		)
       return super().save_pretrained(snake_case__		,      **snake_case__		)







   @classmethod
   def 					lowerCamelCase						(      cls		,      UpperCamelCase__		,      **UpperCamelCase__		)      ->						List[str]:

       '''simple docstring'''




       snake_case       : Union[str, Any]    =       AutoTokenizer.from_pretrained(snake_case__		,      subfolder="qformer_tokenizer"		)
       snake_case       : Tuple    =       cls._get_arguments_from_pretrained(snake_case__		,      **snake_case__		)
       args.append(snake_case__		)
       return cls(*snake_case__		)






"""simple docstring"""




from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap







def 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		return getitem, k







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__  ):





		"""simple docstring"""




		return setitem, k, v







def 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		return delitem, k







def 				_UpperCAmelCase		(							lowerCamelCase__      ,	lowerCamelCase__      ,	*lowerCamelCase__  ):





		"""simple docstring"""




		try:
				return fun(lowerCamelCase__      ,	*lowerCamelCase__  ), None
		except Exception as e:
				return None, e


__lowerCAmelCase     :				Optional[Any]    				=    (
    _set("key_a", "val_a"),
    _set("key_b", "val_b"),
)

__lowerCAmelCase     :				Optional[int]    				=    [
    _set("key_a", "val_a"),
    _set("key_a", "val_b"),
]

__lowerCAmelCase     :				List[Any]    				=    [
    _set("key_a", "val_a"),
    _set("key_b", "val_b"),
    _del("key_a"),
    _del("key_b"),
    _set("key_a", "val_a"),
    _del("key_a"),
]

__lowerCAmelCase     :				int    				=    [
    _get("key_a"),
    _del("key_a"),
    _set("key_a", "val_a"),
    _del("key_a"),
    _del("key_a"),
    _get("key_a"),
]

__lowerCAmelCase     :				Optional[Any]    				=    [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

__lowerCAmelCase     :				Any    				=    [
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("key_a", "val_b"),
]







@pytest.mark.parametrize(
    """operations"""      ,	(
        pytest.param(_add_items      ,	id="""add items"""  ),
        pytest.param(_overwrite_items      ,	id="""overwrite items"""  ),
        pytest.param(_delete_items      ,	id="""delete items"""  ),
        pytest.param(_access_absent_items      ,	id="""access absent items"""  ),
        pytest.param(_add_with_resize_up      ,	id="""add with resize up"""  ),
        pytest.param(_add_with_resize_down      ,	id="""add with resize down"""  ),
    )      ,	)
def 				_UpperCAmelCase		(							lowerCamelCase__  ):





		"""simple docstring"""




		lowerCAmelCase__   = HashMap(initial_block_size=4  )
		lowerCAmelCase__   = {}
		for _, (fun, *args) in enumerate(lowerCamelCase__  ):
				lowerCAmelCase__ ,       lowerCAmelCase__   = _run_operation(lowerCamelCase__      ,	lowerCamelCase__      ,	*lowerCamelCase__  )
				lowerCAmelCase__ ,       lowerCAmelCase__   = _run_operation(lowerCamelCase__      ,	lowerCamelCase__      ,	*lowerCamelCase__  )
				assert my_res == py_res
				assert str(lowerCamelCase__  ) == str(lowerCamelCase__  )
				assert set(lowerCamelCase__  ) == set(lowerCamelCase__  )
				assert len(lowerCamelCase__  ) == len(lowerCamelCase__  )
				assert set(my.items()  ) == set(py.items()  )







def 				_UpperCAmelCase		(							):





		"""simple docstring"""




		def is_public(lowerCamelCase__  ) -> bool:
				return not name.startswith("""_"""  )

		lowerCAmelCase__   = {name for name in dir({}  ) if is_public(lowerCamelCase__  )}
		lowerCAmelCase__   = {name for name in dir(HashMap()  ) if is_public(lowerCamelCase__  )}

		assert dict_public_names > hash_public_names




