


import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class _lowerCamelCase(		_a     ):
       lowercase_				:			List[Any]									=    ["""image_processor""", """tokenizer"""]
       lowercase_				:			Optional[int]									=    """ViTImageProcessor"""
       lowercase_				:			Dict									=    ("""CLIPTokenizer""", """CLIPTokenizerFast""")
       def __init__(      self,   lowerCamelCase=None,   lowerCamelCase=None,   **lowerCamelCase) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							List[str]   	=	None
           if "feature_extractor" in kwargs:
               warnings.warn(
                   'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                   ' instead.',   lowerCamelCase,   )
               _lowercase :							Any   	=	kwargs.pop('feature_extractor')

           _lowercase :							str   	=	image_processor if image_processor is not None else feature_extractor
           if image_processor is None:
               raise ValueError('You need to specify an `image_processor`.')
           if tokenizer is None:
               raise ValueError('You need to specify a `tokenizer`.')

           super().__init__(lowerCamelCase,   lowerCamelCase)
       def __call__(      self,   lowerCamelCase=None,   lowerCamelCase=None,   lowerCamelCase=None,   lowerCamelCase=None,   **lowerCamelCase) ->     int:




           """simple docstring"""

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

           if text is not None and visual_prompt is not None:
               raise ValueError('You have to specify exactly one type of prompt. Either text or visual prompt.')

           if text is not None:
               _lowercase :							List[Any]   	=	self.tokenizer(lowerCamelCase,   return_tensors=lowerCamelCase,   **lowerCamelCase)

           if visual_prompt is not None:
               _lowercase :							str   	=	self.image_processor(lowerCamelCase,   return_tensors=lowerCamelCase,   **lowerCamelCase)

           if images is not None:
               _lowercase :							Dict   	=	self.image_processor(lowerCamelCase,   return_tensors=lowerCamelCase,   **lowerCamelCase)

           if visual_prompt is not None and images is not None:
               _lowercase :							Union[str, Any]   	=	{
                   'pixel_values': image_features.pixel_values,
                   'conditional_pixel_values': prompt_features.pixel_values,
               }
               return encoding
           elif text is not None and images is not None:
               _lowercase :							str   	=	image_features.pixel_values
               return encoding
           elif text is not None:
               return encoding
           elif visual_prompt is not None:
               _lowercase :							Optional[Any]   	=	{
                   'conditional_pixel_values': prompt_features.pixel_values,
               }
               return encoding
           else:
               return BatchEncoding(data=dict(**lowerCamelCase),   tensor_type=lowerCamelCase)
       def     UpperCamelCase  (      self,   *lowerCamelCase,   **lowerCamelCase) ->     Union[str, Any]:




           """simple docstring"""

           return self.tokenizer.batch_decode(*lowerCamelCase,   **lowerCamelCase)
       def     UpperCamelCase  (      self,   *lowerCamelCase,   **lowerCamelCase) ->     Any:




           """simple docstring"""

           return self.tokenizer.decode(*lowerCamelCase,   **lowerCamelCase)
       @property
       def     UpperCamelCase  (      self) ->     List[Any]:




           """simple docstring"""

           warnings.warn(
               '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.',   lowerCamelCase,   )
           return self.image_processor_class




       @property
       def     UpperCamelCase  (      self) ->     List[str]:




           """simple docstring"""

           warnings.warn(
               '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.',   lowerCamelCase,   )
           return self.image_processor






# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


SCREAMING_SNAKE_CASE :   List[Any]							      =				subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8")
SCREAMING_SNAKE_CASE :   Optional[int]							      =				(
    subprocess.check_output(F"git diff --diff-filter=d --name-only {fork_point_sha}".split()).decode("utf-8").split()
)

SCREAMING_SNAKE_CASE :   Any							      =				"|".join(sys.argv[1:])
SCREAMING_SNAKE_CASE :   Union[str, Any]							      =				re.compile(rF"^({joined_dirs}).*?\.py$")

SCREAMING_SNAKE_CASE :   List[Any]							      =				[x for x in modified_files if regex.match(x)]
print(" ".join(relevant_modified_files), end="")


