
from typing import Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_images
from ...utils import TensorType, logging


__lowerCamelCase							=       logging.get_logger(__name__)






class   UpperCAmelCase		(						A_ ):
   A__					:		Any						     =     ["pixel_values"]



   def __init__(self		:					str    ,						snake_case__		:					bool = True    ,						snake_case__		:					Union[int, float] = 1 / 2_55    ,						snake_case__		:					bool = True    ,						snake_case__		:					int = 8    ,						**snake_case__		:					str    ,						)		->	None:


          '''simple docstring'''


          super().__init__(**snake_case__ )

          snake_case       :   Optional[Any]							=      do_rescale
          snake_case       :   Union[str, Any]							=      rescale_factor
          snake_case       :   str							=      do_pad
          snake_case       :   Union[str, Any]							=      pad_size



   def 				_SCREAMING_SNAKE_CASE   (self		:					int    ,						snake_case__		:					np.ndarray    ,						snake_case__		:					float    ,						snake_case__		:					Optional[Union[str, ChannelDimension]] = None    ,						**snake_case__		:					Union[str, Any] )		->	np.ndarray:


          '''simple docstring'''


          return rescale(snake_case__    ,						scale=snake_case__    ,						data_format=snake_case__    ,						**snake_case__ )



   def 				_SCREAMING_SNAKE_CASE   (self		:					List[str]    ,						snake_case__		:					np.ndarray    ,						snake_case__		:					int    ,						snake_case__		:					Optional[Union[str, ChannelDimension]] = None )		->	Optional[int]:


          '''simple docstring'''


          snake_case				,					snake_case       :   Tuple							=      get_image_size(snake_case__ )
          snake_case       :   List[Any]							=      (old_height // size + 1) * size - old_height
          snake_case       :   int							=      (old_width // size + 1) * size - old_width

          return pad(snake_case__    ,						((0, pad_height), (0, pad_width))    ,						mode="symmetric"    ,						data_format=snake_case__ )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Any    ,						snake_case__		:					ImageInput    ,						snake_case__		:					Optional[bool] = None    ,						snake_case__		:					Optional[float] = None    ,						snake_case__		:					Optional[bool] = None    ,						snake_case__		:					Optional[int] = None    ,						snake_case__		:					Optional[Union[str, TensorType]] = None    ,						snake_case__		:					Union[str, ChannelDimension] = ChannelDimension.FIRST    ,						**snake_case__		:					Tuple    ,						)		->	List[str]:


          '''simple docstring'''


          snake_case       :   Optional[int]							=      do_rescale if do_rescale is not None else self.do_rescale
          snake_case       :   Tuple							=      rescale_factor if rescale_factor is not None else self.rescale_factor
          snake_case       :   int							=      do_pad if do_pad is not None else self.do_pad
          snake_case       :   Tuple							=      pad_size if pad_size is not None else self.pad_size

          snake_case       :   Tuple							=      make_list_of_images(snake_case__ )

          if not valid_images(snake_case__ ):
                 raise ValueError(
                     "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
                     "torch.Tensor, tf.Tensor or jax.ndarray." )

          if do_rescale and rescale_factor is None:
                 raise ValueError("Rescale factor must be specified if do_rescale is True." )

          # All transformations expect numpy arrays.
          snake_case       :   List[str]							=      [to_numpy_array(snake_case__ ) for image in images]

          if do_rescale:
                 snake_case       :   Optional[Any]							=      [self.rescale(image=snake_case__    ,						scale=snake_case__ ) for image in images]

          if do_pad:
                 snake_case       :   List[str]							=      [self.pad(snake_case__    ,						size=snake_case__ ) for image in images]

          snake_case       :   Any							=      [to_channel_dimension_format(snake_case__    ,						snake_case__ ) for image in images]

          snake_case       :   Tuple							=      {"pixel_values": images}
          return BatchFeature(data=snake_case__    ,						tensor_type=snake_case__ )







"""simple docstring"""




import logging
import os
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


UpperCAmelCase__      :    Optional[int]    							= {
    'debug': logging.DEBUG,
    'info': logging.INFO,
    'warning': logging.WARNING,
    'error': logging.ERROR,
    'critical': logging.CRITICAL,
}

UpperCAmelCase__      :    List[Any]    							= logging.WARNING

def lowercase_  (   ):
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   os.getenv("""DATASETS_VERBOSITY"""   ,_snake_case						)
							if env_level_str:
														if env_level_str in log_levels:
																					return log_levels[env_level_str]
														else:
																					logging.getLogger().warning(
																					    f'''Unknown option DATASETS_VERBOSITY={env_level_str}, '''
																					    f'''has to be one of: { ', '.join(log_levels.keys()						) }'''						)
							return _default_log_level

def lowercase_  (   ):
							return __name__.split("""."""						)[0]

def lowercase_  (   ):
							return logging.getLogger(_get_library_name()						)

def lowercase_  (   ):
							# Apply our default configuration to the library root logger.
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   _get_library_root_logger()
							library_root_logger.setLevel(_get_default_logging_level()						)

def lowercase_  (   ):
							SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   _get_library_root_logger()
							library_root_logger.setLevel(logging.NOTSET						)

def lowercase_  (   _snake_case = None						):
							if name is None:
														SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   _get_library_name()
							return logging.getLogger(_snake_case						)

def lowercase_  (   ):
							return _get_library_root_logger().getEffectiveLevel()

def lowercase_  (   _snake_case						):
							_get_library_root_logger().setLevel(_snake_case						)

def lowercase_  (   ):
							return set_verbosity(_snake_case						)

def lowercase_  (   ):
							return set_verbosity(_snake_case						)

def lowercase_  (   ):
							return set_verbosity(_snake_case						)

def lowercase_  (   ):
							return set_verbosity(_snake_case						)

def lowercase_  (   ):
							SCREAMING_SNAKE_CASE__						:       Tuple           =   False

def lowercase_  (   ):
							SCREAMING_SNAKE_CASE__						:       str           =   True


# Configure the library root logger at the module level (singleton-like)
_configure_library_root_logger()



class 	lowerCAmelCase_						:


				"""simple docstring"""



				def __init__(self   ,       *SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )					->		int:  # pylint: disable=unused-argument



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       List[str]           =   args[0] if args else None



				def __iter__(self    )					->		int:



											"""simple docstring"""




											return iter(self._iterator    )



				def __getattr__(self   ,       SCREAMING_SNAKE_CASE__    )					->		int:



											"""simple docstring"""




											def empty_fn(*SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    ):  # pylint: disable=unused-argument
																		return

											return empty_fn



				def __enter__(self    )					->		Dict:



											"""simple docstring"""




											return self



				def __exit__(self   ,       SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__    )					->		str:



											"""simple docstring"""




											return






UpperCAmelCase__      :    str    							= True



class 	lowerCAmelCase_						:


				"""simple docstring"""



				def __call__(self   ,       *SCREAMING_SNAKE_CASE__   ,       SCREAMING_SNAKE_CASE__=False   ,       **SCREAMING_SNAKE_CASE__    )					->		List[Any]:



											"""simple docstring"""




											if _tqdm_active and not disable:
																		return tqdm_lib.tqdm(*SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )
											else:
																		return EmptyTqdm(*SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self   ,       *SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )					->		int:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       List[Any]           =   None
											if _tqdm_active:
																		return tqdm_lib.tqdm.set_lock(*SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )



				def 	__magic_name__    (self    )					->		Optional[Any]:



											"""simple docstring"""




											if _tqdm_active:
																		return tqdm_lib.tqdm.get_lock()






UpperCAmelCase__      :    Tuple    							= _tqdm_cls()

def lowercase_  (   ):
							global _tqdm_active
							return bool(_tqdm_active						)

def lowercase_  (   ):
							global _tqdm_active
							SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   True

def lowercase_  (   ):
							global _tqdm_active
							SCREAMING_SNAKE_CASE__						:       str           =   False




