






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						:		Optional[Any]				      = logging.get_logger(__name__)







class 			_lowercase ( lowerCAmelCase__    ):
      _a				:    Optional[Any]				      =				['pixel_values']
      def __init__(  self					,      a = True					,      a = 1 / 2_5_5					,      a = True					,      a = 8					,      **a					,      ):
       super().__init__(**__UpperCAmelCase )

       snake_case__	:     Tuple											=do_rescale
       snake_case__	:     Tuple											=rescale_factor
       snake_case__	:     Union[str, Any]											=do_pad
       snake_case__	:     List[Any]											=pad_size
      def     lowercase__       (  self					,      a					,      a					,      a = None					,      **a ):
       return rescale(__UpperCAmelCase					,      scale=__UpperCAmelCase					,      data_format=__UpperCAmelCase					,      **__UpperCAmelCase )
      def     lowercase__       (  self					,      a					,      a					,      a = None ):
       snake_case__							, snake_case__	:     Union[str, Any]											=get_image_size(__UpperCAmelCase )
       snake_case__	:     Union[str, Any]											=(old_height // size + 1) * size - old_height
       snake_case__	:     Any											=(old_width // size + 1) * size - old_width

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



      def     lowercase__       (  self					,      a					,      a = None					,      a = None					,      a = None					,      a = None					,      a = None					,      a = ChannelDimension.FIRST					,      **a					,      ):
       snake_case__	:     Dict											=do_rescale if do_rescale is not None else self.do_rescale
       snake_case__	:     str											=rescale_factor if rescale_factor is not None else self.rescale_factor
       snake_case__	:     List[str]											=do_pad if do_pad is not None else self.do_pad
       snake_case__	:     Dict											=pad_size if pad_size is not None else self.pad_size

       snake_case__	:     Optional[int]											=make_list_of_images(__UpperCAmelCase )

       if not valid_images(__UpperCAmelCase ):
        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__	:     Dict											=[to_numpy_array(__UpperCAmelCase ) for image in images]

       if do_rescale:
        snake_case__	:     str											=[self.rescale(image=__UpperCAmelCase					,      scale=__UpperCAmelCase ) for image in images]

       if do_pad:
        snake_case__	:     Union[str, Any]											=[self.pad(__UpperCAmelCase					,      size=__UpperCAmelCase ) for image in images]

       snake_case__	:     Dict											=[to_channel_dimension_format(__UpperCAmelCase					,      __UpperCAmelCase ) for image in images]

       snake_case__	:     Optional[Any]											={"""pixel_values""": images}
       return BatchFeature(data=__UpperCAmelCase					,      tensor_type=__UpperCAmelCase )










def 		a__      (		_UpperCamelCase      :			str				):
   if not all(x.isalpha() for x in string				):
      raise ValueError('''String must only contain alphabetic characters.'''				)

   __lowerCamelCase    				=     sorted(string.lower()				)
   return len(_UpperCamelCase				) == len(set(_UpperCamelCase				)				)


if __name__ == "__main__":
  a_								=       input("""Enter a string """).strip()

  a_								=       is_isogram(input_str)
  print(f"{input_str} is {'an' if isogram else 'not an'} isogram.")






