


from typing import List

import numpy as np


def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
     lowercase_  							=			{key: len(A_  ) for key, value in gen_kwargs.items() if isinstance(A_						,							A_  )}
     if len(set(lists_lengths.values()  )  ) > 1:
          raise RuntimeError(
              (
                  """Sharding is ambiguous for this dataset: """
                  + """we found several data sources lists of different lengths, and we don't know over which list we should parallelize:\n"""
                  + """\n""".join(F'''\t- key {key} has length {length}''' for key, length in lists_lengths.items()  )
                  + """\nTo fix this, check the 'gen_kwargs' and make sure to use lists only for data sources, """
                  + """and use tuples otherwise. In the end there should only be one single list, or several lists with the same length."""
              )  )
     lowercase_  							=			max(lists_lengths.values()						,							default=0  )
     return max(1						,							A_  )


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__  ):
     lowercase_  							=			[]
     for group_idx in range(A_  ):
          lowercase_  							=			num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
          if num_shards_to_add == 0:
               break
          lowercase_  							=			shards_indices_per_group[-1].stop if shards_indices_per_group else 0
          lowercase_  							=			range(A_						,							start + num_shards_to_add  )
          shards_indices_per_group.append(A_  )
     return shards_indices_per_group


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__  ):
     lowercase_  							=			_number_of_shards_in_gen_kwargs(A_  )
     if num_shards == 1:
          return [dict(A_  )]
     else:
          lowercase_  							=			_distribute_shards(num_shards=A_						,							max_num_jobs=A_  )
          return [
              {
                  key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
                  if isinstance(A_						,							A_  )
                  else value
                  for key, value in gen_kwargs.items()
              }
              for group_idx in range(len(A_  )  )
          ]


def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
     return {
         key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
         if isinstance(gen_kwargs_list[0][key]						,							A_  )
         else gen_kwargs_list[0][key]
         for key in gen_kwargs_list[0]
     }



def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__  ):
     lowercase_  							=			{len(A_  ) for value in gen_kwargs.values() if isinstance(A_						,							A_  )}
     lowercase_  							=			{}
     for size in list_sizes:
          lowercase_  							=			list(range(A_  )  )
          rng.shuffle(indices_per_size[size]  )
     # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
     lowercase_  							=			dict(A_  )
     for key, value in shuffled_kwargs.items():
          if isinstance(A_						,							A_  ):
               lowercase_  							=			[value[i] for i in indices_per_size[len(A_  )]]
     return shuffled_kwargs






import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
							a					  =     {
							    'linear': PIL.Image.Resampling.BILINEAR,
							    'bilinear': PIL.Image.Resampling.BILINEAR,
							    'bicubic': PIL.Image.Resampling.BICUBIC,
							    'lanczos': PIL.Image.Resampling.LANCZOS,
							    'nearest': PIL.Image.Resampling.NEAREST,
							}
else:
							a					  =     {
							    'linear': PIL.Image.LINEAR,
							    'bilinear': PIL.Image.BILINEAR,
							    'bicubic': PIL.Image.BICUBIC,
							    'lanczos': PIL.Image.LANCZOS,
							    'nearest': PIL.Image.NEAREST,
							}


def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
					lowercase_  							=			(images / 2 + 0.5).clamp(0						,							1  )
					lowercase_  							=			images.cpu().permute(0						,							2						,							3						,							1  ).float().numpy()
					lowercase_  							=			numpy_to_pil(UpperCAmelCase__  )
					return images



def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
					if images.ndim == 3:
										lowercase_  							=			images[None, ...]
					lowercase_  							=			(images * 2_5_5).round().astype("""uint8"""  )
					if images.shape[-1] == 1:
										# special case for grayscale (single channel) images
										lowercase_  							=			[Image.fromarray(image.squeeze()						,							mode="""L"""  ) for image in images]
					else:
										lowercase_  							=			[Image.fromarray(UpperCAmelCase__  ) for image in images]

					return pil_images


