


import argparse
import os
import re


UpperCamelCase								=	"""src/transformers"""

# Pattern that looks at the indentation in a line.
UpperCamelCase								=	re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCamelCase								=	re.compile(r"""^\s*\"([^\"]+)\":""")
# Pattern that matches `_import_structure["key"]` and puts `key` in group 0.
UpperCamelCase								=	re.compile(r"""^\s*_import_structure\[\"([^\"]+)\"\]""")
# Pattern that matches `"key",` and puts `key` in group 0.
UpperCamelCase								=	re.compile(r"""^\s*\"([^\"]+)\",\s*$""")
# Pattern that matches any `[stuff]` and puts `stuff` in group 0.
UpperCamelCase								=	re.compile(r"""\[([^\]]+)\]""")


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE       ):
  A_      :				Optional[Any]		     =					_re_indent.search(SCREAMING_SNAKE_CASE       )
  return "" if search is None else search.groups()[0]


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE ,			SCREAMING_SNAKE_CASE="" ,			SCREAMING_SNAKE_CASE=None ,			SCREAMING_SNAKE_CASE=None       ):
  A_      :				str		     =					0
  A_      :				Optional[Any]		     =					code.split('''\n'''       )
  if start_prompt is not None:
    while not lines[index].startswith(SCREAMING_SNAKE_CASE       ):
      index += 1
    A_      :				Tuple		     =					['''\n'''.join(lines[:index]       )]
  else:
    A_      :				Dict		     =					[]

  # We split into blocks until we get to the `end_prompt` (or the end of the block).
  A_      :				Optional[int]		     =					[lines[index]]
  index += 1
  while index < len(SCREAMING_SNAKE_CASE       ) and (end_prompt is None or not lines[index].startswith(SCREAMING_SNAKE_CASE       )):
    if len(lines[index]       ) > 0 and get_indent(lines[index]       ) == indent_level:
      if len(SCREAMING_SNAKE_CASE       ) > 0 and get_indent(current_block[-1]       ).startswith(indent_level + ''' '''       ):
        current_block.append(lines[index]       )
        blocks.append('''\n'''.join(SCREAMING_SNAKE_CASE       )       )
        if index < len(SCREAMING_SNAKE_CASE       ) - 1:
          A_      :				List[str]		     =					[lines[index + 1]]
          index += 1
        else:
          A_      :				Union[str, Any]		     =					[]
      else:
        blocks.append('''\n'''.join(SCREAMING_SNAKE_CASE       )       )
        A_      :				Union[str, Any]		     =					[lines[index]]
    else:
      current_block.append(lines[index]       )
    index += 1

  # Adds current block if it's nonempty.
  if len(SCREAMING_SNAKE_CASE       ) > 0:
    blocks.append('''\n'''.join(SCREAMING_SNAKE_CASE       )       )

  # Add final block after end_prompt if provided.
  if end_prompt is not None and index < len(SCREAMING_SNAKE_CASE       ):
    blocks.append('''\n'''.join(lines[index:]       )       )

  return blocks


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE       ):

  def _inner(SCREAMING_SNAKE_CASE       ):
    return key(SCREAMING_SNAKE_CASE       ).lower().replace('''_''' ,			''''''       )

  return _inner


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE ,			SCREAMING_SNAKE_CASE=None       ):

  # If no key is provided, we use a noop.
  def noop(SCREAMING_SNAKE_CASE       ):
    return x

  if key is None:
    A_      :				Union[str, Any]		     =					noop
  # Constants are all uppercase, they go first.
  A_      :				Optional[Any]		     =					[obj for obj in objects if key(SCREAMING_SNAKE_CASE       ).isupper()]
  # Classes are not all uppercase but start with a capital, they go second.
  A_      :				List[Any]		     =					[obj for obj in objects if key(SCREAMING_SNAKE_CASE       )[0].isupper() and not key(SCREAMING_SNAKE_CASE       ).isupper()]
  # Functions begin with a lowercase, they go last.
  A_      :				Union[str, Any]		     =					[obj for obj in objects if not key(SCREAMING_SNAKE_CASE       )[0].isupper()]

  A_      :				Union[str, Any]		     =					ignore_underscore(SCREAMING_SNAKE_CASE       )
  return sorted(SCREAMING_SNAKE_CASE ,			key=SCREAMING_SNAKE_CASE       ) + sorted(SCREAMING_SNAKE_CASE ,			key=SCREAMING_SNAKE_CASE       ) + sorted(SCREAMING_SNAKE_CASE ,			key=SCREAMING_SNAKE_CASE       )


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE       ):

  # This inner function sort imports between [ ].
  def _replace(SCREAMING_SNAKE_CASE       ):
    A_      :				List[Any]		     =					match.groups()[0]
    if "," not in imports:
      return f'''[{imports}]'''
    A_      :				Optional[Any]		     =					[part.strip().replace('''"''' ,			''''''       ) for part in imports.split(''','''       )]
    # We will have a final empty element if the line finished with a comma.
    if len(keys[-1]       ) == 0:
      A_      :				List[str]		     =					keys[:-1]
    return "[" + ", ".join([f'''"{k}"''' for k in sort_objects(SCREAMING_SNAKE_CASE       )]       ) + "]"

  A_      :				Dict		     =					import_statement.split('''\n'''       )
  if len(SCREAMING_SNAKE_CASE       ) > 3:
    # Here we have to sort internal imports that are on several lines (one per name):
    # key: [
    #     "object1",
    #     "object2",
    #     ...
    # ]

    # We may have to ignore one or two lines on each side.
    A_      :				Dict		     =					2 if lines[1].strip() == '''[''' else 1
    A_      :				Tuple		     =					[(i, _re_strip_line.search(SCREAMING_SNAKE_CASE       ).groups()[0]) for i, line in enumerate(lines[idx:-idx]       )]
    A_      :				Tuple		     =					sort_objects(SCREAMING_SNAKE_CASE ,			key=lambda SCREAMING_SNAKE_CASE       : x[1]       )
    A_      :				str		     =					[lines[x[0] + idx] for x in sorted_indices]
    return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]       )
  elif len(SCREAMING_SNAKE_CASE       ) == 3:
    # Here we have to sort internal imports that are on one separate line:
    # key: [
    #     "object1", "object2", ...
    # ]
    if _re_bracket_content.search(lines[1]       ) is not None:
      A_      :				Tuple		     =					_re_bracket_content.sub(_replace ,			lines[1]       )
    else:
      A_      :				Optional[Any]		     =					[part.strip().replace('''"''' ,			''''''       ) for part in lines[1].split(''','''       )]
      # We will have a final empty element if the line finished with a comma.
      if len(keys[-1]       ) == 0:
        A_      :				str		     =					keys[:-1]
      A_      :				Dict		     =					get_indent(lines[1]       ) + ''', '''.join([f'''"{k}"''' for k in sort_objects(SCREAMING_SNAKE_CASE       )]       )
    return "\n".join(SCREAMING_SNAKE_CASE       )
  else:
    # Finally we have to deal with imports fitting on one line
    A_      :				List[Any]		     =					_re_bracket_content.sub(_replace ,			SCREAMING_SNAKE_CASE       )
    return import_statement


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE ,			SCREAMING_SNAKE_CASE=True       ):
  with open(SCREAMING_SNAKE_CASE ,			encoding='''utf-8'''       ) as f:
    A_      :				Any		     =					f.read()

  if "_import_structure" not in code:
    return

  # Blocks of indent level 0
  A_      :				int		     =					split_code_in_indented_blocks(
      SCREAMING_SNAKE_CASE ,			start_prompt='''_import_structure = {''' ,			end_prompt='''if TYPE_CHECKING:'''       )

  # We ignore block 0 (everything untils start_prompt) and the last block (everything after end_prompt).
  for block_idx in range(1 ,			len(SCREAMING_SNAKE_CASE       ) - 1       ):
    # Check if the block contains some `_import_structure`s thingy to sort.
    A_      :				Optional[Any]		     =					main_blocks[block_idx]
    A_      :				Any		     =					block.split('''\n'''       )

    # Get to the start of the imports.
    A_      :				Any		     =					0
    while line_idx < len(SCREAMING_SNAKE_CASE       ) and "_import_structure" not in block_lines[line_idx]:
      # Skip dummy import blocks
      if "import dummy" in block_lines[line_idx]:
        A_      :				str		     =					len(SCREAMING_SNAKE_CASE       )
      else:
        line_idx += 1
    if line_idx >= len(SCREAMING_SNAKE_CASE       ):
      continue

    # Ignore beginning and last line: they don't contain anything.
    A_      :				List[str]		     =					'''\n'''.join(block_lines[line_idx:-1]       )
    A_      :				Any		     =					get_indent(block_lines[1]       )
    # Slit the internal block into blocks of indent level 1.
    A_      :				Union[str, Any]		     =					split_code_in_indented_blocks(SCREAMING_SNAKE_CASE ,			indent_level=SCREAMING_SNAKE_CASE       )
    # We have two categories of import key: list or _import_structure[key].append/extend
    A_      :				Dict		     =					_re_direct_key if '''_import_structure = {''' in block_lines[0] else _re_indirect_key
    # Grab the keys, but there is a trap: some lines are empty or just comments.
    A_      :				Union[str, Any]		     =					[(pattern.search(SCREAMING_SNAKE_CASE       ).groups()[0] if pattern.search(SCREAMING_SNAKE_CASE       ) is not None else None) for b in internal_blocks]
    # We only sort the lines with a key.
    A_      :				List[Any]		     =					[(i, key) for i, key in enumerate(SCREAMING_SNAKE_CASE       ) if key is not None]
    A_      :				List[Any]		     =					[x[0] for x in sorted(SCREAMING_SNAKE_CASE ,			key=lambda SCREAMING_SNAKE_CASE       : x[1]       )]

    # We reorder the blocks by leaving empty lines/comments as they were and reorder the rest.
    A_      :				Tuple		     =					0
    A_      :				Union[str, Any]		     =					[]
    for i in range(len(SCREAMING_SNAKE_CASE       )       ):
      if keys[i] is None:
        reorderded_blocks.append(internal_blocks[i]       )
      else:
        A_      :				List[Any]		     =					sort_objects_in_import(internal_blocks[sorted_indices[count]]       )
        reorderded_blocks.append(SCREAMING_SNAKE_CASE       )
        count += 1

        # And we put our main block back together with its first and last line.
    A_      :				Union[str, Any]		     =					'''\n'''.join(block_lines[:line_idx] + reorderded_blocks + [block_lines[-1]]       )

  if code != "\n".join(SCREAMING_SNAKE_CASE       ):
    if check_only:
      return True
    else:
      print(f'''Overwriting {file}.'''       )
      with open(SCREAMING_SNAKE_CASE ,			'''w''' ,			encoding='''utf-8'''       ) as f:
        f.write('''\n'''.join(SCREAMING_SNAKE_CASE       )       )


def   _SCREAMING_SNAKE_CASE	( SCREAMING_SNAKE_CASE=True       ):
  A_      :				Optional[Any]		     =					[]
  for root, _, files in os.walk(SCREAMING_SNAKE_CASE       ):
    if "__init__.py" in files:
      A_      :				Any		     =					sort_imports(os.path.join(SCREAMING_SNAKE_CASE ,			'''__init__.py'''       ) ,			check_only=SCREAMING_SNAKE_CASE       )
      if result:
        A_      :				Tuple		     =					[os.path.join(SCREAMING_SNAKE_CASE ,			'''__init__.py'''       )]
  if len(SCREAMING_SNAKE_CASE       ) > 0:
    raise ValueError(f'''Would overwrite {len(SCREAMING_SNAKE_CASE       )} files, run `make style`.'''       )


if __name__ == "__main__":
     UpperCamelCase								=	argparse.ArgumentParser()
     parser.add_argument("""--check_only""", action="""store_true""", help="""Whether to only check or fix style.""")
     UpperCamelCase								=	parser.parse_args()

     sort_imports_in_all_inits(check_only=args.check_only)








from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    convert_to_rgb,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


UpperCamelCase								=	logging.get_logger(__name__)


if is_vision_available():
     import PIL






class   _lowerCamelCase (					UpperCamelCase			):




       """simple docstring"""
       snake_case      =    ["pixel_values"]



       def __init__(      self				,       _SCREAMING_SNAKE_CASE = True				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = PILImageResampling.BICUBIC				,       _SCREAMING_SNAKE_CASE = True				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = True				,       _SCREAMING_SNAKE_CASE = 1 / 255				,       _SCREAMING_SNAKE_CASE = True				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = True				,       **_SCREAMING_SNAKE_CASE				,       )->None:




         '''simple docstring'''





         super().__init__(**_SCREAMING_SNAKE_CASE		)
         A_      :				Tuple		     =					size if size is not None else {'''shortest_edge''': 224}
         A_      :				Any		     =					get_size_dict(_SCREAMING_SNAKE_CASE				,       default_to_square=_SCREAMING_SNAKE_CASE		)
         A_      :				Tuple		     =					crop_size if crop_size is not None else {'''height''': 224, '''width''': 224}
         A_      :				Dict		     =					get_size_dict(_SCREAMING_SNAKE_CASE				,       default_to_square=_SCREAMING_SNAKE_CASE				,       param_name='''crop_size'''		)

         A_      :				str		     =					do_resize
         A_      :				Tuple		     =					size
         A_      :				Optional[Any]		     =					resample
         A_      :				Tuple		     =					do_center_crop
         A_      :				List[Any]		     =					crop_size
         A_      :				Optional[int]		     =					do_rescale
         A_      :				Tuple		     =					rescale_factor
         A_      :				Any		     =					do_normalize
         A_      :				int		     =					image_mean if image_mean is not None else OPENAI_CLIP_MEAN
         A_      :				Any		     =					image_std if image_std is not None else OPENAI_CLIP_STD
         A_      :				Any		     =					do_convert_rgb



       def        _snake_case       (      self				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE = PILImageResampling.BICUBIC				,       _SCREAMING_SNAKE_CASE = None				,       **_SCREAMING_SNAKE_CASE				,       )->np.ndarray:




         '''simple docstring'''





         A_      :				Dict		     =					get_size_dict(_SCREAMING_SNAKE_CASE				,       default_to_square=_SCREAMING_SNAKE_CASE		)
         if "shortest_edge" not in size:
           raise ValueError(F'''The `size` parameter must contain the key `shortest_edge`. Got {size.keys()}'''		)
         A_      :				Any		     =					get_resize_output_image_size(_SCREAMING_SNAKE_CASE				,       size=size['''shortest_edge''']				,       default_to_square=_SCREAMING_SNAKE_CASE		)
         return resize(_SCREAMING_SNAKE_CASE				,       size=_SCREAMING_SNAKE_CASE				,       resample=_SCREAMING_SNAKE_CASE				,       data_format=_SCREAMING_SNAKE_CASE				,       **_SCREAMING_SNAKE_CASE		)



       def        _snake_case       (      self				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE = None				,       **_SCREAMING_SNAKE_CASE				,       )->np.ndarray:




         '''simple docstring'''





         A_      :				str		     =					get_size_dict(_SCREAMING_SNAKE_CASE		)
         if "height" not in size or "width" not in size:
           raise ValueError(F'''The `size` parameter must contain the keys (height, width). Got {size.keys()}'''		)
         return center_crop(_SCREAMING_SNAKE_CASE				,       size=(size['''height'''], size['''width'''])				,       data_format=_SCREAMING_SNAKE_CASE				,       **_SCREAMING_SNAKE_CASE		)



       def        _snake_case       (      self				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE = None				,       **_SCREAMING_SNAKE_CASE				,       )->int:




         '''simple docstring'''





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



       def        _snake_case       (      self				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE = None				,       **_SCREAMING_SNAKE_CASE				,       )->np.ndarray:




         '''simple docstring'''





         return normalize(_SCREAMING_SNAKE_CASE				,       mean=_SCREAMING_SNAKE_CASE				,       std=_SCREAMING_SNAKE_CASE				,       data_format=_SCREAMING_SNAKE_CASE				,       **_SCREAMING_SNAKE_CASE		)







       def        _snake_case       (      self				,       _SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = None				,       _SCREAMING_SNAKE_CASE = ChannelDimension.FIRST				,       **_SCREAMING_SNAKE_CASE				,       )->PIL.Image.Image:




         '''simple docstring'''





         A_      :				Optional[int]		     =					do_resize if do_resize is not None else self.do_resize
         A_      :				int		     =					size if size is not None else self.size
         A_      :				Optional[int]		     =					get_size_dict(_SCREAMING_SNAKE_CASE				,       param_name='''size'''				,       default_to_square=_SCREAMING_SNAKE_CASE		)
         A_      :				List[Any]		     =					resample if resample is not None else self.resample
         A_      :				Any		     =					do_center_crop if do_center_crop is not None else self.do_center_crop
         A_      :				List[str]		     =					crop_size if crop_size is not None else self.crop_size
         A_      :				int		     =					get_size_dict(_SCREAMING_SNAKE_CASE				,       param_name='''crop_size'''				,       default_to_square=_SCREAMING_SNAKE_CASE		)
         A_      :				Optional[int]		     =					do_rescale if do_rescale is not None else self.do_rescale
         A_      :				int		     =					rescale_factor if rescale_factor is not None else self.rescale_factor
         A_      :				int		     =					do_normalize if do_normalize is not None else self.do_normalize
         A_      :				Tuple		     =					image_mean if image_mean is not None else self.image_mean
         A_      :				Tuple		     =					image_std if image_std is not None else self.image_std
         A_      :				List[str]		     =					do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

         A_      :				Optional[int]		     =					make_list_of_images(_SCREAMING_SNAKE_CASE		)

         if not valid_images(_SCREAMING_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_resize and size is None:
           raise ValueError('''Size must be specified if do_resize is True.'''		)

         if do_center_crop and crop_size is None:
           raise ValueError('''Crop size must be specified if do_center_crop is True.'''		)

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

         if do_normalize and (image_mean is None or image_std is None):
           raise ValueError('''Image mean and std must be specified if do_normalize is True.'''		)

         # PIL RGBA images are converted to RGB
         if do_convert_rgb:
           A_      :				List[str]		     =					[convert_to_rgb(_SCREAMING_SNAKE_CASE		) for image in images]

         # All transformations expect numpy arrays.
         A_      :				int		     =					[to_numpy_array(_SCREAMING_SNAKE_CASE		) for image in images]

         if do_resize:
           A_      :				Tuple		     =					[self.resize(image=_SCREAMING_SNAKE_CASE				,       size=_SCREAMING_SNAKE_CASE				,       resample=_SCREAMING_SNAKE_CASE		) for image in images]

         if do_center_crop:
           A_      :				Union[str, Any]		     =					[self.center_crop(image=_SCREAMING_SNAKE_CASE				,       size=_SCREAMING_SNAKE_CASE		) for image in images]

         if do_rescale:
           A_      :				Tuple		     =					[self.rescale(image=_SCREAMING_SNAKE_CASE				,       scale=_SCREAMING_SNAKE_CASE		) for image in images]

         if do_normalize:
           A_      :				List[Any]		     =					[self.normalize(image=_SCREAMING_SNAKE_CASE				,       mean=_SCREAMING_SNAKE_CASE				,       std=_SCREAMING_SNAKE_CASE		) for image in images]

         A_      :				str		     =					[to_channel_dimension_format(_SCREAMING_SNAKE_CASE				,       _SCREAMING_SNAKE_CASE		) for image in images]

         A_      :				Optional[Any]		     =					{'''pixel_values''': images}
         return BatchFeature(data=_SCREAMING_SNAKE_CASE				,       tensor_type=_SCREAMING_SNAKE_CASE		)




