import argparse
import os
import re


_lowerCamelCase					:   List[str]							=		'''src/diffusers'''

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





def 	__lowerCamelCase							(UpperCAmelCase__     :							Tuple  ):
					SCREAMING_SNAKE_CASE    			=       _re_indent.search(UpperCAmelCase__  )
					return "" if search is None else search.groups()[0]





def 	__lowerCamelCase							(UpperCAmelCase__     :							List[str]      , UpperCAmelCase__     :							List[Any]=""      , UpperCAmelCase__     :							Tuple=None      , UpperCAmelCase__     :							int=None  ):
					SCREAMING_SNAKE_CASE    			=       0
					SCREAMING_SNAKE_CASE    			=       code.split("\n"  )
					if start_prompt is not None:
										while not lines[index].startswith(UpperCAmelCase__  ):
															index += 1
										SCREAMING_SNAKE_CASE    			=       ["\n".join(lines[:index]  )]
					else:
										SCREAMING_SNAKE_CASE    			=       []

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

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

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

					return blocks





def 	__lowerCamelCase							(UpperCAmelCase__     :							Tuple  ):

					def _inner(UpperCAmelCase__     :							Union[str, Any]  ):
										return key(UpperCAmelCase__  ).lower().replace("_"      , ""  )

					return _inner





def 	__lowerCamelCase							(UpperCAmelCase__     :							Tuple      , UpperCAmelCase__     :							List[str]=None  ):

					# If no key is provided, we use a noop.
					def noop(UpperCAmelCase__     :							List[str]  ):
										return x

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

					SCREAMING_SNAKE_CASE    			=       ignore_underscore(UpperCAmelCase__  )
					return sorted(UpperCAmelCase__      , key=UpperCAmelCase__  ) + sorted(UpperCAmelCase__      , key=UpperCAmelCase__  ) + sorted(UpperCAmelCase__      , key=UpperCAmelCase__  )





def 	__lowerCamelCase							(UpperCAmelCase__     :							int  ):

					# This inner function sort imports between [ ].
					def _replace(UpperCAmelCase__     :							Union[str, Any]  ):
										SCREAMING_SNAKE_CASE    			=       match.groups()[0]
										if "," not in imports:
															return F"[{imports}]"
										SCREAMING_SNAKE_CASE    			=       [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:
															SCREAMING_SNAKE_CASE    			=       keys[:-1]
										return "[" + ", ".join([F"\"{k}\"" for k in sort_objects(UpperCAmelCase__  )]  ) + "]"

					SCREAMING_SNAKE_CASE    			=       import_statement.split("\n"  )
					if len(UpperCAmelCase__  ) > 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.
										SCREAMING_SNAKE_CASE    			=       2 if lines[1].strip() == "[" else 1
										SCREAMING_SNAKE_CASE    			=       [(i, _re_strip_line.search(UpperCAmelCase__  ).groups()[0]) for i, line in enumerate(lines[idx:-idx]  )]
										SCREAMING_SNAKE_CASE    			=       sort_objects(UpperCAmelCase__      , key=lambda UpperCAmelCase__  : x[1]  )
										SCREAMING_SNAKE_CASE    			=       [lines[x[0] + idx] for x in sorted_indices]
										return "\n".join(lines[:idx] + sorted_lines + lines[-idx:]  )
					elif len(UpperCAmelCase__  ) == 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:
															SCREAMING_SNAKE_CASE    			=       _re_bracket_content.sub(_replace      , lines[1]  )
										else:
															SCREAMING_SNAKE_CASE    			=       [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:
																				SCREAMING_SNAKE_CASE    			=       keys[:-1]
															SCREAMING_SNAKE_CASE    			=       get_indent(lines[1]  ) + ", ".join([F"\"{k}\"" for k in sort_objects(UpperCAmelCase__  )]  )
										return "\n".join(UpperCAmelCase__  )
					else:
										# Finally we have to deal with imports fitting on one line
										SCREAMING_SNAKE_CASE    			=       _re_bracket_content.sub(_replace      , UpperCAmelCase__  )
										return import_statement





def 	__lowerCamelCase							(UpperCAmelCase__     :							List[Any]      , UpperCAmelCase__     :							int=True  ):
					with open(UpperCAmelCase__      , "r"  ) as f:
										SCREAMING_SNAKE_CASE    			=       f.read()

					if "_import_structure" not in code:
										return

					# Blocks of indent level 0
					SCREAMING_SNAKE_CASE    			=       split_code_in_indented_blocks(
					    UpperCAmelCase__      , start_prompt="_import_structure = {"      , end_prompt="if TYPE_CHECKING:"  )

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

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

										# Ignore beginning and last line: they don't contain anything.
										SCREAMING_SNAKE_CASE    			=       "\n".join(block_lines[line_idx:-1]  )
										SCREAMING_SNAKE_CASE    			=       get_indent(block_lines[1]  )
										# Slit the internal block into blocks of indent level 1.
										SCREAMING_SNAKE_CASE    			=       split_code_in_indented_blocks(UpperCAmelCase__      , indent_level=UpperCAmelCase__  )
										# We have two categories of import key: list or _import_structure[key].append/extend
										SCREAMING_SNAKE_CASE    			=       _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.
										SCREAMING_SNAKE_CASE    			=       [(pattern.search(UpperCAmelCase__  ).groups()[0] if pattern.search(UpperCAmelCase__  ) is not None else None) for b in internal_blocks]
										# We only sort the lines with a key.
										SCREAMING_SNAKE_CASE    			=       [(i, key) for i, key in enumerate(UpperCAmelCase__  ) if key is not None]
										SCREAMING_SNAKE_CASE    			=       [x[0] for x in sorted(UpperCAmelCase__      , key=lambda UpperCAmelCase__  : x[1]  )]

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

        # And we put our main block back together with its first and last line.
										SCREAMING_SNAKE_CASE    			=       "\n".join(block_lines[:line_idx] + reordered_blocks + [block_lines[-1]]  )

					if code != "\n".join(UpperCAmelCase__  ):
										if check_only:
															return True
										else:
															print(F"Overwriting {file}."  )
															with open(UpperCAmelCase__      , "w"  ) as f:
																				f.write("\n".join(UpperCAmelCase__  )  )





def 	__lowerCamelCase							(UpperCAmelCase__     :							Dict=True  ):
					SCREAMING_SNAKE_CASE    			=       []
					for root, _, files in os.walk(UpperCAmelCase__  ):
										if "__init__.py" in files:
															SCREAMING_SNAKE_CASE    			=       sort_imports(os.path.join(UpperCAmelCase__      , "__init__.py"  )      , check_only=UpperCAmelCase__  )
															if result:
																				SCREAMING_SNAKE_CASE    			=       [os.path.join(UpperCAmelCase__      , "__init__.py"  )]
					if len(UpperCAmelCase__  ) > 0:
										raise ValueError(F"Would overwrite {len(UpperCAmelCase__  )} files, run `make style`."  )


if __name__ == "__main__":
							_lowerCamelCase					:   List[Any]							=		argparse.ArgumentParser()
							parser.add_argument('''--check_only''', action='''store_true''', help='''Whether to only check or fix style.''')
							_lowerCamelCase					:   Tuple							=		parser.parse_args()

							sort_imports_in_all_inits(check_only=args.check_only)





from typing import Dict, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_pytesseract_available, is_vision_available, logging, requires_backends


if is_vision_available():
							import PIL

# soft dependency
if is_pytesseract_available():
							import pytesseract

_lowerCamelCase					:   Union[str, Any]							=		logging.get_logger(__name__)





def 	__lowerCamelCase							(UpperCAmelCase__     :							List[Any]      , UpperCAmelCase__     :							List[Any]      , UpperCAmelCase__     :							Optional[Any]  ):
					return [
					    int(1_0_0_0 * (box[0] / width)  ),
					    int(1_0_0_0 * (box[1] / height)  ),
					    int(1_0_0_0 * (box[2] / width)  ),
					    int(1_0_0_0 * (box[3] / height)  ),
					]





def 	__lowerCamelCase							(UpperCAmelCase__     :							np.ndarray      , UpperCAmelCase__     :							Optional[str]      , UpperCAmelCase__     :							Optional[str] = None  ):
					SCREAMING_SNAKE_CASE    			=       tesseract_config if tesseract_config is not None else ""

					# apply OCR
					SCREAMING_SNAKE_CASE    			=       to_pil_image(UpperCAmelCase__  )
					SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       pil_image.size
					SCREAMING_SNAKE_CASE    			=       pytesseract.image_to_data(UpperCAmelCase__      , lang=UpperCAmelCase__      , output_type="dict"      , config=UpperCAmelCase__  )
					SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       data["text"], data["left"], data["top"], data["width"], data["height"]

					# filter empty words and corresponding coordinates
					SCREAMING_SNAKE_CASE    			=       [idx for idx, word in enumerate(UpperCAmelCase__  ) if not word.strip()]
					SCREAMING_SNAKE_CASE    			=       [word for idx, word in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]
					SCREAMING_SNAKE_CASE    			=       [coord for idx, coord in enumerate(UpperCAmelCase__  ) if idx not in irrelevant_indices]

					# turn coordinates into (left, top, left+width, top+height) format
					SCREAMING_SNAKE_CASE    			=       []
					for x, y, w, h in zip(UpperCAmelCase__      , UpperCAmelCase__      , UpperCAmelCase__      , UpperCAmelCase__  ):
										SCREAMING_SNAKE_CASE    			=       [x, y, x + w, y + h]
										actual_boxes.append(UpperCAmelCase__  )

					# finally, normalize the bounding boxes
					SCREAMING_SNAKE_CASE    			=       []
					for box in actual_boxes:
										normalized_boxes.append(normalize_box(UpperCAmelCase__      , UpperCAmelCase__      , UpperCAmelCase__  )  )

					assert len(UpperCAmelCase__  ) == len(UpperCAmelCase__  ), "Not as many words as there are bounding boxes"

					return words, normalized_boxes


class 						lowercase    (     a     ):
							lowercase__						:       Optional[int]								=							["""pixel_values"""]




							def __init__(						self   :					int	,							_UpperCamelCase   :					bool = True	,							_UpperCamelCase   :					Dict[str, int] = None	,							_UpperCamelCase   :					PILImageResampling = PILImageResampling.BILINEAR	,							_UpperCamelCase   :					bool = True	,							_UpperCamelCase   :					Optional[str] = None	,							_UpperCamelCase   :					Optional[str] = ""	,							**_UpperCamelCase   :					Optional[int]	,							)					->				None:



												'''simple docstring'''

												super().__init__(**_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       size if size is not None else {"height": 224, "width": 224}
												SCREAMING_SNAKE_CASE    			=       get_size_dict(_UpperCamelCase      )

												SCREAMING_SNAKE_CASE    			=       do_resize
												SCREAMING_SNAKE_CASE    			=       size
												SCREAMING_SNAKE_CASE    			=       resample
												SCREAMING_SNAKE_CASE    			=       apply_ocr
												SCREAMING_SNAKE_CASE    			=       ocr_lang
												SCREAMING_SNAKE_CASE    			=       tesseract_config




							def 	__snake_case(						self   :					List[Any]	,							_UpperCamelCase   :					np.ndarray	,							_UpperCamelCase   :					Dict[str, int]	,							_UpperCamelCase   :					PILImageResampling = PILImageResampling.BILINEAR	,							_UpperCamelCase   :					Optional[Union[str, ChannelDimension]] = None	,							**_UpperCamelCase   :					Any	,							)					->				np.ndarray:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       get_size_dict(_UpperCamelCase      )
												if "height" not in size or "width" not in size:
																	raise ValueError(F"The size dictionary must contain the keys 'height' and 'width'. Got {size.keys()}"      )
												SCREAMING_SNAKE_CASE    			=       (size["height"], size["width"])
												return resize(_UpperCamelCase	,							size=_UpperCamelCase	,							resample=_UpperCamelCase	,							data_format=_UpperCamelCase	,							**_UpperCamelCase      )





							def 	__snake_case(						self   :					Tuple	,							_UpperCamelCase   :					ImageInput	,							_UpperCamelCase   :					bool = None	,							_UpperCamelCase   :					Dict[str, int] = None	,							_UpperCamelCase   :					PILImageResampling = None	,							_UpperCamelCase   :					bool = None	,							_UpperCamelCase   :					Optional[str] = None	,							_UpperCamelCase   :					Optional[str] = None	,							_UpperCamelCase   :					Optional[Union[str, TensorType]] = None	,							_UpperCamelCase   :					ChannelDimension = ChannelDimension.FIRST	,							**_UpperCamelCase   :					str	,							)					->				PIL.Image.Image:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE    			=       do_resize if do_resize is not None else self.do_resize
												SCREAMING_SNAKE_CASE    			=       size if size is not None else self.size
												SCREAMING_SNAKE_CASE    			=       get_size_dict(_UpperCamelCase      )
												SCREAMING_SNAKE_CASE    			=       resample if resample is not None else self.resample
												SCREAMING_SNAKE_CASE    			=       apply_ocr if apply_ocr is not None else self.apply_ocr
												SCREAMING_SNAKE_CASE    			=       ocr_lang if ocr_lang is not None else self.ocr_lang
												SCREAMING_SNAKE_CASE    			=       tesseract_config if tesseract_config is not None else self.tesseract_config

												SCREAMING_SNAKE_CASE    			=       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_resize and size is None:
																	raise ValueError("Size must be specified if do_resize is True."      )

												# All transformations expect numpy arrays.
												SCREAMING_SNAKE_CASE    			=       [to_numpy_array(_UpperCamelCase      ) for image in images]

												if apply_ocr:
																	requires_backends(self	,							"pytesseract"      )
																	SCREAMING_SNAKE_CASE    			=       []
																	SCREAMING_SNAKE_CASE    			=       []
																	for image in images:
																						SCREAMING_SNAKE_CASE			,   SCREAMING_SNAKE_CASE    			=       apply_tesseract(_UpperCamelCase	,							_UpperCamelCase	,							_UpperCamelCase      )
																						words_batch.append(_UpperCamelCase      )
																						boxes_batch.append(_UpperCamelCase      )

												if do_resize:
																	SCREAMING_SNAKE_CASE    			=       [self.resize(image=_UpperCamelCase	,							size=_UpperCamelCase	,							resample=_UpperCamelCase      ) for image in images]

												# flip color channels from RGB to BGR (as Detectron2 requires this)
												SCREAMING_SNAKE_CASE    			=       [flip_channel_order(_UpperCamelCase      ) for image in images]
												SCREAMING_SNAKE_CASE    			=       [to_channel_dimension_format(_UpperCamelCase	,							_UpperCamelCase      ) for image in images]

												SCREAMING_SNAKE_CASE    			=       BatchFeature(data={"pixel_values": images}	,							tensor_type=_UpperCamelCase      )

												if apply_ocr:
																	SCREAMING_SNAKE_CASE    			=       words_batch
																	SCREAMING_SNAKE_CASE    			=       boxes_batch
												return data




