


import argparse
import glob
import importlib.util
import os
import re

import black
from doc_builder.style_doc import style_docstrings_in_code


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case							: Union[str, Any]      =   '''src/diffusers'''
snake_case							: int      =   '''.'''


# This is to make sure the diffusers module imported is the one in the repo.
snake_case							: int      =   importlib.util.spec_from_file_location(
    '''diffusers''',
    os.path.join(DIFFUSERS_PATH, '''__init__.py'''),
    submodule_search_locations=[DIFFUSERS_PATH],
)
snake_case							: Union[str, Any]      =   spec.loader.load_module()






def 							__lowercase     (				__lowerCAmelCase							:       List[str]      ,					__lowerCAmelCase							:       int     ):
							return line.startswith(__lowerCAmelCase     ) or len(__lowerCAmelCase     ) <= 1 or re.search(R'^\s*\)(\s*->.*:|:)\s*$'      ,					__lowerCAmelCase     ) is not None






def 							__lowercase     (				__lowerCAmelCase							:       Any     ):
							a__    =  object_name.split('.'     )
							a__    =  0

							# First let's find the module where our object lives.
							a__    =  parts[i]
							while i < len(__lowerCAmelCase     ) and not os.path.isfile(os.path.join(__lowerCAmelCase      ,					F'{module}.py'     )     ):
														i += 1
														if i < len(__lowerCAmelCase     ):
																					a__    =  os.path.join(__lowerCAmelCase      ,					parts[i]     )
							if i >= len(__lowerCAmelCase     ):
														raise ValueError(F'`object_name` should begin with the name of a module of diffusers but got {object_name}.'     )

							with open(os.path.join(__lowerCAmelCase      ,					F'{module}.py'     )      ,					'r'      ,					encoding='utf-8'      ,					newline='\n'     ) as f:
														a__    =  f.readlines()

							# Now let's find the class / func in the code!
							a__    =  ''
							a__    =  0
							for name in parts[i + 1 :]:
														while (
														    line_index < len(__lowerCAmelCase     ) and re.search(RF'^{indent}(class|def)\s+{name}(\(|\:)'      ,					lines[line_index]     ) is None
														):
																					line_index += 1
														indent += "    "
														line_index += 1

							if line_index >= len(__lowerCAmelCase     ):
														raise ValueError(F' {object_name} does not match any function or class in {module}.'     )

							# We found the beginning of the class / func, now let's find the end (when the indent diminishes).
							a__    =  line_index
							while line_index < len(__lowerCAmelCase     ) and _should_continue(lines[line_index]      ,					__lowerCAmelCase     ):
														line_index += 1
							# Clean up empty lines at the end (if any).
							while len(lines[line_index - 1]     ) <= 1:
														line_index -= 1

							a__    =  lines[start_index:line_index]
							return "".join(__lowerCAmelCase     )


snake_case							: List[Any]      =   re.compile(r'''^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)''')
snake_case							: Tuple      =   re.compile(r'''^\s*(\S+)->(\S+)(\s+.*|$)''')
snake_case							: str      =   re.compile(r'''<FILL\s+[^>]*>''')






def 							__lowercase     (				__lowerCAmelCase							:       Union[str, Any]     ):
							a__    =  code.split('\n'     )
							a__    =  0
							while idx < len(__lowerCAmelCase     ) and len(lines[idx]     ) == 0:
														idx += 1
							if idx < len(__lowerCAmelCase     ):
														return re.search(R'^(\s*)\S'      ,					lines[idx]     ).groups()[0]
							return ""






def 							__lowercase     (				__lowerCAmelCase							:       Any     ):
							a__    =  len(get_indent(__lowerCAmelCase     )     ) > 0
							if has_indent:
														a__    =  F'class Bla:\n{code}'
							a__    =  black.Mode(target_versions={black.TargetVersion.PYaa}      ,					line_length=1_1_9      ,					preview=__lowerCAmelCase     )
							a__    =  black.format_str(__lowerCAmelCase      ,					mode=__lowerCAmelCase     )
							a__   ,      a__    =  style_docstrings_in_code(__lowerCAmelCase     )
							return result[len('class Bla:\n'     ) :] if has_indent else result






def 							__lowercase     (				__lowerCAmelCase							:       Optional[int]      ,					__lowerCAmelCase							:       Dict=False     ):
							with open(__lowerCAmelCase      ,					'r'      ,					encoding='utf-8'      ,					newline='\n'     ) as f:
														a__    =  f.readlines()
							a__    =  []
							a__    =  0
							# Not a for loop cause `lines` is going to change (if `overwrite=True`).
							while line_index < len(__lowerCAmelCase     ):
														a__    =  _re_copy_warning.search(lines[line_index]     )
														if search is None:
																					line_index += 1
																					continue

														# There is some copied code here, let's retrieve the original.
														a__   ,      a__   ,      a__    =  search.groups()
														a__    =  find_code_in_diffusers(__lowerCAmelCase     )
														a__    =  get_indent(__lowerCAmelCase     )

														a__    =  line_index + 1 if indent == theoretical_indent else line_index + 2
														a__    =  theoretical_indent
														a__    =  start_index

														# Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
														a__    =  True
														while line_index < len(__lowerCAmelCase     ) and should_continue:
																					line_index += 1
																					if line_index >= len(__lowerCAmelCase     ):
																												break
																					a__    =  lines[line_index]
																					a__    =  _should_continue(__lowerCAmelCase      ,					__lowerCAmelCase     ) and re.search(F'^{indent}# End copy'      ,					__lowerCAmelCase     ) is None
														# Clean up empty lines at the end (if any).
														while len(lines[line_index - 1]     ) <= 1:
																					line_index -= 1

														a__    =  lines[start_index:line_index]
														a__    =  ''.join(__lowerCAmelCase     )

														# Remove any nested `Copied from` comments to avoid circular copies
														a__    =  [line for line in theoretical_code.split('\n'     ) if _re_copy_warning.search(__lowerCAmelCase     ) is None]
														a__    =  '\n'.join(__lowerCAmelCase     )

														# Before comparing, use the `replace_pattern` on the original code.
														if len(__lowerCAmelCase     ) > 0:
																					a__    =  replace_pattern.replace('with'      ,					''     ).split(','     )
																					a__    =  [_re_replace_pattern.search(__lowerCAmelCase     ) for p in patterns]
																					for pattern in patterns:
																												if pattern is None:
																																			continue
																												a__   ,      a__   ,      a__    =  pattern.groups()
																												a__    =  re.sub(__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase     )
																												if option.strip() == "all-casing":
																																			a__    =  re.sub(obja.lower()      ,					obja.lower()      ,					__lowerCAmelCase     )
																																			a__    =  re.sub(obja.upper()      ,					obja.upper()      ,					__lowerCAmelCase     )

            # Blackify after replacement. To be able to do that, we need the header (class or function definition)
            # from the previous line
																					a__    =  blackify(lines[start_index - 1] + theoretical_code     )
																					a__    =  theoretical_code[len(lines[start_index - 1]     ) :]

														# Test for a diff and act accordingly.
														if observed_code != theoretical_code:
																					diffs.append([object_name, start_index]     )
																					if overwrite:
																												a__    =  lines[:start_index] + [theoretical_code] + lines[line_index:]
																												a__    =  start_index + 1

							if overwrite and len(__lowerCAmelCase     ) > 0:
														# Warn the user a file has been modified.
														print(F'Detected changes, rewriting {filename}.'     )
														with open(__lowerCAmelCase      ,					'w'      ,					encoding='utf-8'      ,					newline='\n'     ) as f:
																					f.writelines(__lowerCAmelCase     )
							return diffs






def 							__lowercase     (				__lowerCAmelCase							:       bool = False     ):
							a__    =  glob.glob(os.path.join(__lowerCAmelCase      ,					'**/*.py'     )      ,					recursive=__lowerCAmelCase     )
							a__    =  []
							for filename in all_files:
														a__    =  is_copy_consistent(__lowerCAmelCase      ,					__lowerCAmelCase     )
														diffs += [F'- {filename}: copy does not match {d[0]} at line {d[1]}' for d in new_diffs]
							if not overwrite and len(__lowerCAmelCase     ) > 0:
														a__    =  '\n'.join(__lowerCAmelCase     )
														raise Exception(
														    'Found the following copy inconsistencies:\n'
														    + diff
														    + '\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them.'     )


if __name__ == "__main__":
						snake_case							: Optional[Any]      =   argparse.ArgumentParser()
						parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
						snake_case							: str      =   parser.parse_args()

						check_copies(args.fix_and_overwrite)








from typing import List, Optional, Union

import numpy as np
import PIL.Image

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
    ChannelDimension,
    PILImageResampling,
    get_image_size,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


snake_case							: Dict      =   logging.get_logger(__name__)







class  snake_case_     (lowerCamelCase_   ):
					UpperCAmelCase__      :					Dict					   =    ['''pixel_values''']
					def __init__(   self     :Optional[Any]    ,__snake_case     :bool = True    ,__snake_case     :int = 32    ,__snake_case     :Union[str, Any]=PILImageResampling.BILINEAR    ,__snake_case     :bool = True    ,**__snake_case     :Tuple    ,)      ->					None:
												a__    =  do_resize
												a__    =  do_rescale
												a__    =  size_divisor
												a__    =  resample
												super().__init__(**__snake_case   )
					def 				lowerCamelCase__(   self     :Union[str, Any]    ,__snake_case     :np.ndarray    ,__snake_case     :int    ,__snake_case     :Tuple    ,__snake_case     :Optional[ChannelDimension] = None    ,**__snake_case     :List[Any]   )      ->					np.ndarray:
												a__   ,      a__    =  get_image_size(__snake_case   )
												# Rounds the height and width down to the closest multiple of size_divisor
												a__    =  height // size_divisor * size_divisor
												a__    =  width // size_divisor * size_divisor
												a__    =  resize(__snake_case    ,(new_h, new_w)    ,resample=__snake_case    ,data_format=__snake_case    ,**__snake_case   )
												return image
					def 				lowerCamelCase__(   self     :List[str]    ,__snake_case     :np.ndarray    ,__snake_case     :float    ,__snake_case     :Optional[ChannelDimension] = None    ,**__snake_case     :str   )      ->					np.ndarray:
												return rescale(image=__snake_case    ,scale=__snake_case    ,data_format=__snake_case    ,**__snake_case   )



					def 				lowerCamelCase__(   self     :Tuple    ,__snake_case     :Union["PIL.Image.Image", TensorType, List["PIL.Image.Image"], List[TensorType]]    ,__snake_case     :Optional[bool] = None    ,__snake_case     :Optional[int] = None    ,__snake_case     :Union[str, Any]=None    ,__snake_case     :Optional[bool] = None    ,__snake_case     :Optional[Union[TensorType, str]] = None    ,__snake_case     :ChannelDimension = ChannelDimension.FIRST    ,**__snake_case     :List[Any]    ,)      ->					BatchFeature:
												a__    =  do_resize if do_resize is not None else self.do_resize
												a__    =  do_rescale if do_rescale is not None else self.do_rescale
												a__    =  size_divisor if size_divisor is not None else self.size_divisor
												a__    =  resample if resample is not None else self.resample

												if do_resize and size_divisor is None:
																			raise ValueError('size_divisor is required for resizing'   )

												a__    =  make_list_of_images(__snake_case   )

												if not valid_images(__snake_case   ):
																			raise ValueError('Invalid image(s)'   )

												# All transformations expect numpy arrays.
												a__    =  [to_numpy_array(__snake_case   ) for img in images]

												if do_resize:
																			a__    =  [self.resize(__snake_case    ,size_divisor=__snake_case    ,resample=__snake_case   ) for image in images]

												if do_rescale:
																			a__    =  [self.rescale(__snake_case    ,scale=1 / 2_55   ) for image in images]

												a__    =  [to_channel_dimension_format(__snake_case    ,__snake_case   ) for image in images]

												a__    =  {'pixel_values': images}
												return BatchFeature(data=__snake_case    ,tensor_type=__snake_case   )




