
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
lowercase        =  '''src/diffusers'''
lowercase        =  '''.'''


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



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



def      __lowerCAmelCase						(							UpperCAmelCase__				:      int       )  ->    List[str]:
							lowerCamelCase_							  =					object_name.split("""."""       )
							lowerCamelCase_							  =					0

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

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

							# Now let's find the class / func in the code!
							lowerCamelCase_							  =					""""""
							lowerCamelCase_							  =					0
							for name in parts[i + 1 :]:
														while (
														    line_index < len(UpperCAmelCase__       ) 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(UpperCAmelCase__       ):
														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).
							lowerCamelCase_							  =					line_index
							while line_index < len(UpperCAmelCase__       ) and _should_continue(lines[line_index]			,				UpperCAmelCase__       ):
														line_index += 1
							# Clean up empty lines at the end (if any).
							while len(lines[line_index - 1]       ) <= 1:
														line_index -= 1

							lowerCamelCase_							  =					lines[start_index:line_index]
							return "".join(UpperCAmelCase__       )


lowercase        =  re.compile(r'''^(\s*)#\s*Copied from\s+diffusers\.(\S+\.\S+)\s*($|\S.*$)''')
lowercase        =  re.compile(r'''^\s*(\S+)->(\S+)(\s+.*|$)''')
lowercase        =  re.compile(r'''<FILL\s+[^>]*>''')



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Tuple       )  ->    Any:
							lowerCamelCase_							  =					code.split("""\n"""       )
							lowerCamelCase_							  =					0
							while idx < len(UpperCAmelCase__       ) and len(lines[idx]       ) == 0:
														idx += 1
							if idx < len(UpperCAmelCase__       ):
														return re.search(R"""^(\s*)\S"""			,				lines[idx]       ).groups()[0]
							return ""



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



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Tuple			,				UpperCAmelCase__				:      List[str]=False       )  ->    str:
							with open(UpperCAmelCase__			,				"""r"""			,				encoding="""utf-8"""			,				newline="""\n"""       ) as f:
														lowerCamelCase_							  =					f.readlines()
							lowerCamelCase_							  =					[]
							lowerCamelCase_							  =					0
							# Not a for loop cause `lines` is going to change (if `overwrite=True`).
							while line_index < len(UpperCAmelCase__       ):
														lowerCamelCase_							  =					_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.
														lowerCamelCase_  ,   lowerCamelCase_  ,   lowerCamelCase_							  =					search.groups()
														lowerCamelCase_							  =					find_code_in_diffusers(UpperCAmelCase__       )
														lowerCamelCase_							  =					get_indent(UpperCAmelCase__       )

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

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

														lowerCamelCase_							  =					lines[start_index:line_index]
														lowerCamelCase_							  =					"""""".join(UpperCAmelCase__       )

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

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

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

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



def      __lowerCAmelCase						(							UpperCAmelCase__				:      bool = False       )  ->    Any:
							lowerCamelCase_							  =					glob.glob(os.path.join(UpperCAmelCase__			,				"""**/*.py"""       )			,				recursive=UpperCAmelCase__       )
							lowerCamelCase_							  =					[]
							for filename in all_files:
														lowerCamelCase_							  =					is_copy_consistent(UpperCAmelCase__			,				UpperCAmelCase__       )
														diffs += [F'''- {filename}: copy does not match {d[0]} at line {d[1]}''' for d in new_diffs]
							if not overwrite and len(UpperCAmelCase__       ) > 0:
														lowerCamelCase_							  =					"""\n""".join(UpperCAmelCase__       )
														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__":
		lowercase        =  argparse.ArgumentParser()
		parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
		lowercase        =  parser.parse_args()

		check_copies(args.fix_and_overwrite)







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,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_vision_available():
		import PIL


lowercase        =  logging.get_logger(__name__)





class       __A(				UpperCAmelCase       ):
					SCREAMING_SNAKE_CASE			    =    ['''pixel_values''']

					def __init__(	self					:     Any   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Dict[str, int] = None   ,					__UpperCamelCase					:     float = None   ,					__UpperCamelCase					:     PILImageResampling = PILImageResampling.BILINEAR   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Union[int, float] = 1 / 2_5_5   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Optional[Union[float, List[float]]] = None   ,					__UpperCamelCase					:     Optional[Union[float, List[float]]] = None   ,					**__UpperCamelCase					:     Optional[int]   ,					):
												super().__init__(**__UpperCamelCase   )
												lowerCamelCase_							  =					size if size is not None else {"""shortest_edge""": 3_8_4}
												lowerCamelCase_							  =					get_size_dict(__UpperCamelCase   ,					default_to_square=__UpperCamelCase   )

												lowerCamelCase_							  =					do_resize
												lowerCamelCase_							  =					size
												# Default value set here for backwards compatibility where the value in config is None
												lowerCamelCase_							  =					crop_pct if crop_pct is not None else 2_2_4 / 2_5_6
												lowerCamelCase_							  =					resample
												lowerCamelCase_							  =					do_rescale
												lowerCamelCase_							  =					rescale_factor
												lowerCamelCase_							  =					do_normalize
												lowerCamelCase_							  =					image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
												lowerCamelCase_							  =					image_std if image_std is not None else IMAGENET_STANDARD_STD

					def    lowercase__      (	self					:     List[Any]   ,					__UpperCamelCase					:     np.ndarray   ,					__UpperCamelCase					:     Dict[str, int]   ,					__UpperCamelCase					:     float   ,					__UpperCamelCase					:     PILImageResampling = PILImageResampling.BICUBIC   ,					__UpperCamelCase					:     Optional[Union[str, ChannelDimension]] = None   ,					**__UpperCamelCase					:     Tuple   ,					):
												lowerCamelCase_							  =					get_size_dict(__UpperCamelCase   ,					default_to_square=__UpperCamelCase   )
												if "shortest_edge" not in size:
																			raise ValueError(F'''Size dictionary must contain \'shortest_edge\' key. Got {size.keys()}'''   )
												lowerCamelCase_							  =					size["""shortest_edge"""]

												if shortest_edge < 3_8_4:
																			# maintain same ratio, resizing shortest edge to shortest_edge/crop_pct
																			lowerCamelCase_							  =					int(shortest_edge / crop_pct   )
																			lowerCamelCase_							  =					get_resize_output_image_size(__UpperCamelCase   ,					size=__UpperCamelCase   ,					default_to_square=__UpperCamelCase   )
																			lowerCamelCase_							  =					resize(image=__UpperCamelCase   ,					size=__UpperCamelCase   ,					resample=__UpperCamelCase   ,					data_format=__UpperCamelCase   ,					**__UpperCamelCase   )
																			# then crop to (shortest_edge, shortest_edge)
																			return center_crop(image=__UpperCamelCase   ,					size=(shortest_edge, shortest_edge)   ,					data_format=__UpperCamelCase   ,					**__UpperCamelCase   )
												else:
																			# warping (no cropping) when evaluated at 384 or larger
																			return resize(
																			    __UpperCamelCase   ,					size=(shortest_edge, shortest_edge)   ,					resample=__UpperCamelCase   ,					data_format=__UpperCamelCase   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     str   ,					__UpperCamelCase					:     np.ndarray   ,					__UpperCamelCase					:     Union[int, float]   ,					__UpperCamelCase					:     Optional[Union[str, ChannelDimension]] = None   ,					**__UpperCamelCase					:     int   ,					):
												return rescale(__UpperCamelCase   ,					scale=__UpperCamelCase   ,					data_format=__UpperCamelCase   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     List[str]   ,					__UpperCamelCase					:     np.ndarray   ,					__UpperCamelCase					:     Union[float, List[float]]   ,					__UpperCamelCase					:     Union[float, List[float]]   ,					__UpperCamelCase					:     Optional[Union[str, ChannelDimension]] = None   ,					**__UpperCamelCase					:     List[str]   ,					):
												return normalize(__UpperCamelCase   ,					mean=__UpperCamelCase   ,					std=__UpperCamelCase   ,					data_format=__UpperCamelCase   ,					**__UpperCamelCase   )



					def    lowercase__      (	self					:     List[str]   ,					__UpperCamelCase					:     ImageInput   ,					__UpperCamelCase					:     bool = None   ,					__UpperCamelCase					:     Dict[str, int] = None   ,					__UpperCamelCase					:     float = None   ,					__UpperCamelCase					:     PILImageResampling = None   ,					__UpperCamelCase					:     bool = None   ,					__UpperCamelCase					:     float = None   ,					__UpperCamelCase					:     bool = None   ,					__UpperCamelCase					:     Optional[Union[float, List[float]]] = None   ,					__UpperCamelCase					:     Optional[Union[float, List[float]]] = None   ,					__UpperCamelCase					:     Optional[Union[str, TensorType]] = None   ,					__UpperCamelCase					:     ChannelDimension = ChannelDimension.FIRST   ,					**__UpperCamelCase					:     List[str]   ,					):
												lowerCamelCase_							  =					do_resize if do_resize is not None else self.do_resize
												lowerCamelCase_							  =					crop_pct if crop_pct is not None else self.crop_pct
												lowerCamelCase_							  =					resample if resample is not None else self.resample
												lowerCamelCase_							  =					do_rescale if do_rescale is not None else self.do_rescale
												lowerCamelCase_							  =					rescale_factor if rescale_factor is not None else self.rescale_factor
												lowerCamelCase_							  =					do_normalize if do_normalize is not None else self.do_normalize
												lowerCamelCase_							  =					image_mean if image_mean is not None else self.image_mean
												lowerCamelCase_							  =					image_std if image_std is not None else self.image_std

												lowerCamelCase_							  =					size if size is not None else self.size
												lowerCamelCase_							  =					get_size_dict(__UpperCamelCase   ,					default_to_square=__UpperCamelCase   )

												lowerCamelCase_							  =					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 or resample is None:
																			raise ValueError("""Size and resample must be specified if do_resize is True."""   )

												if do_resize and size["shortest_edge"] < 3_8_4 and crop_pct is None:
																			raise ValueError("""crop_pct must be specified if size < 384."""   )

												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."""   )

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

												if do_resize:
																			lowerCamelCase_							  =					[self.resize(image=__UpperCamelCase   ,					size=__UpperCamelCase   ,					crop_pct=__UpperCamelCase   ,					resample=__UpperCamelCase   ) for image in images]

												if do_rescale:
																			lowerCamelCase_							  =					[self.rescale(image=__UpperCamelCase   ,					scale=__UpperCamelCase   ) for image in images]

												if do_normalize:
																			lowerCamelCase_							  =					[self.normalize(image=__UpperCamelCase   ,					mean=__UpperCamelCase   ,					std=__UpperCamelCase   ) for image in images]

												lowerCamelCase_							  =					[to_channel_dimension_format(__UpperCamelCase   ,					__UpperCamelCase   ) for image in images]

												lowerCamelCase_							  =					{"""pixel_values""": images}
												return BatchFeature(data=__UpperCamelCase   ,					tensor_type=__UpperCamelCase   )





