



import importlib
import inspect
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_lowercase     							=						"src/transformers"


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

_lowercase     							=						transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
_lowercase     							=						re.compile('''\[(.+?)\]\((https://huggingface\.co/.+?)\)''')


_lowercase     							=						{
    "CLIPConfigMixin",
    "DecisionTransformerConfigMixin",
    "EncoderDecoderConfigMixin",
    "RagConfigMixin",
    "SpeechEncoderDecoderConfigMixin",
    "VisionEncoderDecoderConfigMixin",
    "VisionTextDualEncoderConfigMixin",
}






def      _A				()  ->Optional[Any]:



			'''simple docstring'''







			lowerCamelCase__ :      List[str]								=		[]

			for config_class in list(CONFIG_MAPPING.values() ):
						lowerCamelCase__ :      Any								=		False

						# source code of `config_class`
						lowerCamelCase__ :      List[str]								=		inspect.getsource(__snake_case )
						lowerCamelCase__ :      Any								=		_re_checkpoint.findall(__snake_case )

						for checkpoint in checkpoints:
									# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
									# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
									lowerCamelCase__ :      Optional[Any]								=		checkpoint

									# verify the checkpoint name corresponds to the checkpoint link
									lowerCamelCase__ :      Dict								=		f"https://huggingface.co/{ckpt_name}"
									if ckpt_link == ckpt_link_from_name:
												lowerCamelCase__ :      Dict								=		True
												break

						lowerCamelCase__ :      Any								=		config_class.__name__
						if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
									configs_without_checkpoint.append(__snake_case )

			if len(__snake_case ) > 0:
						lowerCamelCase__ :      int								=		"\n".join(sorted(__snake_case ) )
						raise ValueError(f"The following configurations don\'t contain any valid checkpoint:\n{message}" )


if __name__ == "__main__":
				check_config_docstrings_have_checkpoints()




from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt






def      _A				(UpperCamelCase		:      np.ndarray      ,			UpperCamelCase		:      np.ndarray      ,			UpperCamelCase		:      np.ndarray      ,			UpperCamelCase		:      int      ,			UpperCamelCase		:      int )  ->np.ndarray:



			'''simple docstring'''







			lowerCamelCase__ :      Union[str, Any]								=		cva.getAffineTransform(UpperCamelCase      ,			UpperCamelCase )
			return cva.warpAffine(UpperCamelCase      ,			UpperCamelCase      ,			(rows, cols) )


if __name__ == "__main__":
				# read original image
				_lowercase     							=						cva.imread(
				    str(Path(__file__).resolve().parent.parent / '''image_data''' / '''lena.jpg''')
				)
				# turn image in gray scale value
				_lowercase     							=						cva.cvtColor(image, cva.COLOR_BGR2GRAY)
				# get image shape
				_lowercase							,				_lowercase     							=						gray_img.shape

				# set different points to rotate image
				_lowercase     							=						np.array([[50, 50], [2_00, 50], [50, 2_00]], np.floataa)
				_lowercase     							=						np.array([[10, 1_00], [2_00, 50], [1_00, 2_50]], np.floataa)
				_lowercase     							=						np.array([[50, 50], [1_50, 50], [1_20, 2_00]], np.floataa)
				_lowercase     							=						np.array([[10, 1_00], [80, 50], [1_80, 2_50]], np.floataa)

				# add all rotated images in a list
				_lowercase     							=						[
				    gray_img,
				    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
				    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
				    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
				]

				# plot different image rotations
				_lowercase     							=						plt.figure(1)
				_lowercase     							=						['''Original''', '''Rotation 1''', '''Rotation 2''', '''Rotation 3''']
				for i, image in enumerate(images):
								plt.subplot(2, 2, i + 1), plt.imshow(image, '''gray''')
								plt.title(titles[i])
								plt.axis('''off''')
								plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
				plt.show()



