

"""simple docstring"""




import argparse
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_dummies.py
_a:      Optional[Any]								=     """src/transformers"""

# Matches is_xxx_available()
_a:      Tuple								=     re.compile(r"""is\_([a-z_]*)_available()""")
# Matches from xxx import bla
_a:      Dict								=     re.compile(r"""\s+from\s+\S*\s+import\s+([^\(\s].*)\n""")
_a:      str								=     re.compile(r"""^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)""")


_a:      List[str]								=     """
{0} = None
"""

_a:      Tuple								=     """
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
"""


_a:      Optional[int]								=     """
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""



def  __lowerCAmelCase (  A      ):
	if _re_test_backend.search(A      ) is None:
		return None
	UpperCAmelCase_    			=     [b[0] for b in _re_backend.findall(A      )]
	backends.sort()
	return "_and_".join(A      )



def  __lowerCAmelCase (  ):
	with open(os.path.join(A    ,       "__init__.py"      )    ,       "r"    ,       encoding="utf-8"    ,       newline="\n"      ) as f:
		UpperCAmelCase_    			=     f.readlines()

	# Get to the point we do the actual imports for type checking
	UpperCAmelCase_    			=     0
	while not lines[line_index].startswith("if TYPE_CHECKING"      ):
		line_index += 1

	UpperCAmelCase_    			=     {}
	# Go through the end of the file
	while line_index < len(A      ):
		# If the line is an if is_backend_available, we grab all objects associated.
		UpperCAmelCase_    			=     find_backend(lines[line_index]      )
		if backend is not None:
			while not lines[line_index].startswith("    else:"      ):
				line_index += 1
			line_index += 1

			UpperCAmelCase_    			=     []
			# Until we unindent, add backend objects to the list
			while len(lines[line_index]      ) <= 1 or lines[line_index].startswith(" " * 8      ):
				UpperCAmelCase_    			=     lines[line_index]
				UpperCAmelCase_    			=     _re_single_line_import.search(A      )
				if single_line_import_search is not None:
					objects.extend(single_line_import_search.groups()[0].split(", "      )      )
				elif line.startswith(" " * 12      ):
					objects.append(line[12:-2]      )
				line_index += 1

			UpperCAmelCase_    			=     objects
		else:
			line_index += 1

	return backend_specific_objects



def  __lowerCAmelCase (  A    ,       A      ):
	if name.isupper():
		return DUMMY_CONSTANT.format(A      )
	elif name.islower():
		return DUMMY_FUNCTION.format(A    ,       A      )
	else:
		return DUMMY_CLASS.format(A    ,       A      )



def  __lowerCAmelCase (  A=None      ):
	if backend_specific_objects is None:
		UpperCAmelCase_    			=     read_init()
	# For special correspondence backend to module name as used in the function requires_modulename
	UpperCAmelCase_    			=     {}

	for backend, objects in backend_specific_objects.items():
		UpperCAmelCase_    			=     "[" + ", ".join(F"\"{b}\"" for b in backend.split("_and_"      )      ) + "]"
		UpperCAmelCase_    			=     "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
		dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
		dummy_file += "\n".join([create_dummy_object(A    ,       A      ) for o in objects]      )
		UpperCAmelCase_    			=     dummy_file

	return dummy_files



def  __lowerCAmelCase (  A=False      ):
	UpperCAmelCase_    			=     create_dummy_files()
	# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
	UpperCAmelCase_    			=     {"torch": "pt"}

	# Locate actual dummy modules and read their content.
	UpperCAmelCase_    			=     os.path.join(A    ,       "utils"      )
	UpperCAmelCase_    			=     {
	    backend: os.path.join(A    ,       F"dummy_{short_names.get(A    ,       A      )}_objects.py"      )
	    for backend in dummy_files.keys()
	}

	UpperCAmelCase_    			=     {}
	for backend, file_path in dummy_file_paths.items():
		if os.path.isfile(A      ):
			with open(A    ,       "r"    ,       encoding="utf-8"    ,       newline="\n"      ) as f:
				UpperCAmelCase_    			=     f.read()
		else:
			UpperCAmelCase_    			=     ""

	for backend in dummy_files.keys():
		if dummy_files[backend] != actual_dummies[backend]:
			if overwrite:
				print(
				    F"Updating transformers.utils.dummy_{short_names.get(A    ,       A      )}_objects.py as the main "
				    "__init__ has new objects."      )
				with open(dummy_file_paths[backend]    ,       "w"    ,       encoding="utf-8"    ,       newline="\n"      ) as f:
					f.write(dummy_files[backend]      )
			else:
				raise ValueError(
				    "The main __init__ has objects that are not present in "
				    F"transformers.utils.dummy_{short_names.get(A    ,       A      )}_objects.py. Run `make fix-copies` "
				    "to fix this."      )


if __name__ == "__main__":
				_a:      Tuple								=     argparse.ArgumentParser()
				parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
				_a:      Optional[int]								=     parser.parse_args()

				check_dummies(args.fix_and_overwrite)


from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import divide, inta, multiply, ravel, sort, zeros_like



def  __lowerCAmelCase (  A    ,       A=3      ):
	UpperCAmelCase_    			=     int(mask / 2      )
	# copy image size
	UpperCAmelCase_    			=     zeros_like(A      )
	for i in range(A    ,       gray_img.shape[0] - bd      ):
		for j in range(A    ,       gray_img.shape[1] - bd      ):
			# get mask according with mask
			UpperCAmelCase_    			=     ravel(gray_img[i - bd : i + bd + 1, j - bd : j + bd + 1]      )
			# calculate mask median
			UpperCAmelCase_    			=     sort(A      )[inta(divide((multiply(A    ,       A      ))    ,       2      ) + 1      )]
			UpperCAmelCase_    			=     median
	return median_img


if __name__ == "__main__":
				# read original image
				_a:      Optional[int]								=     imread("""../image_data/lena.jpg""")
				# turn image in gray scale value
				_a:      Dict								=     cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				_a:      Tuple								=     median_filter(gray, 3)
				_a:      Dict								=     median_filter(gray, 5)

				# show result images
				imshow("""median filter with 3x3 mask""", medianaxa)
				imshow("""median filter with 5x5 mask""", medianaxa)
				waitKey(0)