




"""simple docstring"""






import os
import sys
import unittest


lowercase__  		=		os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
lowercase__  		=		os.path.join(git_repo_path, """src""", """diffusers""")






class lowerCAmelCase__			(  unittest.TestCase		):






			'''simple docstring'''



			def       A_					(						self						):
							_lowerCamelCase  :    str					=					find_backend('    if not is_torch_available():'						)
							self.assertEqual(lowercase						,   'torch'						)

							# backend_with_underscore = find_backend("    if not is_tensorflow_text_available():")
							# self.assertEqual(backend_with_underscore, "tensorflow_text")

							_lowerCamelCase  :    List[Any]					=					find_backend('    if not (is_torch_available() and is_transformers_available()):'						)
							self.assertEqual(lowercase						,   'torch_and_transformers'						)

							# double_backend_with_underscore = find_backend(
							#    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"
							# )
							# self.assertEqual(double_backend_with_underscore, "sentencepiece_and_tensorflow_text")

							_lowerCamelCase  :    Optional[int]					=					find_backend(
							    '    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):'						)
							self.assertEqual(lowercase						,   'torch_and_transformers_and_onnx'						)
			def       A_					(						self						):
							_lowerCamelCase  :    Dict					=					read_init()
							# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
							self.assertIn('torch'						,   lowercase						)
							self.assertIn('torch_and_transformers'						,   lowercase						)
							self.assertIn('flax_and_transformers'						,   lowercase						)
							self.assertIn('torch_and_transformers_and_onnx'						,   lowercase						)

							# Likewise, we can't assert on the exact content of a key
							self.assertIn('UNet2DModel'						,   objects['torch']						)
							self.assertIn('FlaxUNet2DConditionModel'						,   objects['flax']						)
							self.assertIn('StableDiffusionPipeline'						,   objects['torch_and_transformers']						)
							self.assertIn('FlaxStableDiffusionPipeline'						,   objects['flax_and_transformers']						)
							self.assertIn('LMSDiscreteScheduler'						,   objects['torch_and_scipy']						)
							self.assertIn('OnnxStableDiffusionPipeline'						,   objects['torch_and_transformers_and_onnx']						)
			def       A_					(						self						):
							_lowerCamelCase  :    List[str]					=					create_dummy_object('CONSTANT'						,   '\'torch\''						)
							self.assertEqual(lowercase						,   '\nCONSTANT = None\n'						)

							_lowerCamelCase  :    Any					=					create_dummy_object('function'						,   '\'torch\''						)
							self.assertEqual(
							    lowercase						,   '\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'						)

							_lowerCamelCase  :    List[str]					=					'\nclass FakeClass(metaclass=DummyObject):\n    _backends = \'torch\'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, \'torch\')\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, \'torch\')\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, \'torch\')\n'
							_lowerCamelCase  :    int					=					create_dummy_object('FakeClass'						,   '\'torch\''						)
							self.assertEqual(lowercase						,   lowercase						)






			def       A_					(						self						):
							_lowerCamelCase  :    int					=					'# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, ["torch"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = ["torch"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, ["torch"])\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, ["torch"])\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, ["torch"])\n'
							_lowerCamelCase  :    List[str]					=					create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']}						)
							self.assertEqual(dummy_files['torch']						,   lowercase						)





"""simple docstring"""






def   _snake_case    (       lowercase__	):
				_lowerCamelCase  :    Optional[int]					=					int(lowercase__	)
				if decimal in (0, 1):  # Exit cases for the recursion
								return str(lowercase__	)
				_lowerCamelCase,				_lowerCamelCase  :    Dict					=					divmod(lowercase__							,					2	)
				return binary_recursive(lowercase__	) + str(lowercase__	)







def   _snake_case    (       lowercase__	):
				_lowerCamelCase  :    List[Any]					=					str(lowercase__	).strip()
				if not number:
								raise ValueError('No input value was provided'	)
				_lowerCamelCase  :    str					=					'-' if number.startswith('-'	) else ''
				_lowerCamelCase  :    Union[str, Any]					=					number.lstrip('-'	)
				if not number.isnumeric():
								raise ValueError('Input value is not an integer'	)
				return f'''{negative}0b{binary_recursive(int(lowercase__	)	)}'''


if __name__ == "__main__":
			from doctest import testmod

			testmod()