






import os
import sys
import unittest


__UpperCamelCase    :						Optional[int]		     =  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
__UpperCamelCase    :						Any		     =  os.path.join(git_repo_path, """src""", """diffusers""")


class      __SCREAMING_SNAKE_CASE(		unittest.TestCase		):
							def lowerCAmelCase_       (   self:					Union[str, Any]  )						->						List[Any]:
											snake_case__													=   find_backend('    if not is_torch_available():'  )
											self.assertEqual(UpperCamelCase_				,		'torch'  )

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

											snake_case__													=   find_backend('    if not (is_torch_available() and is_transformers_available()):'  )
											self.assertEqual(UpperCamelCase_				,		'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")

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

											# 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 lowerCAmelCase_       (   self:					Optional[Any]  )						->						Optional[int]:
											snake_case__													=   create_dummy_object('CONSTANT'				,		'\'torch\''  )
											self.assertEqual(UpperCamelCase_				,		'\nCONSTANT = None\n'  )

											snake_case__													=   create_dummy_object('function'				,		'\'torch\''  )
											self.assertEqual(
											    UpperCamelCase_				,		'\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'  )

											snake_case__													=   '\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'
											snake_case__													=   create_dummy_object('FakeClass'				,		'\'torch\''  )
											self.assertEqual(UpperCamelCase_				,		UpperCamelCase_  )


							def lowerCAmelCase_       (   self:					Any  )						->						List[Any]:
											snake_case__													=   '# 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'
											snake_case__													=   create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']}  )
											self.assertEqual(dummy_files['torch']				,		UpperCamelCase_  )








from ..utils import DummyObject, requires_backends


class        _a							(			metaclass=UpperCamelCase__			):
							_lowercase	:			Any        = ['''torch''', '''scipy''']

							def __init__(							self:	int    ,						*UpperCamelCase_:	Any    ,						**UpperCamelCase_:	Optional[Any]							)			->   List[str]:





									"""simple docstring"""







									requires_backends(self    ,						['''torch''', '''scipy''']							)

							@classmethod
							def       lowerCamelCase_ (							cls:	Optional[int]    ,						*UpperCamelCase_:	Any    ,						**UpperCamelCase_:	List[Any]							)			->   int:





									"""simple docstring"""







									requires_backends(cls    ,						['''torch''', '''scipy''']							)


							@classmethod
							def       lowerCamelCase_ (							cls:	Any    ,						*UpperCamelCase_:	Any    ,						**UpperCamelCase_:	Dict							)			->   Optional[int]:





									"""simple docstring"""







									requires_backends(cls    ,						['''torch''', '''scipy''']							)


