import os
import sys
import unittest


A_      =      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
A_      =      os.path.join(git_repo_path, "src", "diffusers")






class      __lowercase					(    unittest.TestCase    ):

						def        __a		(	self				:      Optional[int]   )							->		Optional[Any]:


									'''simple docstring'''

									lowercase							=		find_backend('''    if not is_torch_available():'''   )
									self.assertEqual(__lowerCamelCase							,							'''torch'''   )

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

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

									lowercase							=		find_backend(
									    '''    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):'''   )
									self.assertEqual(__lowerCamelCase							,							'''torch_and_transformers_and_onnx'''   )

						def        __a		(	self				:      Optional[Any]   )							->		Tuple:


									'''simple docstring'''

									lowercase							=		read_init()
									# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
									self.assertIn('''torch'''							,							__lowerCamelCase   )
									self.assertIn('''torch_and_transformers'''							,							__lowerCamelCase   )
									self.assertIn('''flax_and_transformers'''							,							__lowerCamelCase   )
									self.assertIn('''torch_and_transformers_and_onnx'''							,							__lowerCamelCase   )

									# 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				:      Dict   )							->		str:


									'''simple docstring'''

									lowercase							=		create_dummy_object('''CONSTANT'''							,							'''\'torch\''''   )
									self.assertEqual(__lowerCamelCase							,							'''\nCONSTANT = None\n'''   )

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

									lowercase							=		'''
class FakeClass(metaclass=DummyObject):
    _backends = \'torch\'

    def __init__(self, *args, **kwargs):
        requires_backends(self, \'torch\')

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, \'torch\')

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, \'torch\')
'''
									lowercase							=		create_dummy_object('''FakeClass'''							,							'''\'torch\''''   )
									self.assertEqual(__lowerCamelCase							,							__lowerCamelCase   )



						def        __a		(	self				:      int   )							->		int:


									'''simple docstring'''

									lowercase							=		'''# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, ["torch"])


class FakeClass(metaclass=DummyObject):
    _backends = ["torch"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, ["torch"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch"])
'''
									lowercase							=		create_dummy_files({'''torch''': ['''CONSTANT''', '''function''', '''FakeClass''']}   )
									self.assertEqual(dummy_files['''torch''']							,							__lowerCamelCase   )






import cmath
import math






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase       )->       complex:



			"""simple docstring"""







			lowercase							=		math.radians(UpperCAmelCase       )
			lowercase							=		math.radians(UpperCAmelCase       )

			# Convert voltage and current to rectangular form
			lowercase							=		cmath.rect(UpperCAmelCase,		UpperCAmelCase       )
			lowercase							=		cmath.rect(UpperCAmelCase,		UpperCAmelCase       )

			# Calculate apparent power
			return voltage_rect * current_rect


if __name__ == "__main__":
						import doctest

						doctest.testmod()





