




"""simple docstring"""




import os
import sys
import unittest


lowercase__				:      Any	   = 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__				:      Tuple	   = os.path.join(git_repo_path, "src", "diffusers")




class       a__	( unittest.TestCase				):







     def       lowerCAmelCase_    (     self			)  ->   List[str]:



          '''simple docstring'''



          a     =				find_backend("    if not is_torch_available():"			)
          self.assertEqual(A  ,		"torch"			)

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

          a     =				find_backend("    if not (is_torch_available() and is_transformers_available()):"			)
          self.assertEqual(A  ,		"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")

          a     =				find_backend(
              "    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):"			)
          self.assertEqual(A  ,		"torch_and_transformers_and_onnx"			)







     def       lowerCAmelCase_    (     self			)  ->   str:



          '''simple docstring'''



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

          # 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]:



          '''simple docstring'''



          a     =				create_dummy_object("CONSTANT"  ,		"'torch'"			)
          self.assertEqual(A  ,		"\nCONSTANT = None\n"			)

          a     =				create_dummy_object("function"  ,		"'torch'"			)
          self.assertEqual(
              A  ,		"\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"			)

          a     =				"\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"
          a     =				create_dummy_object("FakeClass"  ,		"'torch'"			)
          self.assertEqual(A  ,		A			)







     def       lowerCAmelCase_    (     self			)  ->   str:



          '''simple docstring'''



          a     =				"# 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"
          a     =				create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}			)
          self.assertEqual(dummy_files["torch"]  ,		A			)







from __future__ import annotations

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					list[int]:
     a     =				2
     a     =				[]
     while i * i <= n:
          if n % i:
               i += 1
          else:
               n //= i
               factors.append(__UpperCamelCase)
     if n > 1:
          factors.append(__UpperCamelCase)
     return factors


if __name__ == "__main__":
   import doctest

   doctest.testmod()

