






import os
import sys
import unittest


lowerCamelCase      :       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
lowerCamelCase      :       List[Any]    =						os.path.join(git_repo_path, '''src''', '''diffusers''')



class 				_UpperCamelCase      (unittest.TestCase      ):


      def 			__UpperCAmelCase		(						self						)->						Any:
           __lowerCAmelCase             =       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")

           __lowerCAmelCase             =       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")

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


      def 			__UpperCAmelCase		(						self						)->						Tuple:
           __lowerCAmelCase             =       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 			__UpperCAmelCase		(						self						)->						Optional[Any]:
           __lowerCAmelCase             =       create_dummy_object("CONSTANT"       ,    "'torch'"						)
           self.assertEqual(__UpperCamelCase       ,    "\nCONSTANT = None\n"						)

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

           __lowerCAmelCase             =       "\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             =       create_dummy_object("FakeClass"       ,    "'torch'"						)
           self.assertEqual(__UpperCamelCase       ,    __UpperCamelCase						)


      def 			__UpperCAmelCase		(						self						)->						Any:
           __lowerCAmelCase             =       "# 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             =       create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}						)
           self.assertEqual(dummy_files["torch"]       ,    __UpperCamelCase						)














import os

# Precomputes a list of the 100 first triangular numbers
lowerCamelCase      :       str    =						[int(0.5 * n * (n + 1)) for n in range(1, 101)]





def    __lowerCAmelCase   (    ):
     __lowerCAmelCase             =       os.path.dirname(os.path.realpath(__snake_case							)							)
     __lowerCAmelCase             =       os.path.join(__snake_case       ,			"words.txt"							)

     __lowerCAmelCase             =       ""
     with open(__snake_case							) as f:
          __lowerCAmelCase             =       f.readline()

     __lowerCAmelCase             =       [word.strip("\""							) for word in words.strip("\r\n"							).split(","							)]
     __lowerCAmelCase             =       [
         word
         for word in [sum(ord(__snake_case							) - 64 for x in word							) for word in words]
         if word in TRIANGULAR_NUMBERS
     ]
     return len(__snake_case							)


if __name__ == "__main__":
 print(solution())






