




"""simple docstring"""


from math import factorial


def       UpperCAmelCase__ (snake_case__							:      int = 20					):
  """simple docstring"""

  _snake_case							:	List[Any]			=						2 * n  # middle entry of odd rows starting at row 3 is the solution for n = 1,
  # 2, 3,...
  _snake_case							:	str			=						n // 2

  return int(factorial(snake_case__					) / (factorial(snake_case__					) * factorial(n - k					))					)


if __name__ == "__main__":
     import sys

     if len(sys.argv) == 1:
          print(solution(20))
     else:
          try:
               A_									=       int(sys.argv[1])
               print(solution(n))
          except ValueError:
               print('''Invalid entry - please enter a number.''')








"""simple docstring"""


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				):







 '''simple docstring'''





 def 				UpperCamelCase_     (       self:	Tuple	):




   '''simple docstring'''



   _snake_case							:	Optional[int]			=						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")

   _snake_case							:	Any			=						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")

   _snake_case							:	Union[str, Any]			=						find_backend(
       """    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):"""	)
   self.assertEqual(a_,   """torch_and_transformers_and_onnx"""	)


 def 				UpperCamelCase_     (       self:	List[Any]	):




   '''simple docstring'''



   _snake_case							:	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""",   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 				UpperCamelCase_     (       self:	List[str]	):




   '''simple docstring'''



   _snake_case							:	Optional[Any]			=						create_dummy_object("""CONSTANT""",   """'torch'"""	)
   self.assertEqual(a_,   """\nCONSTANT = None\n"""	)

   _snake_case							:	Optional[int]			=						create_dummy_object("""function""",   """'torch'"""	)
   self.assertEqual(
       a_,   """\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"""	)

   _snake_case							:	List[Any]			=						"""
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')
"""
   _snake_case							:	Union[str, Any]			=						create_dummy_object("""FakeClass""",   """'torch'"""	)
   self.assertEqual(a_,   a_	)


 def 				UpperCamelCase_     (       self:	Union[str, Any]	):




   '''simple docstring'''



   _snake_case							:	Union[str, Any]			=						"""# 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\"])
"""
   _snake_case							:	List[Any]			=						create_dummy_files({"""torch""": ["""CONSTANT""", """function""", """FakeClass"""]}	)
   self.assertEqual(dummy_files["""torch"""],   a_	)


