





import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
      import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin
@require_torch
class        SCREAMING_SNAKE_CASE     (unittest.TestCase    ,			UpperCAmelCase   ):


   def  SCREAMING_SNAKE_CASE_							(					self    :       List[str] )->     Any:





     """simple docstring"""







     lowercase__			    =						load_tool('text-to-speech' )
     self.tool.setup()


   def  SCREAMING_SNAKE_CASE_							(					self    :       Union[str, Any] )->     Optional[int]:





     """simple docstring"""







     torch.manual_seed(0 )
     lowercase__			    =						self.tool('hey' )
     lowercase__			    =						result.to_raw()
     self.assertTrue(
         torch.allclose(
             resulting_tensor[:3]    ,  torch.tensor([-0.0005966668832115829, -0.0003657640190795064, -0.00013439502799883485] )    ,  ) )


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





     """simple docstring"""







     torch.manual_seed(0 )
     lowercase__			    =						self.tool('hey' )
     lowercase__			    =						result.to_raw()
     self.assertTrue(
         torch.allclose(
             resulting_tensor[:3]    ,  torch.tensor([-0.0005966668832115829, -0.0003657640190795064, -0.00013439502799883485] )    ,  ) )









def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE = 50	)       ->     int:
  lowercase__			    =						[1] * (length + 1)

  for row_length in range(3	,		length + 1	):
    for block_length in range(3	,		row_length + 1	):
      for block_start in range(row_length - block_length	):
        ways_number[row_length] += ways_number[
            row_length - block_start - block_length - 1
        ]

      ways_number[row_length] += 1

  return ways_number[length]


if __name__ == "__main__":
      print(f'''{solution() = }''')


