docstr: Test that upsample_with_window runs for integer upsampling ratios.
  
  If add_endpoint is False, n_after must be divisible by n_before - 1 instead
  of n_before.
  
  Args:
    n_before: Number of points before resampling.
    add_endpoint: Add extra timestep at end of resampling.
docstr_tok: ["Test","that","upsample_with_window","runs","for","integer","upsampling","ratios",".","If","add_endpoint","is","False",",","n_after","must","be","divisible","by","n_before","-","1","instead","of","n_before",".","Args",":","n_before",":","Number","of","points","before","resampling",".","add_endpoint",":","Add","extra","timestep","at","end","of","resampling","."]
code: def test_window_allows_integer_upsampling_ratios(
      self, n_before, add_endpoint
  ):
      """Test that upsample_with_window runs for integer upsampling ratios.
  
      If add_endpoint is False, n_after must be divisible by n_before - 1 instead
      of n_before.
  
      Args:
        n_before: Number of points before resampling.
        add_endpoint: Add extra timestep at end of resampling.
      """
      _, after = self.create_resampled_signals(
          n_before=n_before,
          n_after=self.n_larger,
          add_endpoint=add_endpoint,
          method="window",
      )
      self.assertEqual(self.n_larger, after.size)
  
imports: from absl.testing import parameterized
  from ddsp import core
  import librosa
  import numpy
  from scipy import signal
  import tensorflow.compat.v2
label_desc: Use image node_id 9 for calling the ResampleTest obj's underlying member method code with example usage: obj.test_window_allows_integer_upsampling_ratios(n_before, add_endpoint) without return types