docstr: Test the shapes are correct for different dimensional inputs.
  
  Args:
    dimensions: The number of dimensions of the input test signal.
docstr_tok: ["Test","the","shapes","are","correct","for","different","dimensional","inputs",".","Args",":","dimensions",":","The","number","of","dimensions","of","the","input","test","signal","."]
code: def test_multi_dimensional_inputs(self, dimensions):
      """Test the shapes are correct for different dimensional inputs.
  
      Args:
        dimensions: The number of dimensions of the input test signal.
      """
      # Create test signal.
      inputs_shape = [self.n_smaller] * dimensions
      inputs = np.ones(inputs_shape)
  
      # Run through the resampling op.
      outputs = core.resample(inputs, self.n_larger)
  
      # Compute output shape.
      outputs_shape = inputs_shape
      if dimensions == 1:
          outputs_shape[0] = self.n_larger
      else:
          outputs_shape[1] = self.n_larger
  
      self.assertListEqual(list(outputs.shape), outputs_shape)
  
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 2 for calling the ResampleTest obj's underlying member method code with example usage: obj.test_multi_dimensional_inputs(dimensions) without return types