code: def test_batch_input(self):
      # Expected results computed using `nelson-seigel-svensson` package
      interpolation_times = [
          [1.0, 2.0, 3.0, 4.0],
          [5.0, 10.0, 15.0, 20.0],
          [30.0, 40.0, 50.0, 60.0],
      ]
      s_p = tff.rates.nelson_seigel_svensson.SvenssonParameters(
          beta_0=0.25,
          beta_1=-0.4,
          beta_2=-0.02,
          beta_3=0.05,
          tau_1=4.5,
          tau_2=10,
      )
  
      output = self.evaluate(
          tff.rates.nelson_seigel_svensson.interpolate(
              interpolation_times, s_p
          )
      )
  
      expected_output = [
          [-0.10825214, -0.07188015, -0.04012282, -0.0123332],
          [0.01203921, 0.09686097, 0.14394756, 0.1716945],
          [0.20045316, 0.21411455, 0.22179659, 0.22668882],
      ]
  
      np.testing.assert_allclose(
          output, expected_output, atol=1e-5, rtol=1e-5
      )
  
file_path: tf-quant-finance/tf_quant_finance/rates/nelson_seigel_svensson/nelson_seigel_svensson_interpolation_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  import tf_quant_finance
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 3 for calling the NelsonSvenssonInterpolationTest obj's underlying member method code with example usage: obj.test_batch_input() without return types