docstr: Checks the interpolation for yield curve is non-NaN for 0 time.
docstr_tok: ["Checks","the","interpolation","for","yield","curve","is","non-NaN","for","0","time","."]
code: def test_interpolated_yields_zero_time(self):
      """Checks the interpolation for yield curve is non-NaN for 0 time."""
      dtypes = [np.float32, np.float64]
      for dtype in dtypes:
          reference_times = np.array(
              [0.3, 1.0, 1.43, 3.7, 9.2, 12.48], dtype=dtype
          )
          yields = np.array([3.0, 3.1, 2.9, 4.1, 4.3, 5.1], dtype=dtype)
  
          # Times for which the interpolated values are required.
          interpolation_times = tf.constant([0.0], dtype=dtype)
          actual = self.evaluate(
              monotone_convex.interpolate_yields(
                  interpolation_times, reference_times, yields=yields
              )
          )
          np.testing.assert_allclose(actual, [0.0], rtol=1e-8)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow.python.framework import test_util
  from tf_quant_finance.rates.hagan_west import monotone_convex
label_desc: Use image node_id 12 for calling the MonotoneConvexTest obj's underlying member method code with example usage: obj.test_interpolated_yields_zero_time() without return types