class_docstr: Test for 1-D usage of tfp.math.interp_regular_1d_grid.
class_docstr_tok: ["Test","for","1-D","usage","of","tfp.math.interp_regular_1d_grid","."]
code: def test_vector_valued_interpolation_with_empty_batch_shape(self):
      implied_x_ref = tf.linspace(1.0, 3.0, 200)  # Shape [200]
      y_ref = tf.stack(  # Shape [200, 2]
          [tf.exp(implied_x_ref), tf.math.log(implied_x_ref)], axis=-1
      )
  
      # x has no batch dims, which it shouldn't since axis=0.
      x = [1.0, 2.0, 3.0]
      y = interpolation.batch_interp_regular_1d_grid(
          x, x_ref_min=1.0, x_ref_max=3.0, y_ref=y_ref, axis=0
      )
      self.assertAllEqual((3, 2), y.shape)
      y_ = self.evaluate(y)
      expected_y = np.stack([np.exp(x), np.log(x)], axis=-1)
      self.assertAllClose(y_, expected_y, rtol=1e-3, atol=1e-3)
  
imports: import numpy
  from scipy import interpolate
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math import interpolation
label_desc: Use image node_id 10 for calling the BatchInterpRegular1DGridTest obj's underlying member method code with example usage: obj.test_vector_valued_interpolation_with_empty_batch_shape() without return types