class_docstr: Tests for methods in linear_interpolation module.
docstr: Tests linear interpolation with multiple batching dimensions.
docstr_tok: ["Tests","linear","interpolation","with","multiple","batching","dimensions","."]
code: def test_linear_interpolation_dynamic_number_points(self):
      """Tests linear interpolation with multiple batching dimensions."""
      if tf.executing_eagerly():
          # No dynamic shapes in eager mode
          return
      dtype = np.float64
      x = tf.compat.v1.placeholder(dtype, [1, 2, None])
      x_data = np.array([[[1, 2], [3, 4]]])
      y_data = np.array([[[0, 1], [2, 3]]])
      op = tff.math.interpolation.linear.interpolate(
          x, x_data, y_data, dtype=dtype
      )
      with self.cached_session() as session:
          results = session.run(
              op, feed_dict={x: [[[1.5, 2.0, 3.0], [3.5, 4.0, 2.0]]]}
          )
      self.assertAllClose(
          results, np.array([[[0.5, 1.0, 1.0], [2.5, 3.0, 2.0]]]), 1e-8
      )
  
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 13 for calling the LinearInterpolation obj's underlying member method code with example usage: obj.test_linear_interpolation_dynamic_number_points() without return types