Example of TF function with dynamic but nonetheless inferrable shapes

tf_dynamic_shapes.py

def model_fn_changing_shapes(x):
  return 2 * x

def run_changing_shapes_model():
  with tf.Session() as sess:
    x = tf.placeholder(tf.float32, name='x')
    result = xla.compile(model_fn_changing_shapes, (x,))[0]
    a = sess.run(result, feed_dict={x: [1., 2.]})
    b = sess.run(result, feed_dict={x: [1., 2., 3.]})

    # Prints "a.shape = (2,); b.shape = (3,)"
    print("a.shape = " + str(a.shape) + "; b.shape = " + str(b.shape))