code: def testPeaNutsNumpy(self):
      def execute(batch_size, latent_size, data_size):
          data = np.random.normal(size=(data_size, latent_size)).astype(
              np.float32
          )
  
          def step_state(state):
              return state + np.sum(
                  np.tensordot(data, state, ([1], [1]))
              )
  
          state = np.random.normal(
              size=(batch_size, latent_size)
          ).astype(np.float32)
  
          def choose_depth(count):
              del count
              return 3
  
          program = test_programs.pea_nuts_program(
              (latent_size,), choose_depth, step_state
          )
          input_counts = np.array([3] * batch_size)
          return vm.execute(
              program, [input_counts, state], 10, backend=NP_BACKEND
          )
  
      # Check that running the program doesn't crash
      result = execute(4, 3, 10)
      self.assertEqual((4, 3), result.shape)
  
imports: import functools
  from absl import flags
  import numpy
  import tensorflow.compat.v1
  from tensorflow_probability.python.experimental.auto_batching import numpy_backend
  from tensorflow_probability.python.experimental.auto_batching import test_programs
  from tensorflow_probability.python.experimental.auto_batching import tf_backend
  from tensorflow_probability.python.experimental.auto_batching import virtual_machine
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 10 for calling the VMTest obj's underlying member method code with example usage: obj.testPeaNutsNumpy() and returns: vm, unknown, int