code: def test_apply_mean(self):
      x = jnp.ones(10)  # Base input
      bx = jnp.ones((7, 10))  # Batched input
  
      wrapped_ffn = params_adding_ffn(x)
  
      rr_ensemble = ensemble.make_ensemble(
          wrapped_ffn, ensemble.apply_mean, num_networks=3
      )
      key = jax.random.PRNGKey(0)
      params = rr_ensemble.init(key)
      self.assertTupleEqual(params.shape, (3,) + x.shape)
      self.assertFalse((params[0, ...] == params[1, ...]).all())
  
      y = rr_ensemble.apply(params, x)
      self.assertTupleEqual(y.shape, x.shape)
      np.testing.assert_allclose(
          jnp.mean(params, axis=0), y - x, atol=1e-5, rtol=1e-5
      )
  
      by = rr_ensemble.apply(params, bx)
      self.assertTupleEqual(by.shape, bx.shape)
  
imports: import functools
  from typing import Any
  from acme.agents.jax.mbop import ensemble
  from acme.jax import networks
  from flax import linen
  import jax
  import jax.numpy
  import numpy
  from absl.testing import absltest
label_desc: Use image node_id 4 for calling the EnsembleTest obj's underlying member method code with example usage: obj.test_apply_mean() without return types