code: def test_switchsparse_ff_predict_equals_eval(self):
      d_model = 1024
      n_experts = 64
      d_ff = d_model * 8
      x_shape = (1, 1, d_model)
      x = np.ones(x_shape).astype(np.float32)
      input_signature = shapes.signature(x)
      eval_model = sparsity.SwitchSparseFF(
          mode="eval", d_ff=d_ff, n_experts=n_experts
      )
      weights, state = eval_model.init(input_signature)
      eval_out, _ = eval_model.pure_fn(
          x, weights, state, rng=jax.random.PRNGKey(0)
      )
      pred_model = sparsity.SwitchSparseFF(
          mode="predict", d_ff=d_ff, n_experts=n_experts
      )
      pred_model.init(input_signature)
      pred_out, _ = pred_model.pure_fn(
          x, weights, state, rng=jax.random.PRNGKey(0)
      )
      self.assertEqual(eval_out.shape, x.shape)
      # eval_out and pred_out should be identical.
      np.testing.assert_array_almost_equal(
          eval_out[0, 0, :], pred_out[0, 0, :]
      )
  
imports: import functools
  from absl.testing import parameterized
  import jax
  import numpy
  from tensorflow import test
  from trax import fastmath
  from trax import shapes
  import trax.layers
  from trax.layers import test_utils
  from trax.layers.research import sparsity
label_desc: Use image node_id 8 for calling the EfficientFeedForwardTest obj's underlying member method code with example usage: obj.test_switchsparse_ff_predict_equals_eval() without return types