code: def test_predict_equals_eval(self):
      with fastmath.use_backend(fastmath.Backend.JAX):
          d_model = 32
          seq_len = 5
          x_shape = (1, seq_len, d_model)
          inp = np.ones(x_shape).astype(np.float32)
  
          model_fn = functools.partial(
              sparsity.MultiplicativeConvCausalAttention,
              d_feature=d_model,
              n_heads=4,
              sparsity=4,
          )
  
          list_kwargs = []
          for share_qk in [True, False]:
              for output in ["none", "mult", "conv", "multconv"]:
                  for concat in ["original", "fixed", "none"]:
                      kwargs = {
                          "share_qk": share_qk,
                          "output_layer_type": output,
                          "v_concat_type": concat,
                      }
                      list_kwargs.append(kwargs)
  
          test_utils.test_eval_equals_predict_configs(
              inp, model_fn, list_kwargs
          )
  
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 3 for calling the MultiplicativeConvCausalAttentionTest obj's underlying member method code with example usage: obj.test_predict_equals_eval() without return types