code: def test_causal_call_and_grad(self):
      layer = tl.Serial(
          tl.Dense(4),
          sparsity.CausalFavor(d_feature=4, n_heads=2),
          tl.L2Loss(),
      )
      x = np.random.uniform(size=(1, 2, 4)).astype(np.float32)
      w = np.ones_like(x)
      x_sig = shapes.signature(x)
      w_sig = shapes.signature(w)
      layer.init((x_sig, x_sig, w_sig))
      y = layer((x, x, w))
      self.assertEqual(y.shape, ())
      state = layer.state
      rng = fastmath.random.get_prng(0)
      fwd = lambda weights, inp: layer.pure_fn(
          inp, weights, state, rng=rng
      )[0]
      g = fastmath.grad(fwd)(layer.weights, (x, x, w))
      self.assertEqual(g[0][0].shape, (4, 4))
  
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 FavorTest obj's underlying member method code with example usage: obj.test_causal_call_and_grad() without return types