code: def test_behaves_same_as_stacked_linears(self):
      w_init = tf.random.normal((3, 5, 7))
      b_init = tf.random.normal((3, 1, 7))
      inputs = tf.random.normal((3, 2, 5))
  
      parallel = parallel_linear.ParallelLinears(
          7, w_init=lambda s, d: w_init, b_init=lambda s, d: b_init
      )
      parallel_outputs = parallel(inputs)
  
      stacked_outputs = []
      for i in range(3):
          layer = linear.Linear(
              7,
              w_init=lambda s, d, i=i: w_init[i],
              b_init=lambda s, d, i=i: b_init[i],
          )
          stacked_outputs.append(layer(inputs[i]))
      stacked_outputs = tf.stack(stacked_outputs, axis=0)
  
      self.assertAllClose(
          parallel_outputs.numpy(), stacked_outputs.numpy()
      )
  
imports: from sonnet.src import linear
  from sonnet.src import parallel_linear
  from sonnet.src import test_utils
  import tensorflow
label_desc: Use image node_id 2 for calling the ParallelLinearTest obj's underlying member method code with example usage: obj.test_behaves_same_as_stacked_linears() without return types