code: def setUp(self):
      super().setUp()
  
      self.s_t = np.array(
          [[0, 1, 0], [1, 1, 2]], dtype=np.float32
      )  # [B, T]
      self.w_s = np.ones([3, 2], dtype=np.float32)
      b_s = np.zeros([2], dtype=np.float32)
      # Add batch dimension to satisfy shape assertions.
      self.b_s = jnp.expand_dims(b_s, 0)
      self.w = np.ones([2, 1], dtype=np.float32)
      self.b = np.zeros([1], dtype=np.float32)
  
      self.expected = np.array([0.5, 0.5], dtype=np.float32)
  
imports: import functools
  from absl.testing import absltest
  from absl.testing import parameterized
  import chex
  import jax
  import jax.numpy
  import numpy
  from rlax._src import distributions
  from rlax._src import policy_gradients
label_desc: Use image node_id 1 for calling the DpgLossTest obj's underlying member method code with example usage: obj.setUp() without return types