docstr: Parallel inference (concat reduction) without batch splitting.
docstr_tok: ["Parallel","inference","(","concat","reduction",")","without","batch","splitting","."]
code: def test_parallel_list(self):
      """Parallel inference (concat reduction) without batch splitting."""
      f = objax.nn.Linear(3, 4)
      g = lambda x: f(x[0]) + x[1][:, jn.newaxis]
      x1 = objax.random.normal((96, 3))
      x2 = objax.random.normal((96,))
      y = g([x1, x2])
      fp = objax.Parallel(g, vc=f.vars())
      with fp.vars().replicate():
          z = fp([x1, x2])
      self.assertTrue(jn.array_equal(y, z))
  
imports: import os
  import unittest
  import jax.numpy
  import numpy
  import objax
label_desc: Use image node_id 4 for calling the TestParallel obj's underlying member method code with example usage: obj.test_parallel_list() without return types