docstr: Parallel inference with broadcasted scalar input.
docstr_tok: ["Parallel","inference","with","broadcasted","scalar","input","."]
code: def test_parallel_concat_broadcast(self):
      """Parallel inference with broadcasted scalar input."""
      f = lambda x, y: x + y
      x = objax.random.normal((96, 3))
      d = jn.float32(0.5)
      y = f(x, d)
      fp = objax.Parallel(f, objax.VarCollection())
      z = fp(x, d)
      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 2 for calling the TestParallel obj's underlying member method code with example usage: obj.test_parallel_concat_broadcast() without return types