message: [tfdbg] Restore numeric-value assertion in distributed_callbacks_test
  After CL/279230921 moved `apply_gradients` inside `train_step`, the discrepancy
  in the numeric values of the updated variables seem to be consistent between
  TAP and Kokoro builds now. This CL reinstates the numeric-value assertions.
diff: @@ -165,20 +165,13 @@ class DistributedDumpingCallbackTest(
  updated_var_values = self.evaluate(mini_model.variables)
  num_devices = len(distribution.extended.worker_devices)
  - assert num_devices in [1, 2]
  - # TODO(cais): We currently refrain from asserting the
  - # element-by-element values of the variable updates. The values seem to
  - # vary among builds. On some builds, it's 0.75; on others, it's 1.0.
  - # This variation is seen in the MirroredCPUAndGPU and OneDeviceGPU
  - # strategies. Needs investigation.
  - # if num_devices == 1:
  - # self.assertAllEqual(0.75 * np.ones([10, 1]), updated_var_values[0])
  - # self.assertAllEqual([0.75], updated_var_values[1]).
  - # else:
  - # self.assertAllEqual(0.5 * np.ones([10, 1]), updated_var_values[0])
  - # self.assertAllEqual([0.5], updated_var_values[1])
  - self.assertEqual(updated_var_values[0].shape, (10, 1))
  - self.assertEqual(updated_var_values[1].shape, (1,))
  + assert num_devices in (1, 2)
  + if num_devices == 1:
  + self.assertAllEqual(0.75 * np.ones([10, 1]), updated_var_values[0])
  + self.assertAllEqual([0.75], updated_var_values[1])
  + else:
  + self.assertAllEqual(0.5 * np.ones([10, 1]), updated_var_values[0])
  + self.assertAllEqual([0.5], updated_var_values[1])
  writer.FlushNonExecutionFiles()
  writer.FlushExecutionFiles()
  