code: def test_0d_1d_parameter_set_value():
      x = C.input_variable(2)
      w_0d = C.parameter(())
      op = x + w_0d
      w_0d_grad = op.grad(
          {x: np.asarray([1, 2], dtype=np.float32)},
          wrt=[w_0d],
          as_numpy=False,
      )
      w_0d.value = w_0d_grad.data
      assert w_0d.value == 2.0
  
      w_1d = C.parameter(shape=2)
      op = x + w_1d
      w_1d_grad = op.grad(
          {x: np.asarray([1, 2], dtype=np.float32)},
          wrt=[w_1d],
          as_numpy=False,
      )
      w_1d.value = w_1d_grad.data
      assert np.array_equal(w_1d.value, [1.0, 1.0])
  
imports: from __future__ import division, print_function
  import numpy
  import cntk
  from cntk import parameter
  import pytest
  import sys
  import itertools
  from cntk.logging import ProgressPrinter
  from cntk.learners import sgd, learning_rate_schedule, learning_parameter_schedule, UnitType, universal
  from cntk.layers import Dense, Sequential
label_desc: Use image node_id 19 for calling a global function with example usage: test_0d_1d_parameter_set_value() without return types