def BlockGrad(data=None, name=None, attr=None, out=None, **kwargs):
    """Stops gradient computation.

    Stops the accumulated gradient of the inputs from flowing through this operator
    in the backward direction. In other words, this operator prevents the contribution
    of its inputs to be taken into account for computing gradients.

    Example::

      v1 = [1, 2]
      v2 = [0, 1]
      a = Variable('a')
      b = Variable('b')
      b_stop_grad = stop_gradient(3 * b)
      loss = MakeLoss(b_stop_grad + a)

      executor = loss.simple_bind(ctx=cpu(), a=(1,2), b=(1,2))
      executor.forward(is_train=True, a=v1, b=v2)
      executor.outputs
      [ 1.  5.]

      executor.backward()
      executor.grad_arrays
      [ 0.  0.]
      [ 1.  1.]



    Defined in src/operator/tensor/elemwise_unary_op_basic.cc:L327

    Parameters
    ----------
    data : Symbol
        The input array.

    name : string, optional.
        Name of the resulting symbol.

    Returns
    -------
    Symbol
        The result symbol.
    """
    return 0,
