NAME

    AI::MXNet::AutoGrad - Autograd for NDArray.

set_is_training

    Set status to training/not training. When training, graph will be constructed
    for gradient computation. Operators will also run with ctx.is_train=True. For example,
    Dropout will drop inputs randomly when is_train=True while simply passing through
    if is_train=False.

    Parameters
    ----------
    is_train: bool

    Returns
    -------
    previous state before this set.

mark_variables

    Mark AI::MXNet::NDArrays as variables to compute gradient for autograd.

    Parameters
    ----------
    variables: array ref of AI::MXNet::NDArrays
    gradients: array ref of AI::MXNet::NDArrays
    grad_reqs: array ref of strings

backward

     Compute the gradients of outputs w.r.t variables.

     Parameters
     ----------
     outputs: array ref of NDArray
     out_grads: array ref of NDArray or undef
     retain_graph: bool, defaults to false

compute_gradient

    Compute the gradients of outputs w.r.t variables.

    Parameters
    ----------
    outputs: array ref of NDArray

    Returns
    -------
    gradients: array ref of NDArray

grad_and_loss

    Return function that computes both gradient of arguments and loss value.

    Parameters
    ----------
    func: a perl sub
        The forward (loss) function.
    argnum: an int or a array ref of int
        The index of argument to calculate gradient for.

    Returns
    -------
    grad_and_loss_func: a perl sub
        A function that would compute both the gradient of arguments and loss value.

grad

    Return function that computes gradient of arguments.

    Parameters
    ----------
    func: a perl sub
        The forward (loss) function.
    argnum: an int or arry ref of int
        The index of argument to calculate gradient for.

    Returns
    -------
    grad_func: a perl function
        A function that would compute the gradient of arguments.