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lib/AI/MXNet/NDArray.pm  view on Meta::CPAN

=head2 _new_empty_handle

    Returns a new empty handle.

    Empty handle can be used to hold result

    Returns
    -------
        a new empty ndarray handle
=cut

sub _new_empty_handle
{
    my $hdl = check_call(AI::MXNetCAPI::NDArrayCreateNone());
    return $hdl;
}

=head2 _new_alloc_handle

    Returns a new handle with specified shape and context.

    Empty handle is only used to hold results

    Returns
    -------
    a new empty ndarray handle
=cut

func _new_alloc_handle($shape, $ctx, $delay_alloc, $dtype)
{
    my $hdl = check_call(AI::MXNetCAPI::NDArrayCreateEx(
        $shape,
        scalar(@$shape),
        $ctx->device_type_id,
        $ctx->device_id,
        $delay_alloc,
        $dtype)
    );
    return $hdl;
}

=head2 waitall

    Wait for all async operations to finish in MXNet.
    This function is used for benchmarks only.
=cut

method waitall()
{
    check_call(AI::MXNetCAPI::NDArrayWaitAll());
}

=head2 _fresh_grad

        Parameters:
        ----------
        Maybe[Bool] $state=

        Whether this array's corresponding gradient array
        (registered via `autograd->mark_variables`) has been
        updated by `autograd->backward` since last reset.

        `_fresh_grad` need to be manually set to False
        after consuming gradient (usually after updating this
        array).
=cut

method _fresh_grad(Maybe[Bool] $state=)
{
    if(defined $state)
    {
        check_call(AI::MXNetCAPI::NDArraySetGradState($self->handle, $state));
        return $state;
    }
    else
    {
        return scalar(check_call(AI::MXNetCAPI::NDArrayGetGradState($self->handle)));
    }
}

=head2 detach

    Returns a new NDArray, detached from the current graph.
=cut

method detach()
{
    my $handle = check_call(AI::MXNetCAPI::NDArrayDetach($self->handle));
    return __PACKAGE__->new(handle => $handle);
}

method backward(Maybe[AI::MXNet::NDArray] $out_grad=, Bool $retain_graph=0)
{
    check_call(
        AI::MXNetCAPI::AutogradBackward(
            1,
            [$self->handle],
            [defined $out_grad ? $out_grad->handle : undef],
            $retain_graph
        )
    )
}

method CachedOp(@args) { AI::MXNet::CachedOp->new(@args) }

my $lvalue_methods = join "\n", map {"use attributes 'AI::MXNet::NDArray', \\&AI::MXNet::NDArray::$_, 'lvalue';"}
qw/at slice aspdl asmpdl reshape copy sever T astype as_in_context copyto empty zero ones full
                       array/;
eval << "EOV" if ($^V and $^V >= 5.006007);
{
  no warnings qw(misc);
  $lvalue_methods
}
EOV

__PACKAGE__->meta->make_immutable;