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                );
            }
            $param->eval_metric->reset if $auto_reset;
        }
    }
}

package AI::MXNet::Speedometer;
use Mouse;
use Time::HiRes qw/time/;
extends 'AI::MXNet::Callback';

=head1 NAME

    AI::MXNet::Speedometer - A callback that logs training speed 
=cut

=head1 DESCRIPTION

    Calculate and log training speed periodically.

    Parameters
    ----------
    batch_size: int
        batch_size of data
    frequent: int
        How many batches between calculations.
        Defaults to calculating & logging every 50 batches.
    auto_reset: Bool
        Reset the metric after each log, defaults to true.
=cut

has 'batch_size' => (is => 'ro', isa => 'Int', required => 1);
has 'frequent'   => (is => 'ro', isa => 'Int', default  => 50);
has 'init'       => (is => 'rw', isa => 'Int', default  => 0);
has 'tic'        => (is => 'rw', isa => 'Num', default  => 0);
has 'last_count' => (is => 'rw', isa => 'Int', default  => 0);
has 'auto_reset' => (is => 'ro', isa => 'Bool', default  => 1);

method call(AI::MXNet::BatchEndParam $param)
{
    my $count = $param->nbatch;
    if($self->last_count > $count)
    {
        $self->init(0);
    }
    $self->last_count($count);

    if($self->init)
    {
        if(($count % $self->frequent) == 0)
        {
            my $speed = $self->frequent * $self->batch_size / (time - $self->tic);
            if(defined $param->eval_metric)
            {
                my $name_value = $param->eval_metric->get_name_value;
                $param->eval_metric->reset if $self->auto_reset;
                while(my ($name, $value) = each %{ $name_value })
                {
                    AI::MXNet::Logging->info(
                        "Epoch[%d] Batch [%d]\tSpeed: %.2f samples/sec\tTrain-%s=%f",
                        $param->epoch, $count, $speed, $name, $value
                    );
                }
            }
            else
            {
                AI::MXNet::Logging->info(
                    "Iter[%d] Batch [%d]\tSpeed: %.2f samples/sec",
                    $param->epoch, $count, $speed
                );
            }
            $self->tic(time);
        }
    }
    else
    {
        $self->init(1);
        $self->tic(time);
    }
}

*slice = \&call;

package AI::MXNet::ProgressBar;
use Mouse;
extends 'AI::MXNet::Callback';

=head1 NAME

    AI::MXNet::ProgressBar - A callback to show a progress bar.

=head1 DESCRIPTION

    Shows a progress bar.

    Parameters
    ----------
    total: Int
        batch size, default is 1
    length: Int
        the length of the progress bar, default is 80 chars
=cut

has 'length'  => (is => 'ro', isa => 'Int', default => 80);
has 'total'   => (is => 'ro', isa => 'Int', required => 1);

method call(AI::MXNet::BatchEndParam $param)
{
    my $count = $param->nbatch;
    my $filled_len = int(0.5 + $self->length * $count / $self->total);
    my $percents = int(100.0 * $count / $self->total) + 1;
    my $prog_bar = ('=' x $filled_len) . ('-' x ($self->length - $filled_len));
    print "[$prog_bar] $percents%\r";
}

*slice = \&call;

# Just logs the eval metrics at the end of an epoch.
package AI::MXNet::LogValidationMetricsCallback;
use Mouse;
extends 'AI::MXNet::Callback';

=head1 NAME

    AI::MXNet::LogValidationMetricsCallback - A callback to log the eval metrics at the end of an epoch.
=cut

method call(AI::MXNet::BatchEndParam $param)