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

    forget_bias: float,a bias for the forget gate.
    Jozefowicz et al. 2015 recommends setting this to 1.0.
=cut

use Mouse;
extends 'AI::MXNet::Initializer';
has 'forget_bias' => (is => 'ro', isa => 'Num', required => 1);

method _init_weight(Str $name, AI::MXNet::NDArray $arr)
{
    $arr .= 0;
    # in the case of LSTMCell the forget gate is the second
    # gate of the 4 LSTM gates, we modify the according values.
    my $num_hidden = int($arr->shape->[0] / 4);
    $arr->slice([$num_hidden, 2*$num_hidden-1]) .= $self->forget_bias;
}

__PACKAGE__->register;

package AI::MXNet::FusedRNN;
use Mouse;
use JSON::PP;
extends 'AI::MXNet::Initializer';

=head1 NAME

    AI::MXNet::FusedRNN - Custom initializer for fused RNN cells.
=cut

=head1 DESCRIPTION

    Initializes parameters for fused rnn layer.

    Parameters
    ----------
    init : Initializer
        initializer applied to unpacked weights.
    All parameters below must be exactly the same as ones passed to the
    FusedRNNCell constructor.

    num_hidden : int
    num_layers : int
    mode : str
    bidirectional : bool
    forget_bias : float
=cut

has 'init'          => (is => 'rw', isa => 'Str|AI::MXNet::Initializer', required => 1);
has 'forget_bias'   => (is => 'ro', isa => 'Num', default => 1);
has [qw/num_hidden
       num_layers/] => (is => 'ro', isa => 'Int', required => 1);
has 'mode'          => (is => 'ro', isa => 'Str', required => 1);
has 'bidirectional' => (is => 'ro', isa => 'Bool', default => 0);

sub BUILD
{
    my $self = shift;
    if(not blessed $self->init)
    {
        my ($klass, $kwargs);
        eval {
            ($klass, $kwargs) = @{ decode_json($self->init) };
        };
        confess("FusedRNN failed to init $@") if $@;
        $self->init($self->get_init_registry->{ lc $klass }->new(%$kwargs));
    }
}

method _init_weight($name, $arr)
{
    my $cell = AI::MXNet::RNN::FusedCell->new(
        num_hidden    => $self->num_hidden,
        num_layers    => $self->num_layers,
        mode          => $self->mode,
        bidirectional => $self->bidirectional,
        forget_bias   => $self->forget_bias,
        prefix        => ''
    );

    my $args = $cell->unpack_weights({ parameters => $arr });
    for my $name (keys %{ $args })
    {
        my $desc = AI::MXNet::InitDesc->new(name => $name);
        # for lstm bias, we use a custom initializer
        # which adds a bias to the forget gate
        if($self->mode eq 'lstm' and $name =~ /f_bias$/)
        {
            $args->{$name} .= $self->forget_bias;
        }
        else
        {
            &{$self->init}($desc, $args->{$name});
        }
    }

    $arr .= $cell->pack_weights($args)->{parameters};
}

__PACKAGE__->register;

1;