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

    Carp::confess("data must not be empty or allow_empty set to true value")
        if(ref($data) eq 'ARRAY' and not @{ $data } and not $allow_empty);

    my @ret;
    if(ref($data) eq 'ARRAY')
    {
        if(@{ $data } == 1)
        {
            @ret = ([$default_name, $data->[0]]);
        }
        else
        {
            my $i = -1;
            @ret = map { $i++; ["_${i}_$default_name", $_] } @{ $data };
        }
    }
    if(ref($data) eq 'HASH')
    {
        while(my ($k, $v) = each %{ $data })
        {
            push @ret, [$k, $v];
        }
    }
    for my $d (@ret)
    {
        if(not (blessed $d->[1] and $d->[1]->isa('AI::MXNet::NDArray')))
        {
            $d->[1] = AI::MXNet::NDArray->array($d->[1]);
        }
    }
    return \@ret;
}

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

package AI::MXNet::DataDesc;
use Mouse;
use overload '""'  => \&stringify,
             '@{}' => \&to_nameshape;
has 'name'   => (is => 'ro', isa => "Str",   required => 1);
has 'shape'  => (is => 'ro', isa => "Shape", required => 1);
has 'dtype'  => (is => 'ro', isa => "Dtype", default => 'float32');
has 'layout' => (is => 'ro', isa => "Str",   default => 'NCHW');

around BUILDARGS => sub {
    my $orig  = shift;
    my $class = shift;
    if(@_ >= 2 and ref $_[1] eq 'ARRAY')
    {
        my $name  = shift;
        my $shape = shift;
        return $class->$orig(name => $name, shape => $shape, @_);
    }
    return $class->$orig(@_);
};

method stringify($other=, $reverse=)
{
    sprintf(
        "DataDesc[%s,%s,%s,%s]",
        $self->name,
        join('x', @{ $self->shape }),
        $self->dtype,
        $self->layout
    );
}

method to_nameshape($other=, $reverse=)
{
    [$self->name, $self->shape];
}

=head1 NAME

    AI::MXNet::DataDesc - A container class for describing the data layout.
=cut

=head2 get_batch_axis

    Get the dimension that corresponds to the batch size.

    Parameters
    ----------
    layout : str
        layout string. For example, "NCHW".

    Returns
    -------
    An axis indicating the batch_size dimension. When data-parallelism is
    used, the data will be automatically split and concatenate along the batch_size
    dimension. Axis can be -1, which means the whole array will be copied for each
    data-parallelism device.
=cut

method get_batch_axis(Str|Undef $layout)
{
    return 0 unless defined $layout;
    return index($layout, 'N');
}

=head2 get_list

    Coverts the input to an array ref AI::MXNet::DataDesc objects.

    Parameters
    ----------
    $shapes : HashRef[Shape]
    $types= :  Maybe[HashRef[Dtype]]
=cut

method get_list(HashRef[Shape] $shapes, Maybe[HashRef[Dtype]] $types=)
{
    $types //= {};
    return [
        map {
            AI::MXNet::DataDesc->new(
                name  => $_,
                shape => $shapes->{$_},
                (exists $types->{$_} ? (type => $types->{$_}) : ())