AI-MXNet

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

    my $class = shift;
    return $class->$orig(name => $_[0]) if @_ == 1;
    return $class->$orig(@_);
};

# Base class for Initializers
package AI::MXNet::Initializer;
use Mouse;
use AI::MXNet::Base qw(:DEFAULT pzeros pceil);
use AI::MXNet::NDArray;
use JSON::PP;
use overload "&{}" => sub { my $self = shift; sub { $self->call(@_) } },
             '""'  => sub {
                my $self = shift;
                my ($name) = ref($self) =~ /::(\w+)$/;
                encode_json(
                    [lc $name,
                        $self->kwargs//{ map { $_ => "".$self->$_ } $self->meta->get_attribute_list }
                ]);
             },
             fallback => 1;

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

    # 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.

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

}

method STORABLE_freeze($cloning)
{
    return $self->tojson();
}

method STORABLE_thaw($cloning, $json)
{
    my $handle = check_call(
        AI::MXNetCAPI::SymbolCreateFromJSON(
            $json
        )
    );
    $self->handle($handle);
}

method stringify($other=, $reverse=)
{
    my $name = $self->name;
    sprintf("<%s %s>", ref($self), $name ? $name : 'Grouped');

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

        load : Used to load symbol from file.
=cut

method save(Str $fname)
{
    check_call(AI::MXNetCAPI::SymbolSaveToFile($self->handle, $fname));
}

=head2 tojson

        Save the symbol into a JSON string.

        See Also
        --------
        load_json : Used to load symbol from JSON string.
=cut

method tojson()
{
    return scalar(check_call(AI::MXNetCAPI::SymbolSaveToJSON($self->handle)));
}

method _get_ndarray_inputs(
    Str                                                      $arg_key,
    HashRef[AI::MXNet::NDArray]|ArrayRef[AI::MXNet::NDArray] $args,
    ArrayRef[Str]                                            $arg_names,
    Bool                                                     $allow_missing=0
)
{
    my ($arg_handles, $arg_arrays) = ([], []);

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

method Group(ArrayRef[AI::MXNet::Symbol] $symbols)
{
    my @handles = map { $_->handle } @{ $symbols };
    my $handle = check_call(AI::MXNetCAPI::SymbolCreateGroup(scalar(@handles), \@handles));
    return __PACKAGE__->new(handle => $handle);
}

=head2 load

    Load symbol from a JSON file.

    You can also use Storable to do the job if you only work with Perl.
    The advantage of load/save is the file is language agnostic.
    This means the file saved using save can be loaded by other language binding of mxnet.
    You also get the benefit being able to directly load/save from cloud storage(S3, HDFS)

    Parameters
    ----------
    fname : str
        The name of the file, examples:

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

    sym : Symbol
        The loaded symbol.

    See Also
    --------
    AI::MXNet::Symbol->tojson : Used to save symbol into json string.
=cut

method load_json(Str $json)
{
    my $handle = check_call(AI::MXNetCAPI::SymbolCreateFromJSON($json));
    return __PACKAGE__->new(handle => $handle);
}

method zeros(Shape :$shape, Dtype :$dtype='float32', Maybe[Str] :$name=, Maybe[Str] :$__layout__=)
{
    return __PACKAGE__->_zeros({ shape => $shape, dtype => $dtype, name => $name, ($__layout__ ? (__layout__ => $__layout__) : ()) });
}

method ones(Shape :$shape, Dtype :$dtype='float32', Maybe[Str] :$name=, Maybe[Str] :$__layout__=)
{

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

package AI::MXNet::Visualization;
use strict;
use warnings;
use AI::MXNet::Base;
use AI::MXNet::Function::Parameters;
use JSON::PP;

=encoding UTF-8

=head1 NAME

    AI::MXNet::Vizualization - Vizualization support for Perl interface to MXNet machine learning library

=head1 SYNOPSIS

    use strict;