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lib/AI/MXNet.pm  view on Meta::CPAN

package AI::MXNet;
use v5.14.0;
use strict;
use warnings;
use AI::MXNet::Base;
use AI::MXNet::Callback;
use AI::MXNet::NDArray;
use AI::MXNet::Symbol;
use AI::MXNet::Executor;
use AI::MXNet::Executor::Group;
use AI::MXNet::Rtc;
use AI::MXNet::Random;
use AI::MXNet::Initializer;
use AI::MXNet::Optimizer;
use AI::MXNet::KVStore;
use AI::MXNet::KVStoreServer;
use AI::MXNet::IO;
use AI::MXNet::Metric;
use AI::MXNet::LRScheduler;
use AI::MXNet::Monitor;
use AI::MXNet::Profiler;
use AI::MXNet::Module::Base;
use AI::MXNet::Module;
use AI::MXNet::Module::Bucketing;
use AI::MXNet::RNN;
use AI::MXNet::Visualization;
use AI::MXNet::RecordIO;
use AI::MXNet::Image;
use AI::MXNet::Contrib;
use AI::MXNet::Contrib::AutoGrad;
use AI::MXNet::CachedOp;
our $VERSION = '1.0102';

sub import
{
    my ($class, $short_name) = @_;
    if($short_name)
    {
        $short_name =~ s/[^\w:]//g;
        if(length $short_name)
        {
            my $short_name_package =<<"EOP";
            package $short_name;
            no warnings 'redefine';
            sub nd { 'AI::MXNet::NDArray' }
            sub sym { 'AI::MXNet::Symbol' }
            sub symbol { 'AI::MXNet::Symbol' }
            sub init { 'AI::MXNet::Initializer' }
            sub initializer { 'AI::MXNet::Initializer' }
            sub optimizer { 'AI::MXNet::Optimizer' }
            sub opt { 'AI::MXNet::Optimizer' }
            sub rnd { 'AI::MXNet::Random' }
            sub random { 'AI::MXNet::Random' }
            sub Context { shift; AI::MXNet::Context->new(\@_) }
            sub cpu { AI::MXNet::Context->cpu(\$_[1]//0) }
            sub gpu { AI::MXNet::Context->gpu(\$_[1]//0) }
            sub kv { 'AI::MXNet::KVStore' }
            sub recordio { 'AI::MXNet::RecordIO' }
            sub io { 'AI::MXNet::IO' }
            sub metric { 'AI::MXNet::Metric' }
            sub mod { 'AI::MXNet::Module' }
            sub mon { 'AI::MXNet::Monitor' }
            sub viz { 'AI::MXNet::Visualization' }
            sub rnn { 'AI::MXNet::RNN' }
            sub callback { 'AI::MXNet::Callback' }
            sub img { 'AI::MXNet::Image' }
            sub contrib { 'AI::MXNet::Contrib' }
            sub name { '$short_name' }
            sub AttrScope { shift; AI::MXNet::Symbol::AttrScope->new(\@_) }
            *AI::MXNet::Symbol::AttrScope::current = sub { \$${short_name}::AttrScope; };
            \$${short_name}::AttrScope = AI::MXNet::Symbol::AttrScope->new;
            sub Prefix { AI::MXNet::Symbol::Prefix->new(prefix => \$_[1]) }
            *AI::MXNet::Symbol::NameManager::current = sub { \$${short_name}::NameManager; };
            \$${short_name}::NameManager = AI::MXNet::Symbol::NameManager->new;
            *AI::MXNet::Context::current_ctx = sub { \$${short_name}::Context; };
            \$${short_name}::Context = AI::MXNet::Context->new(device_type => 'cpu', device_id => 0);
            1;
EOP
            eval $short_name_package;
        }
    }
}

1;
__END__

=encoding UTF-8

=head1 NAME

AI::MXNet - Perl interface to MXNet machine learning library

=head1 SYNOPSIS

    ## Convolutional NN for recognizing hand-written digits in MNIST dataset
    ## It's considered "Hello, World" for Neural Networks
    ## For more info about the MNIST problem please refer to http://neuralnetworksanddeeplearning.com/chap1.html

    use strict;
    use warnings;