AI-MXNet

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

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                ctx         => $self->_ctx,
                args        => \%new_arg_dict,
                args_grad   => \%new_grad_dict,
                grad_req    => $self->_grad_req,
                aux_states  => \%new_aux_dict,
                group2ctx   => $self->_group2ctx,
                shared_exec => $self
    );
}
 
=head2 debug_str
 
    A debug string about the internal execution plan.
 
    Returns
    -------
    debug_str : string
        Debug string of the executor.
=cut
 
method debug_str()
{
    return scalar(check_call(AI::MXNetCAPI::ExecutorPrint($self->handle)));
}
 
1;

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

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use AI::MXNet::Base;
 
extends 'https://metacpan.org/pod/AI::MXNet::DataIter">AI::MXNet::DataIter';
 
=head1 NAME
 
    AI::MXNet::MXDataIter - A data iterator pre-built in C++ layer of MXNet.
=cut
 
has 'handle'           => (is => 'ro', isa => 'DataIterHandle', required => 1);
has '_debug_skip_load' => (is => 'rw', isa => 'Int', default => 0);
has '_debug_at_begin'  => (is => 'rw', isa => 'Int', default => 0);
has 'data_name'        => (is => 'ro', isa => 'Str', default => 'data');
has 'label_name'       => (is => 'ro', isa => 'Str', default => 'softmax_label');
has [qw/first_batch
        provide_data
        provide_label
        batch_size/]   => (is => 'rw', init_arg => undef);
 
sub BUILD
{
    my $self = shift;

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

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        )
    ]);
    $self->batch_size($data->shape->[0]);
}
 
sub DEMOLISH
{
    check_call(AI::MXNetCAPI::DataIterFree(shift->handle));
}
 
=head2 debug_skip_load
 
    Set the iterator to simply return always first batch.
    Notes
    -----
    This can be used to test the speed of network without taking
    the loading delay into account.
=cut
 
method debug_skip_load()
{
    $self->_debug_skip_load(1);
    AI::MXNet::Logging->info('Set debug_skip_load to be true, will simply return first batch');
}
 
method reset()
{
    $self->_debug_at_begin(1);
    $self->first_batch(undef);
    check_call(AI::MXNetCAPI::DataIterBeforeFirst($self->handle));
}
 
method next()
{
    if($self->_debug_skip_load and not $self->_debug_at_begin)
    {
        return  AI::MXNet::DataBatch->new(
                    data  => [$self->getdata],
                    label => [$self->getlabel],
                    pad   => $self->getpad,
                    index => $self->getindex
        );
    }
    if(defined $self->first_batch)
    {
        my $batch = $self->first_batch;
        $self->first_batch(undef);
        return $batch
    }
    $self->_debug_at_begin(0);
    my $next_res =  check_call(AI::MXNetCAPI::DataIterNext($self->handle));
    if($next_res)
    {
        return  AI::MXNet::DataBatch->new(
                    data  => [$self->getdata],
                    label => [$self->getlabel],
                    pad   => $self->getpad,
                    index => $self->getindex
        );
    }

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

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my $batch_data  = AI::MXNet::NDArray->empty([$batch_size, $c, $h, $w]);
my $batch_label = AI::MXNet::NDArray->empty(@{$self->provide_label->[0]}[1]);
my $i = 0;
while ($i < $batch_size)
{
    my ($label, $s) = $self->next_sample;
    last if not defined $label;
    my $data = [AI::MXNet::Image->imdecode($s)];
    if(@{ $data->[0]->shape } == 0)
    {
        AI::MXNet::Logging->debug('Invalid image, skipping.');
        next;
    }
    for my $aug (@{ $self->aug_list })
    {
        $data = [map { @{ $aug->($_) } } @$data];
    }
    for my $d (@$data)
    {
        assert(($i < $batch_size), 'Batch size must be multiples of augmenter output length');
        $batch_data->at($i)  .= AI::MXNet::NDArray->transpose($d, { axes=>[2, 0, 1] });

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

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package AI::MXNet::Logging;
## TODO
use Mouse;
sub warning { shift; warn sprintf(shift, @_) . "\n" };
*debug   = *info = *warning;
sub get_logger { __PACKAGE__->new }
 
1;

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

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package AI::MXNet::Monitor;
use Mouse;
use AI::MXNet::Function::Parameters;
use AI::MXNet::Base;
 
=head1 NAME
 
    AI::MXNet::Monitor - Monitor outputs, weights, and gradients for debugging.
 
=head1 DESCRIPTION
 
    Monitor outputs, weights, and gradients for debugging.
 
    Parameters
    ----------
    interval : int
        Number of batches between printing.
    stat_func : function
        a function that computes statistics of tensors.
        Takes a NDArray and returns a NDArray. defaults to mean
        absolute value |x|/size(x).
    pattern : str

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

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        $self->step($self->step + 1);
}
 
=head2 toc
 
    End collecting for current batch and return results.
    Call after computation of current batch.
 
    Returns
    -------
    res : array ref of array refs with debug info
=cut
 
method toc()
{
    return [] unless $self->activated;
    for my $exe (@{ $self->exes })
    {
        $_->wait_to_read for @{ $exe->arg_arrays };
        $_->wait_to_read for @{ $exe->aux_arrays };
    }

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

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    if($complete)
    {
        return $arg_shapes, $out_shapes, $aux_shapes;
    }
    else
    {
        return (undef, undef, undef);
    }
}
 
=head2 debug_str
 
    The debug string.
 
    Returns
    -------
    debug_str : string
        Debug string of the symbol.
=cut
 
method debug_str()
{
    return scalar(check_call(AI::MXNetCAPI::SymbolPrint($self->handle)));
}
 
=head2 save
 
        Save the symbol into a 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.

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

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        }
    }
    return $dot;
}
 
package AI::MXNet::Visualization::PythonGraphviz;
use Mouse;
use AI::MXNet::Types;
has 'format' => (
    is => 'ro',
    isa => enum([qw/debug canon text ps hpgl pcl mif
                    pic gd gd2 gif jpeg png wbmp cmapx
                    imap vdx vrml vtx mp fig svg svgz
                    plain/]
    )
);
has 'graph' => (is => 'ro', isa => 'GraphViz');
 
method render($output=)
{
    my $method = 'as_' . $self->format;