AI-MXNet
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lib/AI/MXNet.pm view on Meta::CPAN
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
lib/AI/MXNet/Module/Bucketing.pm view on Meta::CPAN
package AI::MXNet::Module::Bucketing;
use Mouse;
use AI::MXNet::Function::Parameters;
use AI::MXNet::Base;
=encoding UTF-8
=head1 NAME
AI::MXNet::Module::Bucketing
=head1 SYNOPSIS
my $buckets = [10, 20, 30, 40, 50, 60];
my $start_label = 1;
my $invalid_label = 0;
lib/AI/MXNet/NDArray.pm view on Meta::CPAN
=cut
method as_in_context(AI::MXNet::Context $context)
{
return $self if $self->context == $context;
return $self->copyto($context);
}
=head2 onehot_encode
One hot encoding indices into matrix out.
Parameters
----------
indices: NDArray
An NDArray containing indices of the categorical features.
out: NDArray
The result of the encoding.
Returns
-------
$out: NDArray
=cut
method onehot_encode(AI::MXNet::NDArray $indices, AI::MXNet::NDArray $out)
{
return __PACKAGE__->_onehot_encode($indices, $out, { out => $out });
}
lib/AI/MXNet/RNN.pm view on Meta::CPAN
package AI::MXNet::RNN;
use strict;
use warnings;
use AI::MXNet::Function::Parameters;
use AI::MXNet::RNN::IO;
use AI::MXNet::RNN::Cell;
use List::Util qw(max);
=encoding UTF-8
=head1 NAME
AI::MXNet::RNN - Functions for constructing recurrent neural networks.
=cut
=head1 SYNOPSIS
=head1 DESCRIPTION
lib/AI/MXNet/RNN/IO.pm view on Meta::CPAN
package AI::MXNet::RNN::IO;
use strict;
use warnings;
use AI::MXNet::Base;
use AI::MXNet::Function::Parameters;
=encoding UTF-8
=head1 NAME
AI::MXNet::RNN::IO - Functions for constructing recurrent neural networks.
=cut
=head1 DESCRIPTION
Functions for constructing recurrent neural networks.
=cut
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