Perl5 interface to MXNet (#5022)

* initial checkin. * Addressed code review issues. 1) Change lincense to Apache 2.0 2) Expanded tests 3) Made perl-package testable via Travis CI. * removed static swig file in favor of dynamically generating ones. * Reset changes to submodules. * small fix in order to get tests pass under Perl 5.22 on Ubuntu 16.04.1 LTS (Xenial Xerus) * 1) Fixed problems that prevented the interface to work on OSX 2) Removed tests that were dependent on random behavior, they were not reliable across different OS. * OSX build process cleanup. * Workaround for SIP (system integrity protection) that prevents DYLD_LIBRARY_PATH from working * 1) added visualization 2) simplified symbol interface a bit in order to make it closer to Python usage 3) miscellaneous cleanups * 1) added bucketing module 2) fixed few pod errors 3) added better Synopsis to main module.
apache · Feb 21, 2017 · 6a0db69 · 6a0db69
1 parent 2a7d6f2
commit 6a0db69
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diff --git a/.travis.yml b/.travis.yml
@@ -21,9 +21,19 @@ env:
 
   # TODO, R test, distributed test, clang, more g++ versions
 
-# matrix:
-#   exclude:
-#     - os: osx
+matrix:
+  include:
+    - os: linux
+      dist: trusty
+      env: TASK=perl_test
+    - os: osx
+      ## sudo is required because
+      ## prexexisting packages conflict
+      ## with new ones.
+      ## would be nice to have macports
+      ## on travis osx, it has all needed perl packages
+      sudo: required
+      env: TASK=perl_test
 #       env: TASK=julia JULIA_VER=0.4
 #     - os: linux
 #       env: TASK=build
@@ -57,6 +67,11 @@ addons:
       - python3-dev
       - python3-nose
       - graphviz
+      - libmouse-perl
+      - pdl
+      - cpanminus
+      - swig
+      - libgraphviz-perl
 
 before_install:
   - export NVCC_PREFIX=${HOME}

diff --git a/perl-package/.gitignore b/perl-package/.gitignore
@@ -0,0 +1 @@
+!*
diff --git a/perl-package/AI-MXNet/Changes b/perl-package/AI-MXNet/Changes
@@ -0,0 +1,5 @@
+Revision history for Perl extension AI::MXNet
+
+0.02  Tue Feb 14 07:28:11 PST 2017
+        - prepared for inclusion to the mxnet code repository.
+
diff --git a/perl-package/AI-MXNet/MANIFEST b/perl-package/AI-MXNet/MANIFEST
@@ -0,0 +1,46 @@
+MANIFEST
+Makefile.PL
+README
+Changes
+lib/AI/MXNet.pm
+lib/AI/MXNet/Base.pm
+lib/AI/MXNet/Callback.pm
+lib/AI/MXNet/Context.pm
+lib/AI/MXNet/Executor.pm
+lib/AI/MXNet/Executor/Group.pm
+lib/AI/MXNet/Function/Parameters.pm
+lib/AI/MXNet/IO.pm
+lib/AI/MXNet/Initializer.pm
+lib/AI/MXNet/KVStore.pm
+lib/AI/MXNet/KVStoreServer.pm
+lib/AI/MXNet/LRScheduler.pm
+lib/AI/MXNet/Logging.pm
+lib/AI/MXNet/Metric.pm
+lib/AI/MXNet/Module.pm
+lib/AI/MXNet/Module/Base.pm
+lib/AI/MXNet/Module/Bucketing.pm
+lib/AI/MXNet/Monitor.pm
+lib/AI/MXNet/NDArray.pm
+lib/AI/MXNet/NDArray/Base.pm
+lib/AI/MXNet/NDArray/Doc.pm
+lib/AI/MXNet/NDArray/Slice.pm
+lib/AI/MXNet/Optimizer.pm
+lib/AI/MXNet/Profiler.pm
+lib/AI/MXNet/Random.pm
+lib/AI/MXNet/Rtc.pm
+lib/AI/MXNet/Symbol.pm
+lib/AI/MXNet/Symbol/AttrScope.pm
+lib/AI/MXNet/Symbol/Base.pm
+lib/AI/MXNet/Symbol/Doc.pm
+lib/AI/MXNet/Symbol/NameManager.pm
+lib/AI/MXNet/TestUtils.pm
+lib/AI/MXNet/Types.pm
+lib/AI/MXNet/Util/Printable.pm
+lib/AI/MXNet/Visualization.pm
+t/AI-MXNet.t
+t/initializers.t
+t/io.t
+t/models.t
+t/optimizers.t
+t/test_conv.t
+t/test_viz.t
diff --git a/perl-package/AI-MXNet/META.yml b/perl-package/AI-MXNet/META.yml
@@ -0,0 +1,22 @@
+---
+abstract: 'Perl interface to MXNet machine learning library'
+author:
+  - 'Sergey Kolychev <sergeykolychev.github@gmail.com>'
+build_requires: {}
+configure_requires:
+  ExtUtils::MakeMaker: 6.30
+dynamic_config: 0
+generated_by: 'Dist::Zilla version 5.008, CPAN::Meta::Converter version 2.143240'
+license: perl
+meta-spec:
+  url: http://module-build.sourceforge.net/META-spec-v1.4.html
+  version: 1.4
+name: AI-MXNet
+requires:
+  AI::MXNetCAPI: 0.02
+  AI::NNVMCAPI: 0.02
+  Function::Parameters: 1.0705
+  Mouse: v2.1.0
+  PDL: 2.007
+  perl: v5.14.0
+version: 0.02
diff --git a/perl-package/AI-MXNet/Makefile.PL b/perl-package/AI-MXNet/Makefile.PL
@@ -0,0 +1,59 @@
+use strict;
+use warnings;
+
+use 5.014000;
+
+use ExtUtils::MakeMaker 6.30;
+
+
+
+my %WriteMakefileArgs = (
+  "ABSTRACT" => "Perl interface to MXNet machine learning library",
+  "AUTHOR" => "Sergey Kolychev <sergeykolychev.github\@gmail.com>",
+  "BUILD_REQUIRES" => {},
+  "CONFIGURE_REQUIRES" => {
+    "ExtUtils::MakeMaker" => "6.30"
+  },
+  "DISTNAME" => "AI-MXNet",
+  "EXE_FILES" => [],
+  "LICENSE" => "apache_2_0",
+  "NAME" => "AI::MXNet",
+  "PREREQ_PM" => {
+    "AI::MXNetCAPI" => "0.02",
+    "AI::NNVMCAPI" => "0.02",
+    "Function::Parameters" => "1.0705",
+    "Mouse" => "2.1.0",
+    "PDL" => "2.007",
+    "GraphViz" => "2.14"
+  },
+  "TEST_REQUIRES" => {},
+  "VERSION" => "0.02",
+  "test" => {
+    "TESTS" => "t/*.t"
+  }
+);
+
+
+my %FallbackPrereqs = (
+  "AI::MXNetCAPI" => "0.02",
+  "AI::NNVMCAPI" => "0.02",
+  "Function::Parameters" => "1.0705",
+  "Mouse" => "2.1.0",
+  "PDL" => "2.007",
+  "GraphViz" => "2.14"
+);
+
+
+unless ( eval { ExtUtils::MakeMaker->VERSION(6.63_03) } ) {
+  delete $WriteMakefileArgs{TEST_REQUIRES};
+  delete $WriteMakefileArgs{BUILD_REQUIRES};
+  $WriteMakefileArgs{PREREQ_PM} = \%FallbackPrereqs;
+}
+
+delete $WriteMakefileArgs{CONFIGURE_REQUIRES}
+  unless eval { ExtUtils::MakeMaker->VERSION(6.52) };
+
+WriteMakefile(%WriteMakefileArgs);
+
+
+
diff --git a/perl-package/AI-MXNet/README b/perl-package/AI-MXNet/README
@@ -0,0 +1,11 @@
+
+
+This archive contains the distribution AI-MXNet,
+version 0.02:
+
+  Perl interface to MXNet machine learning library
+
+Copyright (C) 2017 by Sergey Kolychev <sergeykolychev.github@gmail.com>
+
+This library is licensed under Apache 2.0 license https://www.apache.org/licenses/LICENSE-2.0
+
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet.pm b/perl-package/AI-MXNet/lib/AI/MXNet.pm
@@ -0,0 +1,154 @@
+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::Visualization;
+our $VERSION = '0.02';
+
+sub import
+{
+    my ($class, $short_name) = @_;
+    if($short_name)
+    {
+        $short_name =~ s/[^\w:]//g;
+        if(length $short_name)
+        {
+            my $short_name_package =<<"EOP";
+            package $short_name;
+            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 cpu { AI::MXNet::Context->cpu(\$_[1]//0) }
+            sub gpu { AI::MXNet::Context->gpu(\$_[1]//0) }
+            sub kv { 'AI::MXNet::KVStore' }
+            sub io { 'AI::MXNet::IO' }
+            sub metric { 'AI::MXNet::Metric' }
+            sub mod { 'AI::MXNet::Module' }
+            sub viz { 'AI::MXNet::Visualization' }
+            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;
+    use AI::MXNet qw(mx);
+    use AI::MXNet::TestUtils qw(GetMNIST_ubyte);
+    use Test::More tests => 1;
+
+    # symbol net
+    my $batch_size = 100;
+
+    ### model
+    my $data = mx->symbol->Variable('data');
+    my $conv1= mx->symbol->Convolution(data => $data, name => 'conv1', num_filter => 32, kernel => [3,3], stride => [2,2]);
+    my $bn1  = mx->symbol->BatchNorm(data => $conv1, name => "bn1");
+    my $act1 = mx->symbol->Activation(data => $bn1, name => 'relu1', act_type => "relu");
+    my $mp1  = mx->symbol->Pooling(data => $act1, name => 'mp1', kernel => [2,2], stride =>[2,2], pool_type=>'max');
+
+    my $conv2= mx->symbol->Convolution(data => $mp1, name => 'conv2', num_filter => 32, kernel=>[3,3], stride=>[2,2]);
+    my $bn2  = mx->symbol->BatchNorm(data => $conv2, name=>"bn2");
+    my $act2 = mx->symbol->Activation(data => $bn2, name=>'relu2', act_type=>"relu");
+    my $mp2  = mx->symbol->Pooling(data => $act2, name => 'mp2', kernel=>[2,2], stride=>[2,2], pool_type=>'max');
+
+
+    my $fl   = mx->symbol->Flatten(data => $mp2, name=>"flatten");
+    my $fc1  = mx->symbol->FullyConnected(data => $fl,  name=>"fc1", num_hidden=>30);
+    my $act3 = mx->symbol->Activation(data => $fc1, name=>'relu3', act_type=>"relu");
+    my $fc2  = mx->symbol->FullyConnected(data => $act3, name=>'fc2', num_hidden=>10);
+    my $softmax = mx->symbol->SoftmaxOutput(data => $fc2, name => 'softmax');
+
+    # check data
+    GetMNIST_ubyte();
+
+    my $train_dataiter = mx->io->MNISTIter({
+        image=>"data/train-images-idx3-ubyte",
+        label=>"data/train-labels-idx1-ubyte",
+        data_shape=>[1, 28, 28],
+        batch_size=>$batch_size, shuffle=>1, flat=>0, silent=>0, seed=>10});
+    my $val_dataiter = mx->io->MNISTIter({
+        image=>"data/t10k-images-idx3-ubyte",
+        label=>"data/t10k-labels-idx1-ubyte",
+        data_shape=>[1, 28, 28],
+        batch_size=>$batch_size, shuffle=>1, flat=>0, silent=>0});
+
+    my $n_epoch = 1;
+    my $mod = mx->mod->new(symbol => $softmax);
+    $mod->fit(
+        $train_dataiter,
+        eval_data => $val_dataiter,
+        optimizer_params=>{learning_rate=>0.01, momentum=> 0.9},
+        num_epoch=>$n_epoch
+    );
+    my $res = $mod->score($val_dataiter, mx->metric->create('acc'));
+    ok($res->{accuracy} > 0.8);
+
+=head1 DESCRIPTION
+
+    Perl interface to MXNet machine learning library.
+
+=head1 BUGS AND INCOMPATIBILITIES
+
+Parity with Python inteface is not yet achieved.
+Pod mostly contains Python documentation taken as is.
+This is WIP.
+
+=head1 SEE ALSO
+
+http://mxnet.io/
+https://github.com/sergeykolychev/mxnet/tree/master/perl-package
+
+=head1 AUTHOR
+
+Sergey Kolychev, <sergeykolychev.github@gmail.com>
+
+=head1 COPYRIGHT & LICENSE
+
+Copyright (C) 2017 by Sergey Kolychev <sergeykolychev.github@gmail.com>
+
+This library is licensed under Apache 2.0 license https://www.apache.org/licenses/LICENSE-2.0
+
+=cut