sergeykolychev closed pull request #12739: [MXNET-1026] [Perl] Sync with recent
changes in Python's API
URL: https://github.com/apache/incubator-mxnet/pull/12739
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):
diff --git a/docs/install/validate_mxnet.md b/docs/install/validate_mxnet.md
index a4cf5446f60..dfe8d063f60 100644
--- a/docs/install/validate_mxnet.md
+++ b/docs/install/validate_mxnet.md
@@ -137,8 +137,25 @@ Please contribute an example!
### Perl
-Please contribute an example!
+Start the pdl2 terminal.
+
+```bash
+$ pdl2
+```
+Run a short *MXNet* Perl program to create a 2X3 matrix of ones, multiply each
element in the matrix by 2 followed by adding 1. We expect the output to be a
2X3 matrix with all elements being 3.
+
+```perl
+pdl> use AI::MXNet qw(mx)
+pdl> $a = mx->nd->ones([2, 3])
+pdl> $b = $a * 2 + 1
+pdl> print $b->aspdl
+
+[
+ [3 3 3]
+ [3 3 3]
+]
+```
### R
diff --git a/perl-package/AI-MXNet-Gluon-Contrib/Changes
b/perl-package/AI-MXNet-Gluon-Contrib/Changes
index 81e55aa753a..f91ea2045ed 100644
--- a/perl-package/AI-MXNet-Gluon-Contrib/Changes
+++ b/perl-package/AI-MXNet-Gluon-Contrib/Changes
@@ -1,5 +1,8 @@
Revision history for Perl extension AI::MXNet::Gluon::Contrib
+1.33 Thu Oct 4 13:25:56 PDT 2018
+ - Fixed kwalitee issues.
+
1.32 Sun Jul 15 12:12:15 PDT 2018
- Missing POD fixes.
diff --git a/perl-package/AI-MXNet-Gluon-Contrib/META.json
b/perl-package/AI-MXNet-Gluon-Contrib/META.json
index ec65bb01348..910c7d4d9a1 100644
--- a/perl-package/AI-MXNet-Gluon-Contrib/META.json
+++ b/perl-package/AI-MXNet-Gluon-Contrib/META.json
@@ -30,7 +30,7 @@
},
"runtime" : {
"requires" : {
- "AI::MXNet" : "1.31",
+ "AI::MXNet" : "1.33"
}
},
"test" : {
@@ -38,5 +38,5 @@
}
},
"release_status" : "stable",
- "version" : "1.32"
+ "version" : "1.33"
}
diff --git a/perl-package/AI-MXNet-Gluon-Contrib/META.yml
b/perl-package/AI-MXNet-Gluon-Contrib/META.yml
index aaa194debae..d175c2bd141 100644
--- a/perl-package/AI-MXNet-Gluon-Contrib/META.yml
+++ b/perl-package/AI-MXNet-Gluon-Contrib/META.yml
@@ -18,4 +18,4 @@ no_index:
- inc
requires:
AI::MXNet: '1.31'
-version: '1.32'
+version: '1.33'
diff --git a/perl-package/AI-MXNet-Gluon-Contrib/Makefile.PL
b/perl-package/AI-MXNet-Gluon-Contrib/Makefile.PL
index 6c58d6ea866..a6ff95e8bcc 100644
--- a/perl-package/AI-MXNet-Gluon-Contrib/Makefile.PL
+++ b/perl-package/AI-MXNet-Gluon-Contrib/Makefile.PL
@@ -39,7 +39,7 @@ my %WriteMakefileArgs = (
"AI::MXNet" => "1.31",
},
"TEST_REQUIRES" => {},
- "VERSION" => "1.32",
+ "VERSION" => "1.33",
"test" => {
"TESTS" => "t/*.t"
}
diff --git a/perl-package/AI-MXNet-Gluon-Contrib/README
b/perl-package/AI-MXNet-Gluon-Contrib/README
index 6c0efcc3c89..f0301d168f7 100644
--- a/perl-package/AI-MXNet-Gluon-Contrib/README
+++ b/perl-package/AI-MXNet-Gluon-Contrib/README
@@ -1,5 +1,5 @@
This archive contains the distribution AI-MXNet-Gluon-Contrib,
-version 1.32:
+version 1.33:
Perl interface to MXNet Gluon Contib modules, a collection of supplemental
Gluon blocks.
diff --git a/perl-package/AI-MXNet-Gluon-Contrib/lib/AI/MXNet/Gluon/Contrib.pm
b/perl-package/AI-MXNet-Gluon-Contrib/lib/AI/MXNet/Gluon/Contrib.pm
index 029bc4b65a6..807dfc87200 100644
--- a/perl-package/AI-MXNet-Gluon-Contrib/lib/AI/MXNet/Gluon/Contrib.pm
+++ b/perl-package/AI-MXNet-Gluon-Contrib/lib/AI/MXNet/Gluon/Contrib.pm
@@ -20,10 +20,20 @@ use strict;
use warnings;
use AI::MXNet;
use AI::MXNet::Gluon::Contrib::NN::BasicLayers;
-our $VERSION = '1.32';
+our $VERSION = '1.33';
=head1 NAME
AI::MXNet::Gluon::Contrib - A collection of supplemental Gluon blocks.
=cut
-1;
\ No newline at end of file
+1;
+
+=head1 AUTHOR
+
+ Sergey Kolychev, <[email protected]>
+
+=head1 COPYRIGHT & LICENSE
+
+ This library is licensed under Apache 2.0 license
L<https://www.apache.org/licenses/LICENSE-2.0>
+
+=cut
diff --git a/perl-package/AI-MXNet-Gluon-ModelZoo/Changes
b/perl-package/AI-MXNet-Gluon-ModelZoo/Changes
index 377dff5be8d..61018181c9a 100644
--- a/perl-package/AI-MXNet-Gluon-ModelZoo/Changes
+++ b/perl-package/AI-MXNet-Gluon-ModelZoo/Changes
@@ -1,5 +1,8 @@
Revision history for Perl extension AI::MXNet::Gluon::ModelZoo
+1.33 Thu Oct 4 13:25:56 PDT 2018
+ - Fixed kwalitee issues.
+
1.32 Sun Aug 5 14:25:31 PDT 2018
- Updated vgg16/19 models
diff --git a/perl-package/AI-MXNet-Gluon-ModelZoo/META.json
b/perl-package/AI-MXNet-Gluon-ModelZoo/META.json
index 9ea969e9f5f..2ce7dddba36 100644
--- a/perl-package/AI-MXNet-Gluon-ModelZoo/META.json
+++ b/perl-package/AI-MXNet-Gluon-ModelZoo/META.json
@@ -31,7 +31,8 @@
"runtime" : {
"requires" : {
"AI::MXNet" : "1.31",
- "AI::MXNet::Gluon::Contrib" : "1.3"
+ "AI::MXNet::Gluon::Contrib" : "1.3",
+ "IO::Uncompress::Unzip" : "0"
}
},
"test" : {
@@ -39,5 +40,5 @@
}
},
"release_status" : "stable",
- "version" : "1.32"
+ "version" : "1.33"
}
diff --git a/perl-package/AI-MXNet-Gluon-ModelZoo/META.yml
b/perl-package/AI-MXNet-Gluon-ModelZoo/META.yml
index a04484a898a..d6d9652a6dd 100644
--- a/perl-package/AI-MXNet-Gluon-ModelZoo/META.yml
+++ b/perl-package/AI-MXNet-Gluon-ModelZoo/META.yml
@@ -19,4 +19,5 @@ no_index:
requires:
AI::MXNet: '1.31'
AI::MXNet::Gluon::Contrib: '1.3'
-version: '1.32'
+ IO::Uncompress::Unzip: '0'
+version: '1.33'
diff --git a/perl-package/AI-MXNet-Gluon-ModelZoo/Makefile.PL
b/perl-package/AI-MXNet-Gluon-ModelZoo/Makefile.PL
index d15dfce99b8..de8b1acc5e2 100644
--- a/perl-package/AI-MXNet-Gluon-ModelZoo/Makefile.PL
+++ b/perl-package/AI-MXNet-Gluon-ModelZoo/Makefile.PL
@@ -37,10 +37,11 @@ my %WriteMakefileArgs = (
"NAME" => "AI::MXNet::Gluon::ModelZoo",
"PREREQ_PM" => {
"AI::MXNet" => "1.31",
- "AI::MXNet::Gluon::Contrib" => "1.3"
+ "AI::MXNet::Gluon::Contrib" => "1.3",
+ "IO::Uncompress::Unzip" => "0"
},
"TEST_REQUIRES" => {},
- "VERSION" => "1.32",
+ "VERSION" => "1.33",
"test" => {
"TESTS" => "t/*.t"
}
@@ -49,7 +50,8 @@ my %WriteMakefileArgs = (
my %FallbackPrereqs = (
"AI::MXNet" => "1.31",
- "AI::MXNet::Gluon::Contrib" => "1.3"
+ "AI::MXNet::Gluon::Contrib" => "1.3",
+ "IO::Uncompress::Unzip" => "0"
);
diff --git a/perl-package/AI-MXNet-Gluon-ModelZoo/README
b/perl-package/AI-MXNet-Gluon-ModelZoo/README
index 6b8e04b971e..e39ae4b69be 100644
--- a/perl-package/AI-MXNet-Gluon-ModelZoo/README
+++ b/perl-package/AI-MXNet-Gluon-ModelZoo/README
@@ -1,5 +1,5 @@
This archive contains the distribution AI-MXNet-Gluon-ModelZoo,
-version 1.32:
+version 1.33:
Perl interface to MXNet Gluon ModelZoo, a collection of pretrained machine
learning models for computer vision.
diff --git
a/perl-package/AI-MXNet-Gluon-ModelZoo/lib/AI/MXNet/Gluon/ModelZoo.pm
b/perl-package/AI-MXNet-Gluon-ModelZoo/lib/AI/MXNet/Gluon/ModelZoo.pm
index c9e6e775304..e9cbec02a44 100644
--- a/perl-package/AI-MXNet-Gluon-ModelZoo/lib/AI/MXNet/Gluon/ModelZoo.pm
+++ b/perl-package/AI-MXNet-Gluon-ModelZoo/lib/AI/MXNet/Gluon/ModelZoo.pm
@@ -26,7 +26,7 @@ use AI::MXNet::Gluon::ModelZoo::Vision;
use Exporter;
use base qw(Exporter);
@AI::MXNet::Gluon::ModelZoo::EXPORT_OK = qw(get_model);
-our $VERSION = '1.32';
+our $VERSION = '1.33';
=head1 NAME
@@ -130,3 +130,13 @@ sub get_model
sub vision { 'AI::MXNet::Gluon::ModelZoo::Vision' }
1;
+
+=head1 AUTHOR
+
+ Sergey Kolychev, <[email protected]>
+
+=head1 COPYRIGHT & LICENSE
+
+ This library is licensed under Apache 2.0 license
L<https://www.apache.org/licenses/LICENSE-2.0>
+
+=cut
diff --git a/perl-package/AI-MXNet/Changes b/perl-package/AI-MXNet/Changes
index 8b9463ee84e..8bd43f3be20 100644
--- a/perl-package/AI-MXNet/Changes
+++ b/perl-package/AI-MXNet/Changes
@@ -1,5 +1,17 @@
Revision history for Perl extension AI::MXNet
+1.33 Thu Oct 4 13:25:56 PDT 2018
+ - Added randn function.
+ - Internal SELU function on C++ layer.
+ - Predict now accepts ndarray as well.
+ - Gluon: Only warn when the blocks are unregistered.
+ - Gluon: Better sparse support.
+ - Gluon: Improved block summary.
+ - Added validation docs for MXNet installation for Perl.
+ - Flexible perl env for examples.
+ - Gluon: Custom dtypes for the symbol block
+ - Separate eval metric for the epoch level.
+
1.32 Sun Aug 5 14:25:31 PDT 2018
- Several new metric classes
- Expanded documentation
diff --git a/perl-package/AI-MXNet/META.json b/perl-package/AI-MXNet/META.json
index 7d0ab96c059..bbbea734ccf 100644
--- a/perl-package/AI-MXNet/META.json
+++ b/perl-package/AI-MXNet/META.json
@@ -30,7 +30,7 @@
},
"runtime" : {
"requires" : {
- "AI::MXNetCAPI" : "1.32",
+ "AI::MXNetCAPI" : "1.33",
"AI::NNVMCAPI" : "1.3",
"Function::Parameters" : "1.0705",
"Hash::Ordered" : "0.012",
@@ -45,5 +45,5 @@
}
},
"release_status" : "stable",
- "version" : "1.32"
+ "version" : "1.33"
}
diff --git a/perl-package/AI-MXNet/META.yml b/perl-package/AI-MXNet/META.yml
index ee5d677a813..e604b7cd0da 100644
--- a/perl-package/AI-MXNet/META.yml
+++ b/perl-package/AI-MXNet/META.yml
@@ -17,7 +17,7 @@ no_index:
- t
- inc
requires:
- AI::MXNetCAPI: '1.32'
+ AI::MXNetCAPI: '1.33'
AI::NNVMCAPI: '1.3'
Function::Parameters: '1.0705'
Hash::Ordered: '0.012'
@@ -25,4 +25,4 @@ requires:
Mouse: v2.1.0
PDL: '2.007'
PDL::CCS: '1.23.4'
-version: '1.32'
+version: '1.33'
diff --git a/perl-package/AI-MXNet/Makefile.PL
b/perl-package/AI-MXNet/Makefile.PL
index 59036d905f8..6d70b21344c 100644
--- a/perl-package/AI-MXNet/Makefile.PL
+++ b/perl-package/AI-MXNet/Makefile.PL
@@ -36,7 +36,7 @@ my %WriteMakefileArgs = (
"LICENSE" => "apache_2_0",
"NAME" => "AI::MXNet",
"PREREQ_PM" => {
- "AI::MXNetCAPI" => "1.3",
+ "AI::MXNetCAPI" => "1.33",
"AI::NNVMCAPI" => "1.3",
"Function::Parameters" => "1.0705",
"Hash::Ordered" => "0.012",
@@ -46,7 +46,7 @@ my %WriteMakefileArgs = (
"GraphViz" => "2.14"
},
"TEST_REQUIRES" => {},
- "VERSION" => "1.32",
+ "VERSION" => "1.33",
"test" => {
"TESTS" => "t/*.t"
}
@@ -54,7 +54,7 @@ my %WriteMakefileArgs = (
my %FallbackPrereqs = (
- "AI::MXNetCAPI" => "1.3",
+ "AI::MXNetCAPI" => "1.33",
"AI::NNVMCAPI" => "1.3",
"Function::Parameters" => "1.0705",
"Hash::Ordered" => "0.012",
diff --git a/perl-package/AI-MXNet/README b/perl-package/AI-MXNet/README
index 2f1010a43f9..f370db3804e 100644
--- a/perl-package/AI-MXNet/README
+++ b/perl-package/AI-MXNet/README
@@ -1,5 +1,5 @@
This archive contains the distribution AI-MXNet,
-version 1.32:
+version 1.33:
Perl interface to MXNet machine learning library
diff --git a/perl-package/AI-MXNet/examples/calculator.pl
b/perl-package/AI-MXNet/examples/calculator.pl
index aadc7cd2641..0350536c730 100755
--- a/perl-package/AI-MXNet/examples/calculator.pl
+++ b/perl-package/AI-MXNet/examples/calculator.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/examples/char_lstm.pl
b/perl-package/AI-MXNet/examples/char_lstm.pl
index 1e9c385c95f..a8bf7259979 100755
--- a/perl-package/AI-MXNet/examples/char_lstm.pl
+++ b/perl-package/AI-MXNet/examples/char_lstm.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/examples/cudnn_lstm_bucketing.pl
b/perl-package/AI-MXNet/examples/cudnn_lstm_bucketing.pl
index 326e57c5a6c..53200f3095c 100755
--- a/perl-package/AI-MXNet/examples/cudnn_lstm_bucketing.pl
+++ b/perl-package/AI-MXNet/examples/cudnn_lstm_bucketing.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/examples/gluon/dcgan.pl
b/perl-package/AI-MXNet/examples/gluon/dcgan.pl
index 2bdc56149d7..dd5294763cb 100755
--- a/perl-package/AI-MXNet/examples/gluon/dcgan.pl
+++ b/perl-package/AI-MXNet/examples/gluon/dcgan.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
diff --git a/perl-package/AI-MXNet/examples/gluon/mnist.pl
b/perl-package/AI-MXNet/examples/gluon/mnist.pl
index 5492e7e98f0..1fb2d897250 100755
--- a/perl-package/AI-MXNet/examples/gluon/mnist.pl
+++ b/perl-package/AI-MXNet/examples/gluon/mnist.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/examples/lstm_bucketing.pl
b/perl-package/AI-MXNet/examples/lstm_bucketing.pl
index 3618a62d1fb..168c7c2be30 100755
--- a/perl-package/AI-MXNet/examples/lstm_bucketing.pl
+++ b/perl-package/AI-MXNet/examples/lstm_bucketing.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/examples/mnist.pl
b/perl-package/AI-MXNet/examples/mnist.pl
index ca452cd9544..3786b6be98e 100755
--- a/perl-package/AI-MXNet/examples/mnist.pl
+++ b/perl-package/AI-MXNet/examples/mnist.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/examples/plot_network.pl
b/perl-package/AI-MXNet/examples/plot_network.pl
index fc38ef2baaa..bf39988e710 100755
--- a/perl-package/AI-MXNet/examples/plot_network.pl
+++ b/perl-package/AI-MXNet/examples/plot_network.pl
@@ -1,4 +1,4 @@
-#!/usr/bin/perl
+#!/usr/bin/env perl
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet.pm
b/perl-package/AI-MXNet/lib/AI/MXNet.pm
index 651ca92ad69..6a559a394a9 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet.pm
@@ -51,7 +51,7 @@ use AI::MXNet::Gluon;
use AI::MXNet::NDArray::Sparse;
use AI::MXNet::Symbol::Sparse;
use AI::MXNet::Engine;
-our $VERSION = '1.32';
+our $VERSION = '1.33';
sub import
{
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon.pm
index 92c8386c0d1..fde2f6ac5a6 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon.pm
@@ -82,7 +82,7 @@ sub model_zoo { require AI::MXNet::Gluon::ModelZoo;
'AI::MXNet::Gluon::ModelZoo'
but rather brings the training algorithm and model closer together to
provide flexibility in the development process.
Dynamic Graphs: Gluon enables developers to define neural network models
that are dynamic,
- meaning they can be built on the fly, with any structure, and using any of
Perl’s native control flow.
+ meaning they can be built on the fly, with any structure, and using any of
Perl's native control flow.
High Performance: Gluon provides all of the above benefits without
impacting the training speed that the underlying engine provides.
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Block.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Block.pm
index 1b35e7864c1..599c3c3bef6 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Block.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Block.pm
@@ -93,6 +93,7 @@ method __exit__()
package AI::MXNet::Gluon::Block;
use AI::MXNet::Gluon::Mouse;
+use Scalar::Util qw(refaddr);
=head2 NAME
@@ -288,14 +289,15 @@ method __setattr__($name, $current, $prev=)
method _check_container_with_block()
{
- my $_find_block_in_container;
- $_find_block_in_container = sub { my ($data) = @_;
+ my $_find_unregistered_block_in_container;
+ my %children = map { refaddr($_) => 1 } $self->_children->values;
+ $_find_unregistered_block_in_container = sub { my ($data) = @_;
# Find whether a nested container structure contains Blocks
if(ref $data eq 'ARRAY')
{
for my $ele (@{ $data })
{
- if($_find_block_in_container->($ele))
+ if($_find_unregistered_block_in_container->($ele))
{
return 1
}
@@ -306,7 +308,7 @@ method _check_container_with_block()
{
for my $v (values %$data)
{
- if($_find_block_in_container->($v))
+ if($_find_unregistered_block_in_container->($v))
{
return 1;
}
@@ -315,7 +317,7 @@ method _check_container_with_block()
}
elsif(blessed $data and $data->isa('AI::MXNet::Gluon::Block'))
{
- return 1;
+ return not exists $children{ refaddr($data) };
}
else
{
@@ -327,10 +329,10 @@ method _check_container_with_block()
{
if((ref $v eq 'HASH' or ref $v eq 'ARRAY') and not $k =~ /^__/)
{
- if($_find_block_in_container->($v))
+ if($_find_unregistered_block_in_container->($v))
{
AI::MXNet::Logging->warning(
- '"%s" is a container with Blocks. '.
+ '"%s" is a unregsitered container with Blocks. '.
'Note that Blocks inside the list, tuple or dict will not
be '.
'registered automatically. Make sure to register them
using '.
'register_child() or switching to '.
@@ -837,10 +839,11 @@ method summary(@inputs)
$shared_params += $summary->get($layer)->get('shared');
}
print (('=')x80, "\n");
- print "Total params: $total_params\n";
- print "Trainable params: $trainable_params\n";
- print "Non-trainable params: ", $total_params - $trainable_params,
"\n";
- print "Shared params: $shared_params\n";
+ print "Parameters in forward computation graph, duplicate included\n";
+ print " Total params: $total_params\n";
+ print " Non-trainable params: ", $total_params - $trainable_params,
"\n";
+ print "Shared params in forward computation graph: $shared_params\n";
+ print "Unique parameters in model: ", $total_params - $shared_params,
"\n";
print (('-')x80, "\n");
};
$_->detach for @hooks;
@@ -1361,19 +1364,25 @@ sub BUILD
}
}
- for my $i (@{ $out->list_arguments })
+ my $arg_params = $out->list_arguments;
+ my $aux_params = $out->list_auxiliary_states;
+ my ($arg_types, $aux_types) = _infer_param_types($syms, $out, $arg_params,
$aux_params);
+
+ for(enumerate($arg_params))
{
- if(not exists $input_names{$i})
+ my ($i, $arg) = @$_;
+ if(not exists $input_names{ $arg })
{
- $self->params->get($i, allow_deferred_init => 1);
+ $self->params->get($arg, allow_deferred_init => 1, dtype =>
$arg_types->[$i]);
}
}
- for my $i (@{ $out->list_auxiliary_states })
+ for(enumerate($aux_params))
{
- if(not exists $input_names{$i})
+ my ($i, $arg) = @$_;
+ if(not exists $input_names{ $arg })
{
- $self->params->get($i, grad_req => 'null', allow_deferred_init =>
1);
+ $self->params->get($arg, grad_req => 'null', allow_deferred_init
=> 1, dtype => $aux_types->[$i]);
}
}
@@ -1388,6 +1397,71 @@ sub BUILD
$self->_prefix($prefix);
}
+
+func _infer_param_types($in_params, $out_params, $arg_params, $aux_params,
$default_dtype='float32')
+{
+ # Utility function that helps in inferring DType of args and auxs params
+ # from given input param.
+ # Parameters
+ # ----------
+ # in_params: array ref of AI::MXNet::Symbol objects
+ # List of input symbol variables.
+ # out_params: AI::MXNet::Symbol
+ # Output symbol variable.
+ # arg_params: array ref of Str
+ # List of names of argument parametrs.
+ # aux_params: array ref of Str
+ # List of names of auxiliary parameters.
+ # default_dtype: Dtype, default 'float32'
+ # Default data type for arg_params and aux_params, if unable to infer
the type.
+ # Returns
+ # -------
+ # arg_types: Array ref of Dtype
+ # List of arg_params type. Order is same as arg_params.
+ # Defaults to 'float32', if unable to infer type.
+ # aux_types: Array ref of Dtype
+ # List of aux_params type. Order is same as aux_params.
+ # Defaults to 'float32', if unable to infer type.
+
+ my $arg_types;
+ my $aux_types;
+ # Get Input symbol details. This will be used to infer types of
+ # other parameters.
+ my @input_sym_names = map { $_->name } @{ $in_params };
+ # Try to infer input types. If not successful, we will set default dtype.
+ # If successful, we will try to infer other params in the graph.
+ my @input_sym_arg_types;
+ my $can_infer_input_type = 1;
+ for my $in_param(@{ $in_params })
+ {
+ my $input_sym_arg_type = ($in_param->infer_type)[0];
+ if(not $input_sym_arg_type or @$input_sym_arg_type < 1)
+ {
+ $can_infer_input_type = 0;
+ last;
+ }
+ else
+ {
+ push @input_sym_arg_types, $input_sym_arg_type->[0];
+ }
+ }
+ # Try to infer types of other parameters.
+ if($can_infer_input_type)
+ {
+ my %params = map { $_->[0] => $_->[1] } zip(\@input_sym_names,
\@input_sym_arg_types);
+ ($arg_types, undef, $aux_types) = $out_params->infer_type(%params);
+ if(not defined $arg_types or @$arg_types != @$arg_params)
+ {
+ $arg_types = [($default_dtype)x@$arg_params];
+ }
+ if(not defined $aux_types or @$aux_types != @$aux_params)
+ {
+ $aux_types = [($default_dtype)x@$aux_params];
+ }
+ }
+ return ($arg_types, $aux_types);
+}
+
func _common_prefix(@names)
{
if(not @names)
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/NN/Activation.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/NN/Activation.pm
index 092893a924a..1d6342f4955 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/NN/Activation.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/NN/Activation.pm
@@ -201,16 +201,9 @@ package AI::MXNet::Gluon::NN::SELU;
use AI::MXNet::Gluon::Mouse;
extends 'AI::MXNet::Gluon::HybridBlock';
-sub BUILD
-{
- my $self = shift;
- $self->scale(1.0507009873554804934193349852946);
- $self->alpha(1.6732632423543772848170429916717);
-}
-
method hybrid_forward(GluonClass $F, GluonInput $x)
{
- return $self->scale * $F->where($x > 0, $x, $self->alpha * ($F->exp($x) -
1));
+ $F->LeakyReLU($x, act_type=>'selu', name=>'fwd');
}
__PACKAGE__->register('AI::MXNet::Gluon::NN');
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Parameter.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Parameter.pm
index 475c2a93647..89cd0cac622 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Parameter.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Parameter.pm
@@ -421,7 +421,7 @@ method _reduce()
{
my $all_row_ids = AI::MXNet::NDArray->arange(stop =>
$self->shape->[0], dtype=>'int64', ctx=>$ctx);
$data = AI::MXNet::NDArray->zeros($self->shape, stype=>'row_sparse',
ctx=>$ctx);
- $self->_trainer->_row_sparse_pull($self, $data, $all_row_ids);
+ $self->_trainer->_row_sparse_pull($self, $data, $all_row_ids, 1);
}
return $data;
}
@@ -1047,6 +1047,10 @@ method get(Str $name, %kwargs)
next;
}
}
+ elsif($k eq 'dtype' and ($v//'') eq ($existing//''))
+ {
+ next;
+ }
assert(
(not defined $v or Dumper($v) eq Dumper($param->$k)),
"Cannot retrieve Parameter $name because desired
attribute ".
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Trainer.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Trainer.pm
index 1b3b49f3652..6117777eed8 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Trainer.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Gluon/Trainer.pm
@@ -279,16 +279,24 @@ method _init_kvstore()
$self->_kv_initialized(1);
}
-method _row_sparse_pull($parameter, $out, $row_id)
+# Internal method to invoke pull operations on KVStore. If $full_idx is set to
1,
+# $kv->pull is preferred instead of $kv->row_sparse_pull.
+
+method _row_sparse_pull($parameter, $out, $row_id, $full_idx=0)
{
# initialize kv and params if not already
$self->_init_kvstore() unless $self->_kv_initialized;
$self->_init_params() if scalar(@{ $self->_params_to_init });
- $self->kvstore->row_sparse_pull(
- $self->_param2idx->{ $parameter->name },
- out => $out,
- row_ids => $row_id
- );
+ my $idx = $self->_param2idx->{ $parameter->name };
+ if($full_idx and not $self->kvstore->type =~ /dist/)
+ {
+ assert($row_id->size == $out->shape->[0]);
+ $self->kvstore->pull($idx, out => $out, priority => -$idx,
ignore_sparse => 0);
+ }
+ else
+ {
+ $self->kvstore->row_sparse_pull($idx, out => $out, row_ids => $row_id,
priority => -$idx);
+ }
}
=head2 step
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Initializer.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Initializer.pm
index fe8dce32e2d..0359cc3640d 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Initializer.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Initializer.pm
@@ -86,7 +86,7 @@ has '_print_func' => (is => 'rw', isa => 'CodeRef', lazy => 1,
mx->init->One Initializes weights to one.
mx->init->Constant Initializes the weights to a given value.
mx->init->Orthogonal Initialize weight as orthogonal matrix.
- mx->init->Xavier Returns an initializer performing “Xavier”
initialization for weights.
+ mx->init->Xavier Returns an initializer performing Xavier
initialization for weights.
mx->init->MSRAPrelu Initialize the weight according to a MSRA paper.
mx->init->Bilinear Initialize weight for upsampling layers.
mx->init->FusedRNN Initialize parameters for fused rnn layers.
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/KVStore.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/KVStore.pm
index bb6631f459a..15aad76c7b4 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/KVStore.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/KVStore.pm
@@ -215,13 +215,14 @@ method push(
method pull(
Str|ArrayRef[Str] $key,
AI::MXNet::NDArray|ArrayRef[AI::MXNet::NDArray]|ArrayRef[ArrayRef[AI::MXNet::NDArray]]
:$out,
- Int :$priority=0
+ Int :$priority=0,
+ Bool :$ignore_sparse=1
)
{
my ($keys, $vals) = _key_value($key, $out);
check_call(
- AI::MXNetCAPI::KVStorePullEx(
- $self->handle, scalar(@{ $keys }), $keys, $vals, $priority
+ AI::MXNetCAPI::KVStorePullWithSparseEx(
+ $self->handle, scalar(@{ $keys }), $keys, $vals, $priority,
$ignore_sparse
)
);
}
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Metric.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Metric.pm
index b6e91aeaf72..0941316960a 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Metric.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Metric.pm
@@ -240,7 +240,7 @@ method get()
The accuracy score is defined as
- accuracy(y, y^) = (1/n) * sum(i=0..n−1) { y^(i)==y(i) }
+ accuracy(y, y^) = (1/n) * sum(i=0..n-1) { y^(i)==y(i) }
Parameters:
axis (Int, default=1) – The axis that represents classes.
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Module/Base.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Module/Base.pm
index b9d5011008d..542cf498f49 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Module/Base.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Module/Base.pm
@@ -27,6 +27,7 @@ package AI::MXNet::Module::Base;
use Mouse;
use AI::MXNet::Base;
use Time::HiRes qw(time);
+use Storable qw(dclone);
=head1 NAME
@@ -350,7 +351,7 @@ method iter_predict(AI::MXNet::DataIter $eval_data,
Maybe[Int] :$num_batch=, Boo
Parameters
----------
- $eval_data : AI::MXNet::DataIter
+ $eval_data : AI::MXNet::DataIter|AcceptableInput (PDL|NDArray)
:$num_batch= : Maybe[Int]
Default is undef, indicating running all the batches in the data
iterator.
:$merge_batches=1 : Bool
@@ -363,6 +364,8 @@ method iter_predict(AI::MXNet::DataIter $eval_data,
Maybe[Int] :$num_batch=, Boo
Returns
-------
+ If the input is AI::MXNet::NDArray|PDL then the return value is
AI::MXNet::NDArray.
+
When $merge_batches is 1 (by default), the return value will be an array
ref
[$out1, $out2, $out3] where each element is concatenation of the outputs
for
all the mini-batches. If $always_output_list` also is 0 (by default),
@@ -378,13 +381,21 @@ method iter_predict(AI::MXNet::DataIter $eval_data,
Maybe[Int] :$num_batch=, Boo
=cut
method predict(
- AI::MXNet::DataIter $eval_data,
+ AI::MXNet::DataIter|AcceptableInput $eval_data,
Maybe[Int] :$num_batch=, Bool :$merge_batches=1, Bool :$reset=1, Bool
:$always_output_list=0
)
{
assert($self->binded and $self->params_initialized);
+ if(not blessed $eval_data or not $eval_data->isa('AI::MXNet::DataIter'))
+ {
+ if(not blessed $eval_data or not $eval_data->isa('AI::MXNet::NDArray'))
+ {
+ $eval_data = AI::MXNet::NDArray->array($eval_data);
+ }
+ $self->forward(AI::MXNet::DataBatch->new(data => [$eval_data]));
+ return $self->get_outputs->[0];
+ }
$eval_data->reset() if $reset;
-
my @output_list;
my $nbatch = 0;
while(my $eval_batch = <$eval_data>)
@@ -533,6 +544,7 @@ method fit(
}
$eval_metric = AI::MXNet::Metric->create($eval_metric)
unless blessed $eval_metric;
+ my $epoch_eval_metric = dclone($eval_metric);
################################################################################
# training loop
@@ -541,6 +553,7 @@ method fit(
{
my $tic = time;
$eval_metric->reset;
+ $epoch_eval_metric->reset;
my $nbatch = 0;
my $end_of_batch = 0;
my $next_data_batch = <$train_data>;
@@ -559,10 +572,11 @@ method fit(
{
$end_of_batch = 1;
}
- $self->update_metric($eval_metric, $data_batch->label);
+ $self->update_metric($epoch_eval_metric, $data_batch->label);
$monitor->toc_print if $monitor;
if(defined $batch_end_callback)
{
+ $self->update_metric($eval_metric, $data_batch->label);
my $batch_end_params = AI::MXNet::BatchEndParam->new(
epoch => $epoch,
nbatch => $nbatch,
@@ -576,7 +590,7 @@ method fit(
$nbatch++;
}
# one epoch of training is finished
- my $name_value = $eval_metric->get_name_value;
+ my $name_value = $epoch_eval_metric->get_name_value;
while(my ($name, $val) = each %{ $name_value })
{
$self->logger->info('Epoch[%d] Train-%s=%f', $epoch, $name, $val);
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/NDArray.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/NDArray.pm
index 87395319293..3a7b6bab2e2 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/NDArray.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/NDArray.pm
@@ -27,14 +27,14 @@ package AI::MXNet::NDArray;
AI::MXNet::NDArray - Imperative tensor operations on CPU/GPU
In AI::MXNet, NDArray is the core data structure for all mathematical
computations.
An NDArray represents a multidimensional, fixed-size homogenous array.
- If you’re familiar with the PDL, you might notice some similarities.
+ If you're familiar with the PDL, you might notice some similarities.
However, NDArray is row-major, unlike the PDL that is column-major.
Like the PDL, MXNet’s NDArray enables imperative computation.
Some NDArray advandages compared to PDL:
- MXNet’s NDArray supports fast execution on a wide range of hardware
configurations, including CPU, GPU, and multi-GPU machines.
+ MXNet's NDArray supports fast execution on a wide range of hardware
configurations, including CPU, GPU, and multi-GPU machines.
MXNet also scales to distributed systems in the cloud.
- MXNet’s NDArray executes code lazily, allowing it to automatically
parallelize multiple operations across the available hardware.
+ MXNet's NDArray executes code lazily, allowing it to automatically
parallelize multiple operations across the available hardware.
An NDArray is a multidimensional array of numbers with the same type.
We could represent the coordinates of a point in 3D space, e.g. [2, 1, 6]
as a 1D array with shape (3).
@@ -43,9 +43,9 @@ package AI::MXNet::NDArray;
[[0, 1, 2]
[3, 4, 5]]
- Note that here the use of “dimension” is overloaded. When we say a 2D
array, we mean an array with 2 axes, not an array with two components.
+ Note that here the use of 'dimension' is overloaded. When we say a 2D
array, we mean an array with 2 axes, not an array with two components.
- Each NDArray supports some important attributes that you’ll often want to
query:
+ Each NDArray supports some important attributes that you'll often want to
query:
$ndarray->shape: The dimensions of the array.
It is an array ref of integers indicating the length of the array along
each axis.
diff --git a/perl-package/AI-MXNet/lib/AI/MXNet/Random.pm
b/perl-package/AI-MXNet/lib/AI/MXNet/Random.pm
index 8a47a1210e1..7a99b1dc7ea 100644
--- a/perl-package/AI-MXNet/lib/AI/MXNet/Random.pm
+++ b/perl-package/AI-MXNet/lib/AI/MXNet/Random.pm
@@ -90,6 +90,20 @@ sub AUTOLOAD {
);
my @args;
my @tmp = @_;
+ if($sub eq 'randn')
+ {
+ $sub = 'normal';
+ my @shape;
+ while(defined $tmp[0] and $tmp[0] =~ /^\d+$/)
+ {
+ push @shape, shift(@tmp);
+ }
+ if(@shape)
+ {
+ push @tmp, (shape => \@shape);
+ }
+ %defaults = (%defaults, loc => 0, scale => 1);
+ }
if(ref $tmp[-1] eq 'HASH')
{
my @kwargs = %{ pop(@tmp) };
diff --git a/perl-package/AI-MXNet/t/test_gluon_trainer.t
b/perl-package/AI-MXNet/t/test_gluon_trainer.t
index 8b3b52b1ce9..81113af28c2 100644
--- a/perl-package/AI-MXNet/t/test_gluon_trainer.t
+++ b/perl-package/AI-MXNet/t/test_gluon_trainer.t
@@ -24,6 +24,7 @@ use AI::MXNet::Gluon::NN qw(nn);
use AI::MXNet::TestUtils qw(almost_equal dies_ok);
use Scalar::Util qw(refaddr);
use AI::MXNet::Base;
+$ENV{MXNET_STORAGE_FALLBACK_LOG_VERBOSE} = 0;
sub test_multi_trainer
{
@@ -127,15 +128,16 @@ sub test_trainer
test_trainer();
-sub test_trainer_save_load
+sub test_trainer_sparse_save_load
{
- my $x = gluon->Parameter('x', shape=>[10], lr_mult=>1.0);
- $x->initialize(ctx=>[mx->cpu(0), mx->cpu(1)], init=>'zeros');
+ my $x = gluon->Parameter('x', shape=>[10, 1], lr_mult=>1.0,
stype=>'row_sparse');
+ $x->initialize(ctx=>[mx->cpu(0)], init=>'zeros');
my $trainer = gluon->Trainer([$x], 'sgd', {learning_rate => 0.1});
+ my $all_rows = mx->nd->arange(start => 0, stop => 10, ctx => mx->cpu(0));
mx->autograd->record(sub {
- for my $w (@{ $x->list_data })
+ for my $w (@{ $x->list_row_sparse_data($all_rows) })
{
- my $y = $w + 1;
+ my $y = $w * 1;
$y->backward();
}
});
@@ -148,7 +150,7 @@ sub test_trainer_save_load
ok($trainer->kvstore->_updater->optimizer->_get_lr(0) == 0.2);
}
-test_trainer_save_load();
+test_trainer_sparse_save_load();
sub test_trainer_multi_layer_init
{
diff --git a/perl-package/AI-MXNet/t/test_module.t
b/perl-package/AI-MXNet/t/test_module.t
index c29c459bd1b..3bbd8fdc4ea 100644
--- a/perl-package/AI-MXNet/t/test_module.t
+++ b/perl-package/AI-MXNet/t/test_module.t
@@ -17,7 +17,7 @@
use strict;
use warnings;
-use Test::More tests => 426;
+use Test::More tests => 428;
use AI::MXNet qw(mx);
use AI::MXNet::Base;
use AI::MXNet::TestUtils qw(almost_equal enumerate same_array dies_like
rand_ndarray);
@@ -789,6 +789,17 @@ sub test_forward_reshape
}
+sub test_forward_acceptable_input
+{
+ my $data = mx->sym->Variable('data');
+ my $out = $data * 2;
+ my $mod = mx->mod->Module(symbol => $out);
+ $mod->bind(data_shapes => [['data', [1, 10]]]);
+ $mod->init_params();
+ is_deeply($mod->predict(mx->nd->ones([1, 10]))->shape, [1, 10]);
+ is_deeply($mod->predict(mx->nd->ones([1, 10])->aspdl)->shape, [1, 10]);
+}
+
test_module_input_grads();
test_module_dtype();
test_monitor();
@@ -802,3 +813,4 @@ test_module_set_params();
test_forward_reshape();
test_module_initializer();
test_factorization_machine_module();
+test_forward_acceptable_input();
diff --git a/perl-package/AI-MXNet/t/test_random.t
b/perl-package/AI-MXNet/t/test_random.t
index 542f79c5e71..f049679cbdb 100644
--- a/perl-package/AI-MXNet/t/test_random.t
+++ b/perl-package/AI-MXNet/t/test_random.t
@@ -17,7 +17,7 @@
use strict;
use warnings;
-use Test::More tests => 506;
+use Test::More tests => 515;
use AI::MXNet qw(mx);
use AI::MXNet::TestUtils qw(same enumerate);
@@ -37,6 +37,15 @@ sub check_with_device
[std => sub { my ($x, $params) = @_;
($x->astype('float64')->aspdl->stats)[6] - $params->{scale} }, $tol]
]
},
+ {
+ name => 'randn',
+ ndop => sub { mx->nd->random->randn(@_) },
+ params => { loc => 10.0, scale => 0.5 },
+ checks => [
+ [mean => sub { my ($x, $params) = @_;
$x->astype('float64')->aspdl->avg - $params->{loc} }, $tol],
+ [std => sub { my ($x, $params) = @_;
($x->astype('float64')->aspdl->stats)[6] - $params->{scale} }, $tol]
+ ]
+ },
{
name => 'uniform',
symbol => sub { mx->sym->random->uniform(@_) },
@@ -126,6 +135,7 @@ sub check_with_device
}
# check multi-distribution sampling, only supports cpu for now
+ next unless $symbdic->{inputs};
%params = (shape=>$shape, dtype=>$dtype, ctx=>$device);
%params = (%params, map { $_->[0] => mx->nd->array($_->[1],
ctx=>$device, dtype=>$dtype) } @{ $symbdic->{inputs} });
mx->random->seed(128);
@@ -149,6 +159,7 @@ sub check_with_device
# check symbolic
my $symbol = $symbdic->{symbol};
+ next if not $symbol;
my $X = mx->sym->Variable("X");
%params = %{ $symbdic->{params} };
%params = (%params, shape=>$shape, dtype=>$dtype);
diff --git a/perl-package/AI-MXNetCAPI/Changes
b/perl-package/AI-MXNetCAPI/Changes
index 938b8e268f1..08ad085abce 100644
--- a/perl-package/AI-MXNetCAPI/Changes
+++ b/perl-package/AI-MXNetCAPI/Changes
@@ -1,5 +1,9 @@
Revision history for Perl extension AI::MXNetCAPI
+1.33 Thu Oct 4 13:25:56 PDT 2018
+ - Gluon: Better sparse support for KVStore.
+ - Gpu memory info via mxnet api call.
+
1.32 Sun Aug 5 14:25:31 PDT 2018
- Bugfixes.
diff --git a/perl-package/AI-MXNetCAPI/META.json
b/perl-package/AI-MXNetCAPI/META.json
index 854023559c6..1849e6b3bc1 100644
--- a/perl-package/AI-MXNetCAPI/META.json
+++ b/perl-package/AI-MXNetCAPI/META.json
@@ -37,5 +37,5 @@
}
},
"release_status" : "stable",
- "version" : "1.32"
+ "version" : "1.33"
}
diff --git a/perl-package/AI-MXNetCAPI/META.yml
b/perl-package/AI-MXNetCAPI/META.yml
index 1db34c501d8..eb5d9aae801 100644
--- a/perl-package/AI-MXNetCAPI/META.yml
+++ b/perl-package/AI-MXNetCAPI/META.yml
@@ -19,4 +19,4 @@ no_index:
- inc
requires:
Test::More: '0'
-version: '1.32'
+version: '1.33'
diff --git a/perl-package/AI-MXNetCAPI/README b/perl-package/AI-MXNetCAPI/README
index f5881ff2db0..67b77ccd161 100644
--- a/perl-package/AI-MXNetCAPI/README
+++ b/perl-package/AI-MXNetCAPI/README
@@ -1,4 +1,4 @@
-AI-MXNetCAPI version 1.32
+AI-MXNetCAPI version 1.33
=====================
Swig interface to MXNet c api.
diff --git a/perl-package/AI-MXNetCAPI/lib/AI/MXNetCAPI.pm
b/perl-package/AI-MXNetCAPI/lib/AI/MXNetCAPI.pm
index e371219b0ae..bc7676047d7 100644
--- a/perl-package/AI-MXNetCAPI/lib/AI/MXNetCAPI.pm
+++ b/perl-package/AI-MXNetCAPI/lib/AI/MXNetCAPI.pm
@@ -18,7 +18,7 @@
package AI::MXNetCAPI;
use base qw(DynaLoader);
bootstrap AI::MXNetCAPI;
-our $VERSION = '1.32';
+our $VERSION = '1.33';
1;
__END__
diff --git a/perl-package/AI-MXNetCAPI/mxnet.i
b/perl-package/AI-MXNetCAPI/mxnet.i
index 2540e1bc63b..38665748a0b 100644
--- a/perl-package/AI-MXNetCAPI/mxnet.i
+++ b/perl-package/AI-MXNetCAPI/mxnet.i
@@ -342,6 +342,15 @@ int MXEngineSetBulkSize(int bulk_size, int* out);
*/
int MXGetGPUCount(int* out);
+/*!
+ * \brief get the free and total available memory on a GPU
+ * \param dev the GPU number to query
+ * \param free_mem pointer to the integer holding free GPU memory
+ * \param total_mem pointer to the integer holding total GPU memory
+ * \return 0 when success, -1 when failure happens
+ */
+int MXGetGPUMemoryInformation(int dev, int *out, int *out);
+
//-------------------------------------
// Part 1: NDArray creation and deletion
@@ -1816,6 +1825,24 @@ int MXKVStorePullRowSparseEx(KVStoreHandle handle,
NDArrayHandle* in,
NDArrayHandle* in,
int priority);
+
+/*!
+ * \brief pull a list of (key, value) pairs from the kvstore, where each key
is a string
+ * \param handle handle to the kvstore
+ * \param num the number of key-value pairs
+ * \param keys the list of keys
+ * \param vals the list of values
+ * \param priority the priority of the action
+ * \param ignore_sparse whether to ignore sparse arrays in the request
+ * \return 0 when success, -1 when failure happens
+ */
+int MXKVStorePullWithSparseEx(KVStoreHandle handle,
+ mx_uint num,
+ const char** in,
+ NDArrayHandle* in,
+ int priority,
+ bool ignore_sparse);
+
/*!
* \brief user-defined updater for the kvstore
* It's this updater's responsibility to delete \a recv and \a local
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