[Perl] emulate Python zip() for Perl #8192

tlby · 2017-10-09T17:42:24Z

An alternate version of zip() that can be used a bit more like python's version, and runs a bit faster.

use strict;
use warnings;
use Benchmark;
use AI::MXNet 'mx';

my @l1 = (0 .. 64);
my @l2 = (0 .. 64);
my @l3 = (0 .. 64);
my @l4 = (0 .. 64);

sub orig_zip
{
    my ($sub, @arrays) = @_;
    my $len = @{ $arrays[0] };
    for (my $i = 0; $i < $len; $i++)
    {
        $sub->(map { $_->[$i] } @arrays);
    }
}

Benchmark::cmpthese(-4, {
    orig => sub {
        my @l;
        orig_zip(sub {
            push @l, $_[0] + $_[1] + $_[2] + $_[3];
        }, \@l1, \@l2, \@l3, \@l4);
    },
    repl => sub {
        my @l;
        AI::MXNet::zip(sub {
            push @l, $_[0] + $_[1] + $_[2] + $_[3];
        }, \@l1, \@l2, \@l3, \@l4);
    },
    pure => sub {
        my @l = map { $_->[0] + $_->[1] + $_->[2] + $_->[3] }
            AI::MXNet::zip(\@l1, \@l2, \@l3, \@l4);
    },
});

gives

	Rate	orig	repl	pure
orig	21964/s	--	-32%	-37%
repl	32190/s	47%	--	-7%
pure	34657/s	58%	8%	--

tlby · 2017-10-09T17:52:11Z

@sergeykolychev, the benchmark shows a slight performance boost when using zip() without callbacks, and it would also be closer to the python code. Should this patch also retool the uses of zip() to take advantage of this?

sergeykolychev · 2017-10-09T19:26:29Z

@gautamkmr could you please investigate this jenkins failure, missing license headers in files in the julia-package submodule was why this Jenkins failed.
This pull don't have a julia-package submodule and master doesn't (yet) either.

sergeykolychev

Thanks!

tlby · 2017-10-09T19:31:35Z

#8175 adds the julia-package work and had tests pending at the same time this failure occurred.

sergeykolychev · 2017-10-09T19:44:46Z

@tlby if you have time and desire please retool the current zip (there's also enumerate that uses zip ) usage get those 8% but that's substantial work. If you embark on this project please make sure that you test all examples in addition to the passing tests.

tlby · 2017-10-09T23:14:26Z

The second commit refactors most of the uses of zip() to avoid the callback form, though the handler still supports that call style. Both tests and examples seem happy to me.

sergeykolychev · 2017-10-10T01:42:18Z

@tlby
cool man
did you run the GPU examples as well ?

sergeykolychev · 2017-10-10T02:22:43Z

perl-package/AI-MXNet/t/test_base.t

+use warnings;
+use Test::More;
+use AI::MXNet qw(mx);
+use AI::MXNet::TestUtils qw(same reldiff GetMNIST_ubyte GetCifar10);


this line is not needed

sergeykolychev · 2017-10-10T02:30:32Z

@tlby also please see if it makes sense to retool enumerate calls

tlby · 2017-10-10T03:37:27Z

I'd like to work out enumerate() in a different PR, since this one got kinda big with the refactor.

sergeykolychev · 2017-10-10T06:41:52Z

Ok

tlby · 2017-10-12T15:23:41Z

did you run the GPU examples as well ?

I haven't yet, but I will.

tlby · 2017-10-12T20:48:23Z

The GPU examples are healthy.

* [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form

* Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (#8369) * Allow test to converge (#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (#7988) * [Perl] emulate Python zip() for Perl (#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (#8376) Fix a typo in the example readme.

* CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (#8125) * v0.12 regression: Fix registration of children for Block (#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from #8152 * Add tests from #8152 * Revert "[CMAKE] Fix windows cmake build" (#8311) * Revert "Added my code signing key (#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (#8300) * Update rnn.md (#8320) * fluent methods for missed ops (#8329) * update ps lite (#8327) * Fix unused type warning (#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (#8369) * Allow test to converge (#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (#7988) * [Perl] emulate Python zip() for Perl (#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (#8376) Fix a typo in the example readme.

…che#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme.

* CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (apache#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (apache#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (apache#8125) * v0.12 regression: Fix registration of children for Block (apache#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from apache#8152 * Add tests from apache#8152 * Revert "[CMAKE] Fix windows cmake build" (apache#8311) * Revert "Added my code signing key (apache#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (apache#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (apache#8300) * Update rnn.md (apache#8320) * fluent methods for missed ops (apache#8329) * update ps lite (apache#8327) * Fix unused type warning (apache#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme.

…che#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme.

* CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (apache#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (apache#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (apache#8125) * v0.12 regression: Fix registration of children for Block (apache#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from apache#8152 * Add tests from apache#8152 * Revert "[CMAKE] Fix windows cmake build" (apache#8311) * Revert "Added my code signing key (apache#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (apache#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (apache#8300) * Update rnn.md (apache#8320) * fluent methods for missed ops (apache#8329) * update ps lite (apache#8327) * Fix unused type warning (apache#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme.

* [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form

…che#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme.

* CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (apache#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (apache#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (apache#8125) * v0.12 regression: Fix registration of children for Block (apache#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from apache#8152 * Add tests from apache#8152 * Revert "[CMAKE] Fix windows cmake build" (apache#8311) * Revert "Added my code signing key (apache#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (apache#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (apache#8300) * Update rnn.md (apache#8320) * fluent methods for missed ops (apache#8329) * update ps lite (apache#8327) * Fix unused type warning (apache#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme.

* Fill optimizations * Optimize IdentityCompute for CPU * lint * Fix unused type warning (#8316) * remove unused variable * CR comments * CR comments * Added _full operator * Trigger build * Trigger build * Add _full to symbolic * Merge conflict resolution fix * lint * Timing output for test_factorization_module when Verbose enabled (#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (#8369) * Allow test to converge (#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (#7988) * [Perl] emulate Python zip() for Perl (#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (#8376) Fix a typo in the example readme. * Use omp_get_max_threads() when OMP_NUM_THREADS environment variable is set (#8379) * CPU optimization for ActivationOp (#8296) * CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (#8125) * v0.12 regression: Fix registration of children for Block (#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from #8152 * Add tests from #8152 * Revert "[CMAKE] Fix windows cmake build" (#8311) * Revert "Added my code signing key (#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (#8300) * Update rnn.md (#8320) * fluent methods for missed ops (#8329) * update ps lite (#8327) * Fix unused type warning (#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (#8369) * Allow test to converge (#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (#7988) * [Perl] emulate Python zip() for Perl (#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (#8376) Fix a typo in the example readme. * Fix GPU copy * Remove duplicate * Trigger build

* Memory set/copy speed assertions * Memory set/copy speed assertions * .. * .. * .. * .. * bounce some cache * lint * Timing output for test_factorization_module when Verbose enabled (#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (#8369) * Allow test to converge (#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (#7988) * [Perl] emulate Python zip() for Perl (#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (#8376) Fix a typo in the example readme. * Use omp_get_max_threads() when OMP_NUM_THREADS environment variable is set (#8379) * CPU optimization for ActivationOp (#8296) * CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (#8125) * v0.12 regression: Fix registration of children for Block (#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from #8152 * Add tests from #8152 * Revert "[CMAKE] Fix windows cmake build" (#8311) * Revert "Added my code signing key (#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (#8300) * Update rnn.md (#8320) * fluent methods for missed ops (#8329) * update ps lite (#8327) * Fix unused type warning (#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (#8369) * Allow test to converge (#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (#7988) * [Perl] emulate Python zip() for Perl (#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (#8376) Fix a typo in the example readme. * do gtest test * add assert and do higher runs as performance test only (when performance test flag set) * Trigger build * lint * Trigger build * Sparse operator performance improvement (#8412) * sparse rsprsp perf improvements * Clean up * dtype default to source_array.dtype for sparse ndarrays (#8403) * derive default dtype/ctx from input for sparse ndarrays * add gpu tests * fix lint. add doc * remove default_ctx code * bug fix when passing dtype to array() * update doc * remove extra line * also check ctx * fix using default mean pixels (#8352) * fix gluon.data.RecordFileDataset (#8353) * upgrade MKL (#8378) * Lint fix (#8402) * Trigger build

* Fill optimizations * Optimize IdentityCompute for CPU * lint * Fix unused type warning (apache#8316) * remove unused variable * CR comments * CR comments * Added _full operator * Trigger build * Trigger build * Add _full to symbolic * Merge conflict resolution fix * lint * Timing output for test_factorization_module when Verbose enabled (apache#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme. * Use omp_get_max_threads() when OMP_NUM_THREADS environment variable is set (apache#8379) * CPU optimization for ActivationOp (apache#8296) * CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (apache#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (apache#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (apache#8125) * v0.12 regression: Fix registration of children for Block (apache#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from apache#8152 * Add tests from apache#8152 * Revert "[CMAKE] Fix windows cmake build" (apache#8311) * Revert "Added my code signing key (apache#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (apache#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (apache#8300) * Update rnn.md (apache#8320) * fluent methods for missed ops (apache#8329) * update ps lite (apache#8327) * Fix unused type warning (apache#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme. * Fix GPU copy * Remove duplicate * Trigger build

* Memory set/copy speed assertions * Memory set/copy speed assertions * .. * .. * .. * .. * bounce some cache * lint * Timing output for test_factorization_module when Verbose enabled (apache#8363) * Timing output for test_factorization_module when Verbose enabled * Trigger build * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme. * Use omp_get_max_threads() when OMP_NUM_THREADS environment variable is set (apache#8379) * CPU optimization for ActivationOp (apache#8296) * CPU optimization for ActivationOp Significant improvement on CPU (several magnitudes of order in some cases, especially on backward pass). Very slight improvement on GPU. OLD MSHADOW APPROACH -------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 18.948 ms, avg: 0.037896 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.658 ms, avg: 0.003316 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 57.973 ms, avg: 0.115946 ms X 500 passes Activation Operator CPU: Timing [Backward] 4.748 ms, avg: 0.009496 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 703.446 ms, avg: 1.40689 ms X 500 passes Activation Operator CPU: Timing [Backward] 56.255 ms, avg: 0.11251 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 2107.77 ms, avg: 4.21554 ms X 500 passes Activation Operator CPU: Timing [Backward] 168.483 ms, avg: 0.336966 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 24122.2 ms, avg: 48.2443 ms X 500 passes Activation Operator CPU: Timing [Backward] 1908.7 ms, avg: 3.8174 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.637 ms, avg: 0.003274 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.665 ms, avg: 0.00333 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.562 ms, avg: 0.003124 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.661 ms, avg: 0.003322 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.635 ms, avg: 0.00327 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.702 ms, avg: 0.003404 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.83 ms, avg: 0.00366 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.041 ms, avg: 0.004082 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.08 ms, avg: 0.00416 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.688 ms, avg: 0.005376 ms X 500 passes NEW MXNET_OP APPROACH --------------------- CPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator CPU: Timing [Forward] 80.748 ms, avg: 0.161496 ms X 500 passes Activation Operator CPU: Timing [Backward] 1.176 ms, avg: 0.002352 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator CPU: Timing [Forward] 7.881 ms, avg: 0.015762 ms X 500 passes Activation Operator CPU: Timing [Backward] 2.181 ms, avg: 0.004362 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator CPU: Timing [Forward] 111.48 ms, avg: 0.22296 ms X 500 passes Activation Operator CPU: Timing [Backward] 5.408 ms, avg: 0.010816 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator CPU: Timing [Forward] 333.439 ms, avg: 0.666878 ms X 500 passes Activation Operator CPU: Timing [Backward] 21.331 ms, avg: 0.042662 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator CPU: Timing [Forward] 3429.19 ms, avg: 6.85837 ms X 500 passes Activation Operator CPU: Timing [Backward] 286.324 ms, avg: 0.572648 ms X 500 passes GPU === Timing: 50 iterations of 10 calls, shape = [1,1,28,28] Activation Operator GPU: Timing [Forward] 1.618 ms, avg: 0.003236 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.671 ms, avg: 0.003342 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [1,3,28,28] Activation Operator GPU: Timing [Forward] 1.629 ms, avg: 0.003258 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.728 ms, avg: 0.003456 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,1,18,32] Activation Operator GPU: Timing [Forward] 1.753 ms, avg: 0.003506 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.756 ms, avg: 0.003512 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [50,3,18,32] Activation Operator GPU: Timing [Forward] 1.704 ms, avg: 0.003408 ms X 500 passes Activation Operator GPU: Timing [Backward] 1.791 ms, avg: 0.003582 ms X 500 passes Timing: 50 iterations of 10 calls, shape = [20,3,128,128] Activation Operator GPU: Timing [Forward] 2.032 ms, avg: 0.004064 ms X 500 passes Activation Operator GPU: Timing [Backward] 2.143 ms, avg: 0.004286 ms X 500 passes * lint * Trigger build * Trigger build * Negative begin and end support for csr slice (apache#8241) * negative index support for sparse slice * fix lint * getitem(int) for csr ndarray, support a[-1] * remove unneccessary argument * unittest and doc update * Preparing for 0.12.0.rc0: Final changes before RC (apache#8301) * Final changes before RC * Updates to NEWS.md * Updates * Enable smoothing in softmax operator (apache#8125) * v0.12 regression: Fix registration of children for Block (apache#8277) * Fix Block not registering children If the attribute was already set to something different than Block (e.g. None), it was not being registered. * fix if / elif for block children registration * trigger test * Add fix from apache#8152 * Add tests from apache#8152 * Revert "[CMAKE] Fix windows cmake build" (apache#8311) * Revert "Added my code signing key (apache#8293)" This reverts commit 22ab185. * Revert "[CMAKE] Fix windows cmake build (apache#8227)" This reverts commit 1c1c788. * fixed broken links. https was pointing to http for mxnet.io (apache#8300) * Update rnn.md (apache#8320) * fluent methods for missed ops (apache#8329) * update ps lite (apache#8327) * Fix unused type warning (apache#8316) * Trigger build * Trigger build * Misc fixes for sparse distributed training (apache#8345) * remove mshadow::range in init_op.h * add unit test * remove pass by ptr, add unit test for pull empty wieghts * fix range in key partition * remove wrong comment * remove change for partition * remove unused var * add int64 to arange. add checkpointing example * Fix the Readme (apache#8369) * Allow test to converge (apache#8351) * Allow test to converge * Trigger build * Trigger build * Trigger build * Update cudnn_algoreg-inl.h (apache#7988) * [Perl] emulate Python zip() for Perl (apache#8192) * [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form * add profile option for frontend profiling to image script (apache#8171) * add profile option for frontend profiling to image script * Update image_classification.py * Update image_classification.py * Fix Typo (classification) (apache#8376) Fix a typo in the example readme. * do gtest test * add assert and do higher runs as performance test only (when performance test flag set) * Trigger build * lint * Trigger build * Sparse operator performance improvement (apache#8412) * sparse rsprsp perf improvements * Clean up * dtype default to source_array.dtype for sparse ndarrays (apache#8403) * derive default dtype/ctx from input for sparse ndarrays * add gpu tests * fix lint. add doc * remove default_ctx code * bug fix when passing dtype to array() * update doc * remove extra line * also check ctx * fix using default mean pixels (apache#8352) * fix gluon.data.RecordFileDataset (apache#8353) * upgrade MKL (apache#8378) * Lint fix (apache#8402) * Trigger build

tlby force-pushed the perl-builtin-zip branch from 759e6fe to e305c47 Compare October 9, 2017 18:09

sergeykolychev approved these changes Oct 9, 2017

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tlby added 2 commits October 12, 2017 08:04

[Perl] emulate Python zip() for Perl

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[Perl] retool zip() uses away from the callback form

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tlby force-pushed the perl-builtin-zip branch from d01636e to 4e97dd3 Compare October 12, 2017 15:04

piiswrong merged commit d6062f7 into apache:master Oct 21, 2017

cjolivier01 pushed a commit to cjolivier01/mxnet that referenced this pull request Oct 22, 2017

[Perl] emulate Python zip() for Perl (apache#8192)

52adc56

* [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form

cjolivier01 pushed a commit to cjolivier01/mxnet that referenced this pull request Oct 22, 2017

[Perl] emulate Python zip() for Perl (apache#8192)

8e661aa

* [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form

crazy-cat pushed a commit to crazy-cat/incubator-mxnet that referenced this pull request Oct 26, 2017

[Perl] emulate Python zip() for Perl (apache#8192)

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* [Perl] emulate Python zip() for Perl * [Perl] retool zip() uses away from the callback form

tlby deleted the perl-builtin-zip branch November 28, 2017 18:31

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[Perl] emulate Python zip() for Perl #8192

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[Perl] emulate Python zip() for Perl #8192

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