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[MXNET-117] Sparse operator broadcast_mul/div(csr, dense) = csr #10208

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eric-haibin-lin merged 8 commits into from
Apr 5, 2018
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[MXNET-117] Sparse operator broadcast_mul/div(csr, dense) = csr #10208

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20ac575
support broadcast_mul/div(csr, 1Ddense) = csr
Mar 18, 2018
ae2c4b7
address code reviews and support broadcast_mul/div(csr, 2Ddense) = csr
Mar 20, 2018
2507d67
add test for both 1D and 2D dense case
Mar 23, 2018
fcf9e0b
address code review and fix test error
Mar 23, 2018
a36e02c
added proper overrides for basic arithmetic functions for sparse tens…
sergeykolychev Mar 29, 2018
20ef4c4
address code review and fix test error
Mar 23, 2018
2c71eaa
fix broadcast dimension
Apr 3, 2018
99585fb
address code reviews
Apr 4, 2018
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2 changes: 2 additions & 0 deletions docs/api/python/ndarray/sparse.md
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Original file line number Diff line number Diff line change
Expand Up @@ -386,6 +386,8 @@ We summarize the interface for each class in the following sections.
elemwise_add
elemwise_sub
elemwise_mul
broadcast_mul
broadcast_div
negative
dot
add_n
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90 changes: 90 additions & 0 deletions perl-package/AI-MXNet/lib/AI/MXNet/NDArray/Sparse.pm
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Original file line number Diff line number Diff line change
Expand Up @@ -80,10 +80,100 @@ use overload '""' => sub {
my $shape_info = join('x', @{ $self->shape });
sprintf("\n<%s, %s @%s>", $self->_class_name, $shape_info, $self->context);
},
'+' => \&add,
'-' => \&subtract,
'*' => \&multiply,
'/' => \&divide,
'+=' => \&not_implemented,
'-=' => \&not_implemented,
'*=' => \&not_implemented,
'/=' => \&not_implemented;

method add(AI::MXNet::NDArray|Num $other, $reverse=)
{
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@eric-haibin-lin eric-haibin-lin Mar 29, 2018

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I really appreciate your fast response @sergeykolychev thanks for unblocking us. While I'm not a perl user but some documentations for the new function will be great. Maybe worth adding next time

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@sergeykolychev sergeykolychev Mar 30, 2018 •
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Yeah, I'll add the docs next time with more substantial changes in April. Tried to unblock quickly. Though I don't see anybody using the functions directly and not via the overloaded operators.

if(blessed $other and join(',', @{ $self->shape }) eq join(',', @{ $other->shape }))
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/elemwise_add _plus_scalar/
);
}
else
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/broadcast_add _plus_scalar/
);
}
}


method subtract(AI::MXNet::NDArray|Num $other, $reverse=)
{
if(blessed $other and join(',', @{ $self->shape }) eq join(',', @{ $other->shape }))
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/elemwise_sub _minus_scalar _rminus_scalar/,
$reverse
);
}
else
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/broadcast_sub _minus_scalar _rminus_scalar/,
$reverse
);
}
}

method multiply(AI::MXNet::NDArray|Num $other, $reverse=)
{
if(blessed $other and join(',', @{ $self->shape }) eq join(',', @{ $other->shape }))
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/elemwise_mul _mul_scalar/,
);
}
else
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/broadcast_mul _mul_scalar/,
);
}
}

method divide(AI::MXNet::NDArray|Num $other, $reverse=)
{
if(blessed $other and join(',', @{ $self->shape }) eq join(',', @{ $other->shape }))
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/elemwise_div _div_scalar _rdiv_scalar/,
$reverse
);
}
else
{
return AI::MXNet::NDArray::_ufunc_helper(
$self,
$other,
qw/broadcast_div _div_scalar _rdiv_scalar/,
$reverse
);
}
}

{
no warnings 'redefine';
*_sync_copyfrom = *_at = *_slice = *reshape = *size = \&not_implemented;
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