Reduce
#include <popops/Reduce.hpp>
Define types of operations used in a reduce.

namespace popops
Common functions, such as elementwise and reductions.
map
Map an expression across tensors.
Elementwise Options
enableGenerateCodelet
(true, false) [=true]When true and the following conditions are met, poplar will generate a codelet to execute the map operation. Otherwise, it will sequence poplibs codelets to create the expression.
All of the inputs are of the same size
Inputs do not alias
Multiple operations are being performed
mapInPlace
Update the input tensors with the result of map().
mapWithOutput
Write the result of map() to the given output tensor.
checkTypes
Check that the host compiletime type
constType
is compatible with the runtime IPU typeelementType
. param elementType
The runtime IPU type.
 param constant
Unused.
 tparam constType
The host compiletime type.
 throws std::runtime_error
If the types are not compatible.
varianceToInvStdDev
Convert variance to inverse standard deviation.
Each element in the output tensor is the result of
1 / sqrt(variance_value + epsilon)
, wherevariance_value
is the corresponding element invariance
.Warning
If
variance_value + epsilon
is zero then the result will be invalid and this operation could generate a dividebyzero floatingpoint exception (if enabled). param graph
The graph to update.
 param variance
A tensor of variance values.
 param epsilon
A (typically small) scalar to add to the variance values, to avoid numerical issues (for example, divide by zero).
 param prog
The sequence of programs to append this conversion operation to.
 param debugContext
Optional debug information.
 return
A tensor where each element is the inverse standard deviation.
invStdDevToVariance
Convert inverse standard deviation to variance.
Each element in the output tensor is the result of
1 / (invStdDev_value + epsilon)^2
, whereinvStdDev_value
is the corresponding element ininvStdDev
.Warning
If
invStdDev_value + epsilon
is zero then the result will be invalid and this operation could generate a dividebyzero floatingpoint exception (if enabled). param graph
The graph to update.
 param invStdDev
A tensor of inverse standard deviation values.
 param epsilon
A (typically small) scalar to add to the variance values, to avoid numerical issues (for example, divide by zero).
 param prog
The sequence of programs to append this conversion operation to.
 param debugContext
Optional debug information.
 param options
A list of flags to pass to the expression evaluator.
 return
A tensor where each element is the variance.
add
Add each element in
A
to the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a + b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
addInPlace
Update the tensor
A
with the result of add().See add() for parameter descriptions.
addWithOutput
Write the result of add() to the given output tensor,
out
.See add() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
sub
Subtract the elements of
B
fromA
and return the result in a new tensor. param graph
The graph to update.
 param A
The tensor of elements which will be subtracted from.
 param B
The tensor of elements to subtract from
A
. param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is equal to a  b, where
a
andb
are the corresponding elements ofA
andB
tensors respectively.
subInPlace
Update the tensor
A
with the result of sub().See sub() for parameter descriptions.
subWithOutput
Write the result of sub() to the given output tensor,
out
.See sub() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
mul
Multiply each element in
A
by the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a * b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
mulInPlace
Update the tensor
A
with the result of mul().See mul() for parameter descriptions.
mulWithOutput
Write the result of mul() to the given output tensor,
out
.See mul() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
div
Divide each element in
A
by the corresponding element inB
. param graph
The graph to update.
 param A
The tensor of dividends.
 param B
The tensor of divisors.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a / b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
divInPlace
Update the tensor
A
with the result of div().See div() for parameter descriptions.
divWithOutput
Write the result of div() to the given output tensor,
out
.See div() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
pow
Compute each element in
A
to the power of the corresponding element inB
. param graph
The graph to update.
 param A
The tensor of bases.
 param B
The tensor of exponents.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is equal to
pow(a, b)
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
powInPlace
Update the tensor
A
with the result of pow().See pow() for parameter descriptions.
powWithOutput
Write the result of pow() to the given output tensor,
out
.See pow() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
rem
Compute the remainder of each element in
A
divided by the corresponding element inB
. param graph
The graph to update.
 param A
The tensor of dividends.
 param B
The tensor of divisors.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is equal to a % b, where
a
andb
are the corresponding elements ofA
andB
tensors respectively.
remInPlace
Update the tensor
A
with the result of rem().See rem() for parameter descriptions.
remWithOutput
Write the result of rem() to the given output tensor,
out
.See rem() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
bitwiseAnd
Compute the bitwise AND of each element in
A
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a & b
, wherea
andbare
the corresponding elements ofA
andB
tensors respectively.
bitwiseAndInPlace
Update the tensor
A
with the result of bitwiseAnd().See bitwiseAnd() for parameter descriptions.
bitwiseAndWithOutput
Write the result of bitwiseAnd() to the given output tensor,
out
.See bitwiseAnd() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
bitwiseOr
Compute the bitwise OR of each element in
A
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a  b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
bitwiseOrInPlace
Update the tensor
A
with the result of bitwiseOr().See bitwiseOr() for parameter descriptions.
bitwiseOrWithOutput
Write the result of bitwiseOr() to the given output tensor,
out
.See bitwiseOr() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
bitwiseXor
Compute the bitwise XOR of each element in
A
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a ^ b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
bitwiseXorInPlace
Update the tensor
A
with the result of bitwiseXor().See bitwiseXnor() for parameter descriptions.
bitwiseXorWithOutput
Write the result of bitwiseXor() to the given output tensor,
out
.See bitwiseXor() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
bitwiseXnor
Compute the bitwise XNOR of each element in
A
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
!(a ^ b)
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
bitwiseXnorInPlace
Update the tensor
A
with the result of bitwiseXnor().See bitwiseXnor() for parameter descriptions.
bitwiseXnorWithOutput
Write the result of bitwiseXnor() to the given output tensor,
out
.See bitwiseXnor() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
shiftLeft
Shift the elements of
A
left by the corresponding elements ofB
. param graph
The graph to update.
 param A
The tensor of elements which to leftshift.
 param B
The tensor of elements that describe the amount to leftshift
A
by. param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is equal to a << b, where
a
andb
are the corresponding elements ofA
andB
tensors respectively.
shiftLeftInPlace
Update the tensor
A
with the result of shiftLeft().See shiftLeft() for parameter descriptions.
shiftLeftWithOutput
Write the result of shiftLeft() to the given output tensor,
out
.See shiftLeft() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
shiftRight
Shift the elements of
A
right by the corresponding elements ofB
. param graph
The graph to update.
 param A
The tensor of elements which to rightshift.
 param B
The tensor of elements that describe the amount to rightshift by.
A
. param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is equal to a >> b (without sign extension), where
a
andb
are the corresponding elements ofA
andB
tensors respectively.
shiftRightInPlace
Update the tensor
A
with the result of shiftRight().See shiftRight() for parameter descriptions.
shiftRightWithOutput
Write the result of shiftRight() to the given output tensor,
out
.See shiftRight() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
shiftRightSignExtend
Shift the elements of
A
right with sign extension by the corresponding elements ofB
. param graph
The graph to update.
 param A
The tensor of elements which to rightshift.
 param B
The tensor of elements that describe the amount to rightshift
A
by. param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is equal to
a >> b
with sign extension, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
shiftRightSignExtendInPlace
Update the tensor
A
with the result of shiftRightSignExtend().See shiftRightSignExtend() for parameter descriptions.
shiftRightSignExtendWithOutput
Write the result of shiftRightSignExtend() to the given output tensor,
out
.See shiftRightSignExtend() for the remaining parameter descriptions.
 param out
The tensor to write the results to.
logicalAnd
Compute the logical AND (
&&
) of each element inA
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a && b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
logicalAndInPlace
Update the tensor
A
with the result of logicalAnd().See logicalAnd() for parameter descriptions.
logicalAndWithOutput
Write the result of logicalAnd() to the given output tensor,
out
.See logicalAnd() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
logicalOr
Compute the logical OR (

) of each element inA
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a  b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
logicalOrInPlace
Update the tensor
A
with the result of logicalOr().See logicalOr() for parameter descriptions.
logicalOrWithOutput
Write the result of logicalOr() to the given output tensor,
out
.See logicalOr() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
eq
Check if each element in
A
is equal to the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a == b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
eqInPlace
Update the tensor
A
with the result of eq().See eq() for parameter descriptions.
eqWithOutput
Write the result of eq() to the given output tensor,
out
.See eq() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
neq
Check if each element in
A
is not equal to the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a != b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
neqInPlace
Update the tensor
A
with the result of neq().See neq() for parameter descriptions.
neqWithOutput
Write the result of neq() to the given output tensor,
out
.See neq() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
gteq
Check if each element in
A
is greater than or equal to the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a >= b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
gteqInPlace
Update the tensor
A
with the result of gteq().See gteq() for parameter descriptions.
gteqWithOutput
Write the result of gteq() to the given output tensor,
out
.See gteq() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
gt
Check if each element in
A
is greater than the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a > b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
gtInPlace
Update the tensor
A
with the result of gt().See gt() for parameter descriptions.
gtWithOutput
Write the result of gt() to the given output tensor,
out
.See gt() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
lteq
Check if each element in
A
is less than or equal to the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a <= b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
lteqInPlace
Update the
A
with the result of lteq().See lteq() for parameter descriptions.
lteqWithOutput
Write the result of lteq() to the given output tensor,
out
.See lteq() for the remaining parameter descriptions.
 param out
The tensor to write the booleans to.
lt
Check if each element in
A
is less than the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
a < b
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
ltInPlace
Update the
A
with the result of lt().See lt() for parameter descriptions.
ltWithOutput
Write the result of lt() to the given output tensor,
out
.See lt() for the remaining parameter descriptions.
 param out
The tensor to write the boolean results to.
max
Compute the maximum of each element in
A
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
max(a, b)
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
maxWithOutput
Write the result of max() to the given output tensor,
out
.See max() for the remaining parameter descriptions.
 param out
The tensor to write the maximums to.
min
Compute the minimum of each element in
A
with the corresponding element inB
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information.
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
min(a, b)
, wherea
andb
are the corresponding elements ofA
andB
tensors respectively.
minWithOutput
Write the result of min() to the given output tensor,
out
.See min() for the remaining parameter descriptions.
 param out
The tensor to write the minimums to.
atan2
Compute the elementwise arctangent of
A / B
. param graph
The graph to update.
 param A
A tensor of elements.
 param B
A tensor of elements.
 param prog
The sequence to extend with the execution of the expression evaluation.
 param debugContext
Optional debug information
 param options
Elementwise options. See map().
 return
A tensor where each element is the result of
arctan(a / b)
;a
andb
are the corresponding elements ofA
andB
tensors respectively.
atan2InPlace
Update the tensor
A
with the result of atan2().See atan2() for parameter descriptions.
atan2WithOutput
Write the result of atan2() to the given output tensor,
out
.See atan2() for the remaining parameter descriptions.
 param out
The tensor to write the result to.
invStdDevToVarianceInPlace
Update the
invStdDev
tensor with the result of invStdDevToVariance().See invStdDevToVariance() for parameter descriptions.
invStdDevToVarianceWithOutput
Write the result of invStdDevToVariance() to the given output tensor,
out
.See invStdDevToVariance() for the remaining parameter descriptions.
 param out
The tensor to write the variance to.
varianceToInvStdDevInPlace
Update the
variance
tensor with the result of varianceToInvStdDev().See varianceToInvStdDev() for parameter descriptions.
varianceToInvStdDevWithOutput
Write the result of varianceToInvStdDev() to the given output tensor,
out
.See varianceToInvStdDev() for the remaining parameter descriptions.
 param out
The tensor to write inverse standard deviation to.
Unnamed Group

poplar::Tensor reduce(poplar::Graph &graph, const poplar::Tensor &in, const poplar::Type &outType, const std::vector<std::size_t> &dims, ReduceParams params, std::vector<poplar::ComputeSet> &css, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})
Apply a reduction operation to a tensor.
 Deprecated:
The reduce overloads that expect a vector of compute sets are deprecated. Please use the reduceMany() function instead.
These are alternate forms that add their vertices to a vector of compute sets instead of a poplar::program::Sequence. The caller is expected to add each compute set to a poplar::program::Sequence (in a poplar::program::Execute) themselves, like this:
Sequence seq; std::vector<ComputeSet> css; auto A = reduce(..., css); auto B = reduce(..., css); for (const auto &cs : css) { seq.add(Execute(cs));
This allows you to do multiple reductions in parallel. Note that the reductions are not aware of each other, so it may be more efficient to concatenate tensors and do a single reduction instead if they have the same shape, operation, and input and output types.
scale
andupdate
are only valid with theADD
,SQUARE_ADD
orLOG_ADD
operations.LOG_ADD
performs all arithmetic consistent with the input and output being log probabilities. In other words, theupdate
is another log add operation and thescale
is a log multiply operation.Internally, this creates a new variable for the output then calls reduceWithOutput(). The type of the output will be
outType
.The options parameter accepts the following:
accumType.interTile (float, half)
The type to use for intermediate values between tiles. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
accumType.inVertex (float, half)
The type to use for intermediate values within a vertex. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
If either of the above options are not set then the intermediate type will default to either the input tensor element type or float if the input is of type half and the reduction operation benefits from higher precision (for example, add).
The input and output types that are supported depend on the operation:
ADD
,SQUARE_ADD
,MUL
: float>float, half>half, int>int, float>half, half>floatLOG_ADD
: float>float, half>half, float>half, half>floatMAX
,MIN
: float>float, half>half, int>intLOGICAL_AND
,LOGICAL_OR
: bool>bool
 Parameters
graph – The graph to add the operation to.
in – The tensor to be reduced.
outType – The output type of the reduce operation.
dims – The dimensions to reduce in.
prog – The program sequence to add the operation to.
debugContext – Optional debug information.

poplar::Tensor reduce(poplar::Graph &graph, const poplar::Tensor &in, const std::vector<std::size_t> &dims, ReduceParams params, std::vector<poplar::ComputeSet> &css, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})

void reduceWithOutput(poplar::Graph &graph, const poplar::Tensor &in, const poplar::Tensor &out, const std::vector<std::size_t> &dims, ReduceParams params, std::vector<poplar::ComputeSet> &css, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})
Functions

poplar::Tensor reduce(poplar::Graph &graph, const poplar::Tensor &in, const poplar::Type &outType, const std::vector<std::size_t> &dims, ReduceParams params, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})
Apply a reduction operation to a tensor.
scale
andupdate
are only valid with theADD
,SQUARE_ADD
orLOG_ADD
operations.LOG_ADD
performs all arithmetic consistent with the input and output being log probabilities. In other words, theupdate
is another log add operation and thescale
is a log multiply operation.Internally, this creates a new variable for the output then calls reduceWithOutput(). The type of the output will be
outType
.The options parameter accepts the following:
accumType.interTile (float, half)
The type to use for intermediate values between tiles. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
accumType.inVertex (float, half)
The type to use for intermediate values within a vertex. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
If either of the above options are not set then the intermediate type will default to either the input tensor element type or float if the input is of type half and the reduction operation benefits from higher precision (for example, add).
The input and output types that are supported depend on the operation:
ADD
,SQUARE_ADD
,MUL
: float>float, half>half, int>int, float>half, half>floatLOG_ADD
: float>float, half>half, float>half, half>floatMAX
,MIN
: float>float, half>half, int>intLOGICAL_AND
,LOGICAL_OR
: bool>bool
 Parameters
graph – The graph to add the operation to.
in – The tensor to be reduced.
outType – The output type of the reduce operation.
dims – The dimensions to reduce in.
prog – The program sequence to add the operation to.
debugContext – Optional debug information.

poplar::Tensor reduce(poplar::Graph &graph, const poplar::Tensor &in, const std::vector<std::size_t> &dims, ReduceParams params, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})
Apply a reduction operation to a tensor.
An alias for reduce(graph, in, in.elementType(), …)
scale
andupdate
are only valid with theADD
,SQUARE_ADD
orLOG_ADD
operations.LOG_ADD
performs all arithmetic consistent with the input and output being log probabilities. In other words, theupdate
is another log add operation and thescale
is a log multiply operation.Internally, this creates a new variable for the output then calls reduceWithOutput(). The type of the output will be
outType
.The options parameter accepts the following:
accumType.interTile (float, half)
The type to use for intermediate values between tiles. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
accumType.inVertex (float, half)
The type to use for intermediate values within a vertex. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
If either of the above options are not set then the intermediate type will default to either the input tensor element type or float if the input is of type half and the reduction operation benefits from higher precision (for example, add).
The input and output types that are supported depend on the operation:
ADD
,SQUARE_ADD
,MUL
: float>float, half>half, int>int, float>half, half>floatLOG_ADD
: float>float, half>half, float>half, half>floatMAX
,MIN
: float>float, half>half, int>intLOGICAL_AND
,LOGICAL_OR
: bool>bool
 Parameters
graph – The graph to add the operation to.
in – The tensor to be reduced.
outType – The output type of the reduce operation.
dims – The dimensions to reduce in.
prog – The program sequence to add the operation to.
debugContext – Optional debug information.

void reduceWithOutput(poplar::Graph &graph, const poplar::Tensor &in, const poplar::Tensor &out, const std::vector<std::size_t> &dims, ReduceParams params, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})
Apply a reduction operation to a tensor.
This is similar to reduce() but allows you to specify the output. If the tile mapping of
out
is not complete it will be set. Otherwise it won’t be changed.scale
andupdate
are only valid with theADD
,SQUARE_ADD
orLOG_ADD
operations.LOG_ADD
performs all arithmetic consistent with the input and output being log probabilities. In other words, theupdate
is another log add operation and thescale
is a log multiply operation.Internally, this creates a new variable for the output then calls reduceWithOutput(). The type of the output will be
outType
.The options parameter accepts the following:
accumType.interTile (float, half)
The type to use for intermediate values between tiles. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
accumType.inVertex (float, half)
The type to use for intermediate values within a vertex. If the type specified is smaller than the output type then the option is ignored and the output type is used instead.
If either of the above options are not set then the intermediate type will default to either the input tensor element type or float if the input is of type half and the reduction operation benefits from higher precision (for example, add).
The input and output types that are supported depend on the operation:
ADD
,SQUARE_ADD
,MUL
: float>float, half>half, int>int, float>half, half>floatLOG_ADD
: float>float, half>half, float>half, half>floatMAX
,MIN
: float>float, half>half, int>intLOGICAL_AND
,LOGICAL_OR
: bool>bool
 Parameters
graph – The graph to add the operation to.
in – The tensor to be reduced.
outType – The output type of the reduce operation.
dims – The dimensions to reduce in.
prog – The program sequence to add the operation to.
debugContext – Optional debug information.

void reduceMany(poplar::Graph &graph, const std::vector<SingleReduceOp> &reductions, std::vector<poplar::Tensor> &outputs, poplar::program::Sequence &prog, const poplar::DebugContext &debugContext = {}, const poplar::OptionFlags &options = {})
Perform many reductions (in parallel if possible).
Please see the documentation for reduce() for details of the common inputs.
 Parameters
reductions – The inputs to each reduction to perform. The
outType
attribute controls the element type of the output tensor ifoutputs
is empty, otherwise it is ignored. Ifoutputs
is empty anduseOutType
isfalse
then the output element type will be set to the same element type as the correspondingin
tensor.outputs – The tensors to store the output of the reductions. This may be empty in which case
reduceMany
will create the tensors. If the tile mapping is not set or not complete it will be set completely by this function.
 Throws
poputils::poplibs_error – If
outputs
is not empty then its size must exactly match the size of reductions else an exception will be thrown.poputils::poplibs_error – If
outputs
is empty and any reduction hasparams.update
set to true then an exception will be thrown.outputs
is required to perform an update reduction.

struct ReduceParams
 #include <Reduce.hpp>
Stores parameters for the reduce operation, as well as the basic operation being performed (for example,
add
ormul
).Public Functions

ReduceParams() = default

inline ReduceParams(popops::Operation op, bool update, poplar::Tensor scale)
Define the details of the reduce operation that will be performed by the reduce() and reduceWithOutput() functions.
 Parameters
op – The reduce operation to use.
scale – Can (optionally) scale the output.
update – Specify that the output should be updated, where
out += reduce(in)
rather thanout = reduce(in)
.

ReduceParams() = default

struct SingleReduceOp
 #include <Reduce.hpp>
The parameterisation of the inputs to a single reduction for the reduceMany() function.
Please see the documentation for reduce() for a description of the struct members.
Public Functions
Public Members

ReduceParams params

bool useOutType
Note that if
useOutType
isfalse
then the element type ofin
is used.Also note that
OutType
is ignored if theoutputs
vector is not empty when calling reduceMany().

ReduceParams params