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TM activeCells_ is a SDR #442

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TM activeCells_ is a SDR #442

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d3502c6
Revert "Revert "TM: activeCells_ is now a SDR""
breznak May 3, 2019
cd48099
Revert "Revert "TMRegion: fix testLinking fail""
breznak May 3, 2019
2911cd2
TM:getActiveCells() python return SDR
breznak May 3, 2019
e720007
fix Debug code
breznak May 5, 2019
34be516
Merge branch 'master_community' into tm_active_sdr
breznak May 5, 2019
b318d8a
Revert "fix Debug code"
breznak May 5, 2019
5230991
TM.activeCells as SDR: Fix for external predictive inputs.
ctrl-z-9000-times May 5, 2019
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24 changes: 10 additions & 14 deletions src/nupic/algorithms/TemporalMemory.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -298,7 +298,7 @@ static void growSynapses(Connections &connections,
}

static void activatePredictedColumn(
SDR &activeCellsSDR,
SDR &activeCellsSDR,
vector<CellIdx> &winnerCells,
Connections &connections,
Random &rng,
Expand Down Expand Up @@ -543,12 +543,12 @@ void TemporalMemory::activateDendrites(const bool learn,
{
NTA_CHECK( extraActive.size == extra_ );
NTA_CHECK( extraWinners.size == extra_ );
NTA_CHECK( extraActive.dimensions == extraWinners.dimensions);
#ifdef NTA_ASSERTIONS_ON
SDR both(extraActive.dimensions);
both.intersection(extraActive, extraWinners);
NTA_ASSERT(both == extraWinners) << "ExtraWinners must be a subset of ExtraActive";
#endif
NTA_CHECK( extraActive.dimensions == extraWinners.dimensions);
#ifdef NTA_ASSERTIONS_ON
SDR both(extraActive.dimensions);
both.intersection(extraActive, extraWinners);
NTA_ASSERT(both == extraWinners) << "ExtraWinners must be a subset of ExtraActive";
#endif
}
else
{
Expand All @@ -560,12 +560,8 @@ void TemporalMemory::activateDendrites(const bool learn,
if( segmentsValid_ )
return;

#ifdef NTA_ASSERTIONS_ON
for(const auto &active : extraActive.getSparse()) {
NTA_ASSERT( active < extra_ );
}
#endif
activeCells_.concatenate(activeCells_, extraActive);
SDR dendriteInputs({ activeCells_.size + extraActive.size });
dendriteInputs.concatenate(activeCells_.flatten(), extraActive.flatten());
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oh, thank you! I've totally forgot about this problem.


for(const auto &winner : extraWinners.getSparse()) {
NTA_ASSERT( winner < extra_ );
Expand All @@ -578,7 +574,7 @@ void TemporalMemory::activateDendrites(const bool learn,
numActivePotentialSynapsesForSegment_.assign(length, 0);
connections.computeActivity(numActiveConnectedSynapsesForSegment_,
numActivePotentialSynapsesForSegment_,
activeCells_.getSparse());
dendriteInputs.getSparse());

// Active segments, connected synapses.
activeSegments_.clear();
Expand Down
3 changes: 3 additions & 0 deletions src/nupic/types/Sdr.cpp
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Expand Up @@ -426,6 +426,9 @@ namespace sdr {
SDR::setDenseInplace();
}

Reshape SparseDistributedRepresentation::flatten() const
{ return Reshape(*this, {size} ); }
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do we want Reshape, or a plain SDR {size} + setSparse would do?

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That would work too, but it would copy the data. The Reshape class does not copy data.


bool SparseDistributedRepresentation::operator==(const SparseDistributedRepresentation &sdr) const {
// Check attributes
if( sdr.size != size or dimensions.size() != sdr.dimensions.size() )
Expand Down
4 changes: 4 additions & 0 deletions src/nupic/types/Sdr.hpp
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Expand Up @@ -42,6 +42,8 @@ using SDR_sparse_t = std::vector<ElemSparse>;
using SDR_coordinate_t = std::vector<std::vector<UInt>>;
using SDR_callback_t = std::function<void()>;

class Reshape; // Forward Declaration.

/**
* SparseDistributedRepresentation class
* Also known as "SDR" class
Expand Down Expand Up @@ -519,6 +521,8 @@ class SparseDistributedRepresentation : public Serializable
void concatenate(std::vector<const SparseDistributedRepresentation*> inputs,
UInt axis = 0u);

Reshape flatten() const;

/**
* Print a human readable version of the SDR.
*/
Expand Down