TM, SP: fix possible underflow in seed. Default random (0) seed.

bindings/py/cpp_src/bindings/algorithms/py_SpatialPooler.cpp

@@ -173,9 +173,9 @@ Argument boostStrength A number greater or equal than 0, used to
         too much boosting may also lead to instability of SP outputs.
 
 
-Argument seed Seed for our random number generator. If seed is < 0
+Argument seed Seed for our random number generator. If seed is 0
         a randomly generated seed is used. The behavior of the spatial
-        pooler is deterministic once the seed is set.
+        pooler is deterministic once the seed is set > 0.
 
 Argument spVerbosity spVerbosity level: 0, 1, 2, or 3
 
@@ -197,7 +197,7 @@ Argument wrapAround boolean value that determines whether or not inputs
             , py::arg("minPctOverlapDutyCycle") = 0.001
             , py::arg("dutyCyclePeriod") = 1000
             , py::arg("boostStrength") = 0.0
-            , py::arg("seed") = 1
+            , py::arg("seed") = 0
             , py::arg("spVerbosity") = 0
             , py::arg("wrapAround") = true
         );

bindings/py/cpp_src/bindings/algorithms/py_TemporalMemory.cpp

@@ -112,7 +112,8 @@ Argument predictedSegmentDecrement
     0.01 = 0.0004
 
 Argument seed
-    Seed for the random number generator.
+    Seed for the random number generator. Default (0) means truly random, 
+    > 0 is a fixed pseudorandom-sequence. See Random.hpp. 
 
 Argument maxSegmentsPerCell
     The maximum number of segments per cell.
@@ -146,7 +147,7 @@ Argument anomalyMode (optional, default ANMode::RAW) selects mode for `TM.anomal
                 , py::arg("permanenceIncrement") = 0.1
                 , py::arg("permanenceDecrement") = 0.1
                 , py::arg("predictedSegmentDecrement") = 0.0
-                , py::arg("seed") = 42
+                , py::arg("seed") = 0
                 , py::arg("maxSegmentsPerCell") = 255
                 , py::arg("maxSynapsesPerSegment") = 255
                 , py::arg("checkInputs") = true

src/examples/hello/HelloSPTP.cpp

@@ -72,8 +72,7 @@ EPOCHS = 2; // make test faster in Debug
   SpatialPooler  spLocal(enc.dimensions, vector<UInt>{COLS}); // Spatial pooler with local inh
   spGlobal.setGlobalInhibition(true);
   spLocal.setGlobalInhibition(false);
-  Random rnd(42); //uses fixed seed for deterministic output checks
-
+
   TemporalMemory tm(vector<UInt>{COLS}, CELLS);
 
   AnomalyLikelihood anLikelihood;
@@ -94,6 +93,12 @@ EPOCHS = 2; // make test faster in Debug
   Metrics statsSPglobal(outSPglobal, 1000);
   Metrics statsTM(outTM, 1000);
 
+  //uses fixed seed for deterministic output checks:
+  Random rnd(42);
+  spGlobal.setSeed(1);
+  spLocal.setSeed(1);
+  tm.setSeed(42);
+
   /*
    * For example: fn = sin(x) -> periodic >= 2Pi ~ 6.3 && x+=0.01 -> 630 steps to 1st period -> window >= 630
    */
@@ -201,7 +206,7 @@ EPOCHS = 2; // make test faster in Debug
 
       SDR goldSP({COLS});
       const SDR_sparse_t deterministicSP{
-        62, 72, 73, 82, 85, 102, 263, 277, 287, 303, 306, 308, 309, 322, 337, 339, 340, 352, 370, 493, 1094, 1095, 1114, 1115, 1120, 1463, 1512, 1518, 1647, 1651, 1691, 1694, 1729, 1745, 1746, 1760, 1770, 1774, 1775, 1781, 1797, 1798, 1803, 1804, 1805, 1812, 1827, 1828, 1831, 1832, 1858, 1859, 1860, 1861, 1862, 1875, 1878, 1880, 1881, 1898, 1918, 1923, 1929, 1931,1936, 1950, 1953, 1956, 1958, 1961, 1964, 1965, 1967, 1971, 1973, 1975, 1976, 1979, 1980, 1981, 1982, 1984, 1985, 1986, 1988, 1991, 1994, 1996, 1997, 1998, 1999, 2002, 2006, 2008, 2011, 2012, 2013, 2017, 2019, 2022, 2027, 2030
+        66, 70, 72, 75, 76, 82, 83, 85, 99, 297, 300, 301, 303, 305, 306, 308, 309, 311, 316, 320, 321, 323, 324, 325, 327, 329, 330, 343, 345, 347, 363, 508, 1084, 1110, 1112, 1115, 1120, 1131, 1522, 1532, 1535, 1634, 1684, 1697, 1732, 1769, 1777, 1778, 1800, 1801, 1803, 1817, 1818, 1823, 1830, 1834, 1836, 1844, 1847, 1851, 1855, 1859, 1860, 1862, 1866, 1882, 1886, 1897,1906, 1918, 1921, 1922, 1931, 1936, 1954, 1961, 1964, 1965, 1966, 1967, 1968, 1970, 1971, 1972, 1973, 1975, 1977, 1978, 1980, 1981, 1987, 1989, 1990, 2001, 2006, 2007, 2009, 2015, 2016, 2018, 2020, 2042
       };
       goldSP.setSparse(deterministicSP);
 

src/htm/algorithms/SpatialPooler.cpp

@@ -76,7 +76,7 @@ SpatialPooler::SpatialPooler(
     Real localAreaDensity, UInt numActiveColumnsPerInhArea,
     UInt stimulusThreshold, Real synPermInactiveDec, Real synPermActiveInc,
     Real synPermConnected, Real minPctOverlapDutyCycles, UInt dutyCyclePeriod,
-    Real boostStrength, Int seed, UInt spVerbosity, bool wrapAround)
+    Real boostStrength, UInt seed, UInt spVerbosity, bool wrapAround)
     : SpatialPooler::SpatialPooler()
 {
   // The current version number for serialzation.
@@ -381,7 +381,7 @@ void SpatialPooler::initialize(
     Real minPctOverlapDutyCycles, 
     UInt dutyCyclePeriod,
     Real boostStrength, 
-    Int seed, 
+    UInt seed, 
     UInt spVerbosity, 
     bool wrapAround) {
 

src/htm/algorithms/SpatialPooler.hpp

@@ -75,7 +75,7 @@ class SpatialPooler : public Serializable
     Real minPctOverlapDutyCycles = 0.001f,
     UInt dutyCyclePeriod = 1000u, 
     Real boostStrength = 0.0f,
-    Int seed = 1, 
+    UInt seed = 0u, //random
     UInt spVerbosity = 0u, 
     bool wrapAround = true);
 
@@ -200,9 +200,9 @@ class SpatialPooler : public Serializable
         too much boosting may also lead to instability of SP outputs.
 
 
-  @param seed Seed for our random number generator. If seed is < 0
+  @param seed Seed for our random number generator. If seed is 0,
         a randomly generated seed is used. The behavior of the spatial
-        pooler is deterministic once the seed is set.
+        pooler is deterministic once the seed is fixed to > 0.
 
   @param spVerbosity spVerbosity level: 0, 1, 2, or 3
 
@@ -220,10 +220,15 @@ class SpatialPooler : public Serializable
 	     Real localAreaDensity = 0.05f,
 	     UInt numActiveColumnsPerInhArea = 0,
              UInt stimulusThreshold = 0u,
-             Real synPermInactiveDec = 0.01f, Real synPermActiveInc = 0.1f,
-             Real synPermConnected = 0.1f, Real minPctOverlapDutyCycles = 0.001f,
-             UInt dutyCyclePeriod = 1000u, Real boostStrength = 0.0f,
-             Int seed = 1, UInt spVerbosity = 0u, bool wrapAround = true);
+             Real synPermInactiveDec = 0.01f, 
+	     Real synPermActiveInc = 0.1f,
+             Real synPermConnected = 0.1f, 
+	     Real minPctOverlapDutyCycles = 0.001f,
+             UInt dutyCyclePeriod = 1000u, 
+	     Real boostStrength = 0.0f,
+             UInt seed = 0u, 
+	     UInt spVerbosity = 0u, 
+	     bool wrapAround = true);
 
 
   /**
@@ -769,6 +774,13 @@ class SpatialPooler : public Serializable
   */
   void getConnectedCounts(UInt connectedCounts[]) const;
 
+  /** set seed for internal random number generator. 
+   * See @ref `seed` arg in the constructor.
+   */
+  void setSeed(UInt seed) {
+    rng_ = Random(seed);
+  }
+
 
   /**
   Returns the boosted overlap score for each column.

src/htm/algorithms/TemporalMemory.cpp

@@ -63,7 +63,7 @@ TemporalMemory::TemporalMemory(
     Permanence permanenceIncrement, 
     Permanence permanenceDecrement,
     Permanence predictedSegmentDecrement, 
-    Int seed, 
+    UInt seed, 
     SegmentIdx maxSegmentsPerCell,
     SynapseIdx maxSynapsesPerSegment, 
     bool checkInputs, 
@@ -90,7 +90,7 @@ void TemporalMemory::initialize(
     Permanence permanenceIncrement, 
     Permanence permanenceDecrement,
     Permanence predictedSegmentDecrement, 
-    Int seed, 
+    UInt seed, 
     SegmentIdx maxSegmentsPerCell,
     SynapseIdx maxSynapsesPerSegment, 
     bool checkInputs, 

src/htm/algorithms/TemporalMemory.hpp

@@ -104,7 +104,8 @@ class TemporalMemory : public Serializable
    * something like 4% * 0.01 = 0.0004).
    *
    * @param seed
-   * Seed for the random number generator.
+   * Seed for the random number generator. 0 (default) means truly random, 
+   * use > 0 for fixed pseudo-random. 
    *
    * @param maxSegmentsPerCell
    * The maximum number of segments per cell.
@@ -144,7 +145,7 @@ class TemporalMemory : public Serializable
       Permanence      permanenceIncrement         = 0.10,
       Permanence      permanenceDecrement         = 0.10,
       Permanence      predictedSegmentDecrement   = 0.0,
-      Int             seed                        = 42,
+      UInt            seed                        = 0, //random
       SegmentIdx      maxSegmentsPerCell          = 255,
       SynapseIdx      maxSynapsesPerSegment       = 255,
       bool            checkInputs                 = true,
@@ -164,7 +165,7 @@ class TemporalMemory : public Serializable
     Permanence    permanenceIncrement         = 0.10,
     Permanence    permanenceDecrement         = 0.10,
     Permanence    predictedSegmentDecrement   = 0.0,
-    Int           seed                        = 42,
+    UInt          seed                        = 0,
     SegmentIdx    maxSegmentsPerCell          = 255,
     SynapseIdx    maxSynapsesPerSegment       = 255,
     bool          checkInputs                 = true,
@@ -595,6 +596,10 @@ class TemporalMemory : public Serializable
   virtual bool operator==(const TemporalMemory &other) const;
   inline bool operator!=(const TemporalMemory &other) const { return not this->operator==(other); }
 
+  void setSeed(UInt seed) {
+    rng_ = Random(seed);
+  }
+
   //----------------------------------------------------------------------
   // Debugging helpers
   //----------------------------------------------------------------------
@@ -638,6 +643,9 @@ class TemporalMemory : public Serializable
    *
    */
   SDR cellsToColumns(const SDR& cells) const;
+
+
+
 private:
   void punishPredictedColumn_(vector<Segment>::const_iterator columnMatchingSegmentsBegin, 
 		              vector<Segment>::const_iterator columnMatchingSegmentsEnd, 

src/htm/regions/RDSEEncoderRegion.cpp

@@ -68,7 +68,7 @@ namespace htm {
 
 
 RDSEEncoderRegion::RDSEEncoderRegion(const ValueMap &par, Region *region) : RegionImpl(region) {
-  rnd_ = Random(42);
+  rnd_ = Random(42); //TODO use seed value here?
   spec_.reset(createSpec());
   ValueMap params = ValidateParameters(par, spec_.get());
 
@@ -78,8 +78,8 @@ RDSEEncoderRegion::RDSEEncoderRegion(const ValueMap &par, Region *region) : Regi
   args.sparsity =   params.getScalarT<Real32>("sparsity");
   args.radius =     params.getScalarT<Real32>("radius");
   args.resolution = params.getScalarT<Real32>("resolution");
-  args.category =   params.getScalarT<bool>("category");
-  args.seed =       params.getScalarT<UInt32>("seed");
+  args.category =   params.getScalarT<bool>("category", false);
+  args.seed =       params.getScalarT<UInt32>("seed", 0);
 
   encoder_ = std::make_shared<RandomDistributedScalarEncoder>(args);
   sensedValue_ = params.getScalarT<Real64>("sensedValue");

src/htm/regions/SPRegion.cpp

@@ -55,7 +55,7 @@ SPRegion::SPRegion(const ValueMap &values, Region *region)
   args_.minPctOverlapDutyCycles = values.getScalarT<Real32>("minPctOverlapDutyCycles", 0.001f);
   args_.dutyCyclePeriod = values.getScalarT<UInt32>("dutyCyclePeriod", 1000);
   args_.boostStrength = values.getScalarT<Real32>("boostStrength", 0.0f);
-  args_.seed = values.getScalarT<Int32>("seed", 1);
+  args_.seed = values.getScalarT<Int32>("seed", 0u);
   args_.spVerbosity = values.getScalarT<UInt32>("spVerbosity", 0);
   args_.wrapAround = values.getScalarT<bool>("wrapAround", true);
   spatialImp_ = values.getString("spatialImp", "");
@@ -452,11 +452,11 @@ Spec *SPRegion::createSpec() {
       "seed",
       ParameterSpec(
           "(int)\n"
-          "Seed for our own pseudo - random number generator. Default ``-1``.",
+          "Seed for our own pseudo - random number generator. Default ``0``(=random), >0 means fixed.",
           NTA_BasicType_Int32,           // type
           1,                             // elementCount
           "",                            // constraints
-          "1",                          // defaultValue
+          "0",                           // defaultValue
           ParameterSpec::CreateAccess)); // access
 
   ns->parameters.add(

src/htm/regions/SPRegion.hpp

@@ -174,7 +174,7 @@ class SPRegion  : public RegionImpl, Serializable
       Real minPctOverlapDutyCycles;
       UInt dutyCyclePeriod;
       Real boostStrength;
-      Int  seed;
+      UInt seed;
       UInt spVerbosity;
       bool wrapAround;
       bool learningMode;

src/htm/regions/TMRegion.cpp

@@ -52,7 +52,7 @@ TMRegion::TMRegion(const ValueMap &params, Region *region)
   args_.permanenceIncrement = params.getScalarT<Real32>("permanenceIncrement", 0.10f);
   args_.permanenceDecrement = params.getScalarT<Real32>("permanenceDecrement", 0.10f);
   args_.predictedSegmentDecrement = params.getScalarT<Real32>("predictedSegmentDecrement", 0.0f);
-  args_.seed = params.getScalarT<Int32>("seed", 42);
+  args_.seed = params.getScalarT<Int32>("seed", 0);
   args_.maxSegmentsPerCell = params.getScalarT<UInt32>("maxSegmentsPerCell", 255u);
   args_.maxSynapsesPerSegment = params.getScalarT<UInt32>("maxSynapsesPerSegment", 255u);
   args_.checkInputs = params.getScalarT<bool>("checkInputs", true);
@@ -416,11 +416,11 @@ Spec *TMRegion::createSpec() {
       "seed",
       ParameterSpec("(int)  Random number generator seed. The seed affects the random "
                     "aspects of initialization like the initial permanence values. A "
-                    "fixed value ensures a reproducible result.",
+                    "fixed value > 0 ensures a reproducible result.",
                     NTA_BasicType_Int32,              // type
                     1,                                // elementCount
                     "",                               // constraints
-                    "42",                             // defaultValue
+                    "0",                             // defaultValue
                     ParameterSpec::CreateAccess)); // access
 
   ///////// Parameters not part of the calling arguments //////////

src/htm/regions/TMRegion.hpp

@@ -165,7 +165,7 @@ class TMRegion : public RegionImpl, Serializable {
     Real32 permanenceIncrement;
     Real32 permanenceDecrement;
     Real32 predictedSegmentDecrement;
-    Int32 seed;
+    UInt32 seed;
     Int32 maxSegmentsPerCell;
     Int32 maxSynapsesPerSegment;
     UInt32 externalPredictiveInputs;

src/test/unit/algorithms/SpatialPoolerTest.cpp

@@ -1944,27 +1944,24 @@ TEST(SpatialPoolerTest, testSerialization_ar) {
 
   SpatialPooler sp1;
   sp1.initialize(inputDims, colDims);
+  sp1.setSeed(1);
 
   SDR input(inputDims);
   SDR output(colDims);
 
+  //burn-in the SP
   for (UInt i = 0; i < 100; ++i) {
     input.randomize(0.05f, random); //5% random ON
     sp1.compute(input, true, output);
   }
 
-  // Now we reuse the last input to test after serialization
-
-  auto activeColumnsBefore = output.getSparse();
 
   // Save initial trained model
   stringstream ss;
 	ss.precision(std::numeric_limits<double>::digits10 + 1);
 	ss.precision(std::numeric_limits<float>::digits10 + 1);
   sp1.save(ss);
 
-  SpatialPooler sp2;
-
   htm::Timer testTimer;
 
   for (UInt i = 0; i < 6; ++i) {
@@ -1975,26 +1972,26 @@ TEST(SpatialPoolerTest, testSerialization_ar) {
     SDR outputBaseline(output);
     sp1.compute(input, true, outputBaseline);
 
-    // C - Next do old version
+    // C - Next, verify the same results come from the de/serialized version
     {
       SpatialPooler spTemp;
       testTimer.start();
 
       // Deserialize
       ss.seekg(0);
-      spTemp.load(ss);
+      EXPECT_NO_THROW(spTemp.load(ss));
 
       // Feed new record through
       SDR outputC({numColumns});
       spTemp.compute(input, true, outputC);
 
       // Serialize
       ss.clear();
-      spTemp.save(ss);
+      EXPECT_NO_THROW(spTemp.save(ss));
 
       testTimer.stop();
 
-      EXPECT_EQ(outputBaseline, outputC);
+      EXPECT_EQ(outputBaseline, outputC); //FIXME this test randomly fails. (De/serialization of rng_ is correct?) 
     }
   }
   ss.clear();

src/test/unit/engine/CppRegionTest.cpp

@@ -111,7 +111,7 @@ TEST(CppRegionTest, testCppLinkingSDR) {
   Network net;
 
   std::shared_ptr<Region> region1 = net.addRegion("region1", "ScalarEncoderRegion", "{dim: [6,1], n: 6, w: 2}");
-  std::shared_ptr<Region> region2 = net.addRegion("region2", "SPRegion", "{dim: [20,3]}");
+  std::shared_ptr<Region> region2 = net.addRegion("region2", "SPRegion", "{dim: [20,3], seed: 1}"); //seed is fixed for deterministic results in tests
 
   net.link("region1", "region2");
 

src/test/unit/regions/ClassifierRegionTest.cpp

@@ -101,7 +101,7 @@ TEST(ClassifierRegionTest, asCategoryDecoder) {
   Network net;
 
   std::shared_ptr<Region> encoder = net.addRegion("encoder", "RDSEEncoderRegion", "{size: 400, seed: 42, category: true, activeBits: 40}");
-  std::shared_ptr<Region> sp = net.addRegion("sp", "SPRegion", "{columnCount: 1000, globalInhibition: true}");
+  std::shared_ptr<Region> sp = net.addRegion("sp", "SPRegion", "{columnCount: 1000, globalInhibition: true, seed: 1}");
   std::shared_ptr<Region> classifier = net.addRegion("classifier", "ClassifierRegion", "{learn: true}");
 
   net.link("encoder", "sp", "", "", "encoded", "bottomUpIn");
@@ -144,7 +144,7 @@ TEST(ClassifierRegionTest, asRealDecoder) {
   Network net;
 
   std::shared_ptr<Region> encoder = net.addRegion("encoder", "RDSEEncoderRegion", "{size: 400, radius: 0.1, seed: 42, activeBits: 40}");
-  std::shared_ptr<Region> sp = net.addRegion("sp", "SPRegion", "{columnCount: 1000, globalInhibition: true}");
+  std::shared_ptr<Region> sp = net.addRegion("sp", "SPRegion", "{columnCount: 1000, globalInhibition: true, seed: 1}");
   std::shared_ptr<Region> classifier = net.addRegion("classifier", "ClassifierRegion", "{learn: true}");
 
   net.link("encoder", "sp", "", "", "encoded", "bottomUpIn");
@@ -244,4 +244,4 @@ TEST(ClassifierRegionTest, testSerialization) {
   Directory::removeTree("TestOutputDir", true);
 }
 
-} // namespace testing
+} // namespace testing