Changeset 17493

Timestamp:

04/02/20 13:13:38 (4 years ago)

Author:

pfleck

Message:

#3040 Write optimized constants back to tree.

Location:

branches/3040_VectorBasedGP

Files:

• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/TensorFlowConstantOptimizationEvaluator.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/TreeToTensorConverter.cs (modified) (1 diff)

branches/3040_VectorBasedGP/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/TensorFlowConstantOptimizationEvaluator.cs

@@ -111 +111 @@
         out Dictionary<Tensor, string> parameters, out List<Tensor> variables/*, out double[] initialConstants*/);
 
+      if (!success)
+        return (ISymbolicExpressionTree)tree.Clone();
+
 #if EXPLICIT_SHAPE
       var target = tf.placeholder(tf.float64, new TensorShape(numRows, 1), name: problemData.TargetVariable);
@@ -143 +146 @@
       variablesFeed.Add(target, np.array(targetData, copy: false).reshape(numRows, 1));
 
+      List<NDArray> constants;
       using (var session = tf.Session()) {
         session.run(tf.global_variables_initializer());
@@ -162 +166 @@
             Trace.WriteLine($"{v.name}: {session.run(v).ToString(true)}");
         }
+
+        constants = variables.Select(v => session.run(v)).ToList();
       }
 
-      if (!success)
-        return (ISymbolicExpressionTree)tree.Clone();
+      if (applyLinearScaling)
+        constants = constants.Skip(2).ToList();
+      var newTree = (ISymbolicExpressionTree)tree.Clone();
+      UpdateConstants(newTree, constants, updateVariableWeights);
 
+      return newTree;
+    }
 
-      return null;
+    private static void UpdateConstants(ISymbolicExpressionTree tree, IList<NDArray> constants, bool updateVariableWeights) {
+      int i = 0;
+      foreach (var node in tree.Root.IterateNodesPrefix().OfType<SymbolicExpressionTreeTerminalNode>()) {
+        if (node is ConstantTreeNode constantTreeNode)
+          constantTreeNode.Value = constants[i++].GetDouble(0, 0);
+        else if (node is VariableTreeNodeBase variableTreeNodeBase && updateVariableWeights)
+          variableTreeNodeBase.Weight = constants[i++].GetDouble(0, 0);
+        else if (node is FactorVariableTreeNode factorVarTreeNode && updateVariableWeights) {
+          for (int j = 0; j < factorVarTreeNode.Weights.Length; j++)
+            factorVarTreeNode.Weights[j] = constants[i++].GetDouble(0, 0);
+        }
+      }
     }
 

branches/3040_VectorBasedGP/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/TreeToTensorConverter.cs

@@ -288 +288 @@
 
           var alpha_arr = np.array(1.0).reshape(1, 1);
-          var alpha = tf.Variable(alpha_arr, name: $"alpha", dtype: tf.float64);
-          var beta_arr = np.array(1.0).reshape(1, 1);
-          var beta = tf.Variable(beta_arr, name: $"beta", dtype: tf.float64);
+          var alpha = tf.Variable(alpha_arr, name: "alpha", dtype: tf.float64);
+          var beta_arr = np.array(0.0).reshape(1, 1);
+          var beta = tf.Variable(beta_arr, name: "beta", dtype: tf.float64);
 #endif
           //var alpha = tf.Variable(1.0, name: $"alpha_{1.0}", dtype: tf.float64/*, shape: new[] { 1, 1 }*/);