@TensorFlowCns::setupSynapses; debug reduced

Purpose: since `session->Run` can have order-of-ops issues, try not to reuse training step to compute `loss`.
Is followup to commit HEAD~1 (@`TensorFlowCns::setupSynapses`; debug print loss). TODO: `squash` this

Author: SwuduSusuwu

cxx/ClassTensorFlowCns.hxx

@@ -355,18 +355,16 @@ public:
 					{"input", inputTensor},
 					{"labels", expectedOutputTensor}
 				},
-				outputTensors,
+				(0 == validationCount) ? outputTensors : std::vector<std::string>(),
 				{"optimizerCoefficients" SUSUWU_CNS_IF_BIAS(SUSUWU_COMMA "optimizerBiases")},
-				&outputs
+				(0 == validationCount) ? &outputs : SUSUWU_NULLPTR
 			);
 			if(!status.ok()) {
 				throw std::runtime_error(SUSUWU_ERRSTR(SUSUWU_SH_ERROR, getName() + "::setupSynapses() { const tensorflow::Status status = session->Run({{\"input\", inputTensor}, {\"labels\", expectedOutputTensor}, {" + ((0 == validationCount) ? "\"loss\"" : "") + "}, {\"optimizerCoefficients\" " + "" SUSUWU_CNS_IF_BIAS(", \"optimizerBiases\"") + "}, &outputs); (!status.ok()) { epoch == " + std::to_string(epoch) + "; status.ToString() == \"" + status.ToString() + "\"; } }"));
 			}
-			const float trainingLossVal = outputs[0].scalar<float>()();
-			SUSUWU_DEBUG(getName() + "::setupSynapses() { for(size_t epoch = 0; epoch < trainingIterations; ++epoch) { /* training */ epoch == " + std::to_string(epoch) + "; trainingLossVal == " + std::to_string(trainingLossVal) + "; status.ToString() == \"" + status.ToString() + "\"; ... } }");
 			float lossVal;
 			if(0 == validationCount) {
-				lossVal = trainingLossVal;
+				lossVal = outputs[0].scalar<float>()();
 			} else {
 				outputs.clear();
 				status = session->Run(
@@ -378,9 +376,9 @@ public:
 				if(!status.ok()) {
 					throw std::runtime_error(SUSUWU_ERRSTR(SUSUWU_SH_ERROR, getName() + "::setupSynapses() { const tensorflow::Status status = session->Run({{\"inputs\", inputTensor2}, {\"labels\", expectedOutputTensor2}}, {\"loss\"}, {}, &outputs); (!status.ok()) { epoch == " + std::to_string(epoch) + "; status.ToString() == \"" + status.ToString() + "\"; } }"));
 				}
-				lossVal = outputs[0].scalar<float>()(); /* TODO: use for eager stop */
-				SUSUWU_DEBUG(getName() + "::setupSynapses() { for(size_t epoch = 0; epoch < trainingIterations; ++epoch) { ... /* validation */ epoch == " + std::to_string(epoch) + "; lossVal == " + std::to_string(trainingLossVal) + "; status.ToString() == \"" + status.ToString() + "\"; ... } }");
+				lossVal = outputs[0].scalar<float>()();
 			}
+			SUSUWU_DEBUG(getName() + "::setupSynapses() { for(size_t epoch = 0; epoch < trainingIterations; ++epoch) { epoch == " + std::to_string(epoch) + "; lossVal == " + std::to_string(lossVal) + "; status.ToString() == \"" + status.ToString() + "\"; ... } }");
 			if(lossVal < desiredLossThreshold) { break; }
 			if(lossVal < bestLoss - minLossDelta) {
 				bestLoss = lossVal;