RT version of MLP objects

release-packaging/Classes/FluidMLP.sc

@@ -1,11 +1,11 @@
-FluidBaseMLP : FluidDataClient {
+FluidMLPRegressor : FluidRTDataClient {
+
 	const <identity = 0;
 	const <sigmoid  =  1;
 	const <relu = 2;
 	const <tanh = 3;
 
-
+	*new {|server, hidden = #[3,3] , activation = 0, outputLayer = 0, maxIter = 100, learnRate = 0.0001, momentum = 0.9, batchSize = 50, validation = 0.2|
-	*new {|server, hidden = #[3,3] , activation = 0, maxIter = 100, learnRate = 0.0001, momentum = 0.9, batchSize = 50, validation = 0.2|
 		var hiddenCtrlLabels;
 		hidden = [hidden.size]++hidden;
 
@@ -15,6 +15,7 @@ FluidBaseMLP : FluidDataClient {
 			[hiddenCtrlLabels,hidden].lace ++
 			[
 			\activation,activation,
+			\outputLayer, outputLayer,
 			\maxIter, maxIter,
 			\learnRate,learnRate,
 			\momentum, momentum,
@@ -27,13 +28,6 @@ FluidBaseMLP : FluidDataClient {
 		this.prSendMsg(\clear,action:action);
 	}
 
-}
-
-FluidMLPRegressor : FluidBaseMLP {
-	*new {|server, hidden = #[3,3] , activation = 0, maxIter = 100, learnRate = 0.0001, momentum = 0.9, batchSize = 50, validation = 0.2|
-		^super.new(server,hidden,activation, maxIter,learnRate, momentum, batchSize,validation)
-	}
-
 	fit{|sourceDataSet, targetDataSet, action|
 	   this.prSendMsg(\fit,
 			[sourceDataSet.asSymbol, targetDataSet.asSymbol],
@@ -41,23 +35,49 @@ FluidMLPRegressor : FluidBaseMLP {
 		);
 	}
 
-	predict{ |sourceDataSet, targetDataSet, layer, action|
+	predict{ |sourceDataSet, targetDataSet, action|
 		this.prSendMsg(\predict,
-			[sourceDataSet.asSymbol, targetDataSet.asSymbol,layer],
+			[sourceDataSet.asSymbol, targetDataSet.asSymbol],
 			action);
 	}
 
-	predictPoint { |sourceBuffer, targetBuffer, layer action|
+	predictPoint { |sourceBuffer, targetBuffer, action|
 		this.prSendMsg(\predictPoint,
-      [sourceBuffer.asUGenInput, targetBuffer.asUGenInput, layer], action);
+      [sourceBuffer.asUGenInput, targetBuffer.asUGenInput], action);
 	}
 }
 
-FluidMLPClassifier : FluidBaseMLP {
+
+FluidMLPClassifier : FluidRTDataClient {
+
+	const <identity = 0;
+	const <sigmoid  =  1;
+	const <relu = 2;
+	const <tanh = 3;
+
 	*new {|server, hidden = #[3,3] , activation = 0, maxIter = 100, learnRate = 0.0001, momentum = 0.9, batchSize = 50, validation = 0.2|
-		^super.new(server,hidden,activation, maxIter,learnRate, momentum, batchSize,validation)
+		var hiddenCtrlLabels;
+		hidden = [hidden.size]++hidden;
+
+		hiddenCtrlLabels = hidden.collect{|x,i| \hidden++i};
+
+		^super.new1(server,
+			[hiddenCtrlLabels,hidden].lace ++
+			[
+			\activation,activation,
+			\maxIter, maxIter,
+			\learnRate,learnRate,
+			\momentum, momentum,
+			\batchsize,batchSize,
+			\validation,validation,
+		])
 	}
 
+	clear{ |action|
+		this.prSendMsg(\clear,action:action);
+	}
+
+
 	fit{|sourceDataSet, targetLabelSet, action|
 	   this.prSendMsg(\fit,
 			[sourceDataSet.asSymbol, targetLabelSet.asSymbol],
@@ -65,14 +85,14 @@ FluidMLPClassifier : FluidBaseMLP {
 		);
 	}
 
-	predict{ |sourceDataSet, targetLabelSet, action|
+	predict{ |sourceDataSet, targetDataSet, action|
 		this.prSendMsg(\predict,
-			[sourceDataSet.asSymbol, targetLabelSet.asSymbol],
+			[sourceDataSet.asSymbol, targetDataSet.asSymbol],
 			action);
 	}
 
 	predictPoint { |sourceBuffer, action|
 		this.prSendMsg(\predictPoint,
-			[sourceBuffer.asUGenInput], action,string(FluidMessageResponse,_,_));
+			[sourceBuffer.asUGenInput], action, string(FluidMessageResponse,_,_));
 	}
 }

src/FluidManipulation/FluidManipulation.cpp

@@ -38,6 +38,6 @@ PluginLoad(FluidSTFTUGen)
   makeSCWrapper<RTAudioTransportClient>("FluidAudioTransport",ft);
   makeSCWrapper<NRTThreadedAudioTransportClient>("FluidBufAudioTransport",ft);
   makeSCWrapper<NRTThreadedDataSetWriter>("FluidDataSetWr", ft);
-  makeSCWrapper<NRTThreadedMLPRegressorClient>("FluidMLPRegressor",ft);
+  makeSCWrapper<RTMLPRegressorClient>("FluidMLPRegressor",ft);
-  makeSCWrapper<NRTThreadedMLPClassifierClient>("FluidMLPClassifier",ft);
+  makeSCWrapper<RTMLPClassifierClient>("FluidMLPClassifier",ft);
 }