Proteus

commit aa3f53d60cc50c97874196c40078fd44583a81c3
parent 585810a7c6a29e0cce2570e1d1d3b5eee23e3f63
Author: Keith <smartguitarml@gmail.com>
Date:   Thu,  6 Oct 2022 20:39:39 -0500

Updates

Diffstat:
M
src/PluginProcessor.cpp
 | 
11
++++++-----
M
src/RTNeuralLSTM.cpp
 | 
55
+++++++++++++++++++++++++++++++++++++++++++++----------
M
src/RTNeuralLSTM.h
 | 
3
+++

3 files changed, 54 insertions(+), 15 deletions(-)
diff --git a/src/PluginProcessor.cpp b/src/PluginProcessor.cpp
@@ -171,10 +171,10 @@ void ProteusAudioProcessor::processBlock (AudioBuffer<float>& buffer, MidiBuffer
             // Apply ramped changes for gain smoothing
             if (driveValue == previousDriveValue)
             {
-                buffer.applyGain(driveValue*10.0);
+                buffer.applyGain(driveValue*2.5);
             }
              else {
-                buffer.applyGainRamp(0, (int) buffer.getNumSamples(), previousDriveValue * 10.0, driveValue * 10.0);
+                buffer.applyGainRamp(0, (int) buffer.getNumSamples(), previousDriveValue * 2.5, driveValue * 2.5);
                 previousDriveValue = driveValue;
             }
             auto block44k = resampler.processIn(block);
@@ -190,7 +190,7 @@ void ProteusAudioProcessor::processBlock (AudioBuffer<float>& buffer, MidiBuffer
             }
             resampler.processOut(block44k, block);
         } else {
-            buffer.applyGain(5.0); // Apply default boost to help sound
+            buffer.applyGain(1.5); // Apply default boost to help sound
             // resample to target sample rate
             
             auto block44k = resampler.processIn(block);
@@ -213,10 +213,10 @@ void ProteusAudioProcessor::processBlock (AudioBuffer<float>& buffer, MidiBuffer
         // Apply ramped changes for gain smoothing
         if (masterValue == previousMasterValue)
         {
-            buffer.applyGain(masterValue);
+            buffer.applyGain(masterValue*1.2);
         }
         else {
-            buffer.applyGainRamp(0, (int) buffer.getNumSamples(), previousMasterValue, masterValue);
+            buffer.applyGainRamp(0, (int) buffer.getNumSamples(), previousMasterValue * 1.2, masterValue * 1.2);
             previousMasterValue = masterValue;
         }
     }
@@ -285,6 +285,7 @@ void ProteusAudioProcessor::loadConfig(File configFile)
 
     LSTM.reset();
     LSTM2.reset();
+
     LSTM.load_json(char_filename);
     LSTM2.load_json(char_filename);
 
diff --git a/src/RTNeuralLSTM.cpp b/src/RTNeuralLSTM.cpp
@@ -52,23 +52,39 @@ void RT_LSTM::load_json(const char* filename)
 {
     // Read in the JSON file
     std::ifstream i2(filename);
-	nlohmann::json weights_json;
-	i2 >> weights_json;
+    nlohmann::json weights_json;
+    i2 >> weights_json;
+
+    // Check that format is correct
+    /*
+    int hidden_size_temp = 0;
+    std::string network;
+    try {
+        hidden_size_temp = weights_json["/model_data/hidden_size"_json_pointer];
+        network = weights_json["/model_data/unit_type"_json_pointer];
+        throw(hidden_size_temp);
+    } 
+    catch (int hidden_size_temp) {
+        return;
+    }
+    */
 
+    //if (hidden_size_temp == 40 && network == "LSTM") {
     // Get the input size of the JSON file
-	int input_size_json = weights_json["/model_data/input_size"_json_pointer];
-	input_size = input_size_json;
+    int input_size_json = weights_json["/model_data/input_size"_json_pointer];
+    input_size = input_size_json;
 
     // Load the appropriate model
     if (input_size == 1) {
-		set_weights(&model, filename);
+        set_weights(&model, filename);
     }
     else if (input_size == 2) {
-		set_weights(&model_cond1, filename);
-    } 
+        set_weights(&model_cond1, filename);
+    }
     else if (input_size == 3) {
-		set_weights(&model_cond2, filename);
-    } 
+        set_weights(&model_cond2, filename);
+    }
+    //}
 }
 
 
@@ -83,17 +99,36 @@ void RT_LSTM::reset()
 
 void RT_LSTM::process(const float* inData, float* outData, int numSamples)
 {
+
     for (int i = 0; i < numSamples; ++i)
         outData[i] = model.forward(inData + i) + inData[i];
 }
 
 void RT_LSTM::process(const float* inData, float param, float* outData, int numSamples)
 {
+    // Check for parameter changes for smoothing calculations
+    if (param != previousParam1) {
+        steppedValue1 = (param - previousParam1) / numSamples;
+        changedParam1 = true;
+    }
+    else {
+        changedParam1 = false;
+    }
+
     for (int i = 0; i < numSamples; ++i) {
         inArray1[0] = inData[i];
-        inArray1[1] = param;
+
+        // Perform ramped value calculations to smooth out sound
+        if (changedParam1 == true) {
+            inArray1[1] = previousParam1 + (i + 1) * steppedValue1;
+        }
+        else {
+            inArray1[1] = param;
+        }
+
         outData[i] = model_cond1.forward(inArray1) + inData[i];
     }
+    previousParam1 = param;
 }
 
 void RT_LSTM::process(const float* inData, float param1, float param2, float* outData, int numSamples)
diff --git a/src/RTNeuralLSTM.h b/src/RTNeuralLSTM.h
@@ -18,6 +18,9 @@ public:
     void process(const float* inData, float param1, float param2, float* outData, int numSamples);
 
     int input_size = 1;
+    float previousParam1 = 0.0;
+    float steppedValue1 = 0.0;
+    bool changedParam1 = false;
     
 private:
     RTNeural::ModelT<float, 1, 1,