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implement all the DSP stuff for AIDA-X

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Signed-off-by: falkTX <falktx@falktx.com>
This commit is contained in:
falkTX 2023-05-18 18:49:46 +02:00
parent 1ad3d130d4
commit 2823dcfe78
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GPG key ID: CDBAA37ABC74FBA0
3 changed files with 422 additions and 36 deletions
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2
.github/workflows/build.yml vendored
View file

@ -429,7 +429,7 @@ jobs:
sudo rm -f /etc/apt/sources.list.d/microsoft-prod.list
sudo dpkg --add-architecture i386
sudo apt-get update -qq
sudo apt-get install libc6:i386 libgcc-s1:i386 libstdc++6:i386 --allow-downgrades
sudo apt-get install -yqq --allow-downgrades libc6:i386 libgcc-s1:i386 libstdc++6:i386
sudo apt-get clean
- name: Set up dependencies
if: ${{ matrix.target == 'win32' }}

9
Makefile
View file

@ -200,6 +200,15 @@ else
gen:
endif
# --------------------------------------------------------------
# extra rules, for quick testing
jack: carla deps dgl plugins resources
$(MAKE) jack -C src $(CARLA_EXTRA_ARGS)
native: carla deps dgl plugins resources
$(MAKE) native -C src $(CARLA_EXTRA_ARGS)
# --------------------------------------------------------------
# Packaging standalone for CI

447
plugins/Cardinal/src/AIDA-X.cpp
View file

@ -34,6 +34,8 @@ static constexpr float MAP(const float x, const float in_min, const float in_max
/* Defines for tone controls */
static constexpr const float COMMON_Q = 0.707f;
static constexpr const float DEPTH_FREQ = 75.f;
static constexpr const float PRESENCE_FREQ = 900.f;
/* Defines for antialiasing filter */
static constexpr const float INLPF_MAX_CO = 0.99f * 0.5f; /* coeff * ((samplerate / 2) / samplerate) */
@ -52,7 +54,7 @@ struct DynamicModel {
// This function carries model calculations
static inline
void applyModel(DynamicModel* model, float* const out, uint32_t numSamples)
void applyModelOffline(DynamicModel* model, float* const out, uint32_t numSamples)
{
const bool input_skip = model->input_skip;
const float input_gain = model->input_gain;
@ -82,6 +84,54 @@ void applyModel(DynamicModel* model, float* const out, uint32_t numSamples)
out[i] = custom_model.forward(out + i) * output_gain;
}
}
else if constexpr (ModelType::input_size == 2)
{
float inArray1 alignas(RTNEURAL_DEFAULT_ALIGNMENT)[2];
if (input_skip)
{
for (uint32_t i=0; i<numSamples; ++i)
{
inArray1[0] = out[i];
inArray1[1] = 0.f;
out[i] += custom_model.forward(inArray1);
}
}
else
{
for (uint32_t i=0; i<numSamples; ++i)
{
inArray1[0] = out[i];
inArray1[1] = 0.f;
out[i] = custom_model.forward(inArray1) * output_gain;
}
}
}
else if constexpr (ModelType::input_size == 3)
{
float inArray2 alignas(RTNEURAL_DEFAULT_ALIGNMENT)[3];
if (input_skip)
{
for (uint32_t i=0; i<numSamples; ++i)
{
inArray2[0] = out[i];
inArray2[1] = 0.f;
inArray2[2] = 0.f;
out[i] += custom_model.forward(inArray2);
}
}
else
{
for (uint32_t i=0; i<numSamples; ++i)
{
inArray2[0] = out[i];
inArray2[1] = 0.f;
inArray2[2] = 0.f;
out[i] = custom_model.forward(inArray2) * output_gain;
}
}
}
if (input_skip && d_isNotEqual(output_gain, 1.f))
{
@ -94,7 +144,7 @@ void applyModel(DynamicModel* model, float* const out, uint32_t numSamples)
}
static inline
float applyModel(DynamicModel* model, float sample)
float applyModel(DynamicModel* model, float sample, const float param1, const float param2)
{
const bool input_skip = model->input_skip;
const float input_gain = model->input_gain;
@ -103,13 +153,13 @@ float applyModel(DynamicModel* model, float sample)
sample *= input_gain;
std::visit(
[&sample, input_skip, output_gain] (auto&& custom_model)
[&sample, input_skip, output_gain, param1, param2] (auto&& custom_model)
{
using ModelType = std::decay_t<decltype (custom_model)>;
float* out = &sample;
if constexpr (ModelType::input_size == 1)
{
float* out = &sample;
if (input_skip)
{
sample += custom_model.forward(out);
@ -120,6 +170,32 @@ float applyModel(DynamicModel* model, float sample)
sample = custom_model.forward(out) * output_gain;
}
}
else if constexpr (ModelType::input_size == 2)
{
float inArray1 alignas(RTNEURAL_DEFAULT_ALIGNMENT)[2] = {sample, param1};
if (input_skip)
{
sample += custom_model.forward(inArray1);
sample *= output_gain;
}
else
{
sample = custom_model.forward(inArray1) * output_gain;
}
}
else if constexpr (ModelType::input_size == 3)
{
float inArray2 alignas(RTNEURAL_DEFAULT_ALIGNMENT)[3] = {sample, param1, param2};
if (input_skip)
{
sample += custom_model.forward(inArray2);
sample *= output_gain;
}
else
{
sample = custom_model.forward(inArray2) * output_gain;
}
}
},
model->variant
);
@ -130,11 +206,35 @@ float applyModel(DynamicModel* model, float sample)
// --------------------------------------------------------------------------------------------------------------------
struct AidaPluginModule : Module {
enum ParamIds {
PARAM_INPUT_LEVEL,
PARAM_OUTPUT_LEVEL,
enum Parameters {
kParameterINLPF,
kParameterINLEVEL,
kParameterNETBYPASS,
kParameterEQBYPASS,
kParameterEQPOS,
kParameterBASSGAIN,
kParameterBASSFREQ,
kParameterMIDGAIN,
kParameterMIDFREQ,
kParameterMIDQ,
kParameterMTYPE,
kParameterTREBLEGAIN,
kParameterTREBLEFREQ,
kParameterDEPTH,
kParameterPRESENCE,
kParameterOUTLEVEL,
kParameterPARAM1,
kParameterPARAM2,
NUM_PARAMS
};
enum EqPos {
kEqPost,
kEqPre
};
enum MidEqType {
kMidEqPeak,
kMidEqBandpass
};
enum InputIds {
AUDIO_INPUT,
NUM_INPUTS
@ -147,16 +247,20 @@ struct AidaPluginModule : Module {
NUM_LIGHTS
};
enum Parameters {
kParameterCount
};
CardinalPluginContext* const pcontext;
bool fileChanged = false;
std::string currentFile;
Biquad dc_blocker { bq_type_highpass, 0.5f, COMMON_Q, 0.0f };
Biquad in_lpf { bq_type_lowpass, 0.5f, COMMON_Q, 0.0f };
Biquad bass { bq_type_lowshelf, 0.5f, COMMON_Q, 0.0f };
Biquad mid { bq_type_peak, 0.5f, COMMON_Q, 0.0f };
Biquad treble { bq_type_highshelf, 0.5f, COMMON_Q, 0.0f };
Biquad depth { bq_type_peak, 0.5f, COMMON_Q, 0.0f };
Biquad presence { bq_type_highshelf, 0.5f, COMMON_Q, 0.0f };
float cachedParams[NUM_PARAMS] = {};
dsp::ExponentialFilter inlevel;
dsp::ExponentialFilter outlevel;
DynamicModel* model = nullptr;
@ -169,8 +273,35 @@ struct AidaPluginModule : Module {
configInput(AUDIO_INPUT, "Audio");
configOutput(AUDIO_OUTPUT, "Audio");
configParam(PARAM_INPUT_LEVEL, -12.f, 12.f, 0.f, "Input level", " dB");
configParam(PARAM_OUTPUT_LEVEL, -12.f, 12.f, 0.f, "Output level", " dB");
configParam(kParameterINLPF, -0.f, 100.f, 66.216f, "ANTIALIASING", " %");
configParam(kParameterINLEVEL, -12.f, 12.f, 0.f, "INPUT", " dB");
configSwitch(kParameterNETBYPASS, 0.f, 1.f, 0.f, "NETBYPASS");
configSwitch(kParameterEQBYPASS, 0.f, 1.f, 0.f, "EQBYPASS");
configSwitch(kParameterEQPOS, 0.f, 1.f, 0.f, "NETBYPASS");
configParam(kParameterBASSGAIN, -8.f, 8.f, 0.f, "BASS", " dB");
configParam(kParameterBASSFREQ, 60.f, 305.f, 75.f, "BFREQ", " Hz");
configParam(kParameterMIDGAIN, -8.f, 8.f, 0.f, "MID", " dB");
configParam(kParameterMIDFREQ, 150.f, 5000.f, 750.f, "MFREQ", " Hz");
configParam(kParameterMIDQ, 0.2f, 5.f, 0.707f, "MIDQ");
configSwitch(kParameterMTYPE, 0.f, 1.f, 0.f, "MTYPE");
configParam(kParameterTREBLEGAIN, -8.f, 8.f, 0.f, "TREBLE", " dB");
configParam(kParameterTREBLEFREQ, 1000.f, 4000.f, 2000.f, "TFREQ", " Hz");
configParam(kParameterDEPTH, -8.f, 8.f, 0.f, "DEPTH", " dB");
configParam(kParameterPRESENCE, -8.f, 8.f, 0.f, "PRESENCE", " dB");
configParam(kParameterOUTLEVEL, -15.f, 15.f, 0.f, "OUTPUT", " dB");
configParam(kParameterPARAM1, 0.f, 1.f, 0.f, "PARAM1");
configParam(kParameterPARAM2, 0.f, 1.f, 0.f, "PARAM2");
cachedParams[kParameterINLPF] = 66.216f;
cachedParams[kParameterBASSGAIN] = 0.f;
cachedParams[kParameterBASSFREQ] = 75.f;
cachedParams[kParameterMIDGAIN] = 0.f;
cachedParams[kParameterMIDFREQ] = 750.f;
cachedParams[kParameterMIDQ] = 0.707f;
cachedParams[kParameterTREBLEGAIN] = 0.f;
cachedParams[kParameterTREBLEFREQ] = 2000.f;
cachedParams[kParameterDEPTH] = 0.f;
cachedParams[kParameterPRESENCE] = 0.f;
in_lpf.setFc(MAP(66.216f, 0.0f, 100.0f, INLPF_MAX_CO, INLPF_MIN_CO));
inlevel.setTau(1 / 30.f);
@ -240,7 +371,7 @@ struct AidaPluginModule : Module {
/* Understand which model type to load */
input_size = model_json["in_shape"].back().get<int>();
if (input_size > 1) { // MAX_INPUT_SIZE
if (input_size > MAX_INPUT_SIZE) {
throw std::invalid_argument("Value for input_size not supported");
}
@ -302,7 +433,7 @@ struct AidaPluginModule : Module {
// Pre-buffer to avoid "clicks" during initialization
float out[2048] = {};
applyModel(newmodel.get(), out, ARRAY_SIZE(out));
applyModelOffline(newmodel.get(), out, ARRAY_SIZE(out));
// swap active model
DynamicModel* const oldmodel = model;
@ -315,30 +446,207 @@ struct AidaPluginModule : Module {
delete oldmodel;
}
MidEqType getMidType() const
{
return cachedParams[kParameterMTYPE] > 0.5f ? kMidEqBandpass : kMidEqPeak;
}
float applyToneControls(float sample)
{
return getMidType() == kMidEqBandpass
? mid.process(sample)
: presence.process(
treble.process(
mid.process(
bass.process(
depth.process(sample)))));
}
void process(const ProcessArgs& args) override
{
const float stime = args.sampleTime;
const float inlevelv = DB_CO(params[PARAM_INPUT_LEVEL].getValue());
const float outlevelv = DB_CO(params[PARAM_OUTPUT_LEVEL].getValue());
const float inlevelv = DB_CO(params[kParameterINLEVEL].getValue());
const float outlevelv = DB_CO(params[kParameterOUTLEVEL].getValue());
const bool net_bypass = params[kParameterNETBYPASS].getValue() > 0.5f;
const bool eq_bypass = params[kParameterEQBYPASS].getValue() > 0.5f;
const EqPos eq_pos = params[kParameterEQPOS].getValue() > 0.5f ? kEqPre : kEqPost;
// update tone controls
bool changed = false;
float value;
value = params[kParameterINLPF].getValue();
if (d_isNotEqual(cachedParams[kParameterINLPF], value))
{
cachedParams[kParameterINLPF] = value;
in_lpf.setFc(MAP(value, 0.0f, 100.0f, INLPF_MAX_CO, INLPF_MIN_CO));
}
value = params[kParameterBASSGAIN].getValue();
if (d_isNotEqual(cachedParams[kParameterBASSGAIN], value))
{
cachedParams[kParameterBASSGAIN] = value;
changed = true;
}
value = params[kParameterBASSFREQ].getValue();
if (d_isNotEqual(cachedParams[kParameterBASSFREQ], value))
{
cachedParams[kParameterBASSFREQ] = value;
changed = true;
}
if (changed)
{
changed = false;
bass.setBiquad(bq_type_lowshelf,
cachedParams[kParameterBASSFREQ] / args.sampleRate,
COMMON_Q,
cachedParams[kParameterBASSGAIN]);
}
value = params[kParameterMIDGAIN].getValue();
if (d_isNotEqual(cachedParams[kParameterMIDGAIN], value))
{
cachedParams[kParameterMIDGAIN] = value;
changed = true;
}
value = params[kParameterMIDFREQ].getValue();
if (d_isNotEqual(cachedParams[kParameterMIDFREQ], value))
{
cachedParams[kParameterMIDFREQ] = value;
changed = true;
}
value = params[kParameterMIDQ].getValue();
if (d_isNotEqual(cachedParams[kParameterMIDQ], value))
{
cachedParams[kParameterMIDQ] = value;
changed = true;
}
value = params[kParameterMTYPE].getValue();
if (d_isNotEqual(cachedParams[kParameterMTYPE], value))
{
cachedParams[kParameterMTYPE] = value;
changed = true;
}
if (changed)
{
changed = false;
mid.setBiquad(getMidType() == kMidEqBandpass ? bq_type_bandpass : bq_type_peak,
cachedParams[kParameterMIDFREQ] / args.sampleRate,
cachedParams[kParameterMIDQ],
cachedParams[kParameterMIDGAIN]);
}
value = params[kParameterTREBLEGAIN].getValue();
if (d_isNotEqual(cachedParams[kParameterTREBLEGAIN], value))
{
cachedParams[kParameterTREBLEGAIN] = value;
changed = true;
}
value = params[kParameterTREBLEFREQ].getValue();
if (d_isNotEqual(cachedParams[kParameterTREBLEFREQ], value))
{
cachedParams[kParameterTREBLEFREQ] = value;
changed = true;
}
if (changed)
{
changed = false;
treble.setBiquad(bq_type_highshelf,
cachedParams[kParameterTREBLEFREQ] / args.sampleRate,
COMMON_Q,
cachedParams[kParameterTREBLEGAIN]);
}
value = params[kParameterDEPTH].getValue();
if (d_isNotEqual(cachedParams[kParameterDEPTH], value))
{
cachedParams[kParameterDEPTH] = value;
depth.setPeakGain(value);
}
value = params[kParameterPRESENCE].getValue();
if (d_isNotEqual(cachedParams[kParameterPRESENCE], value))
{
cachedParams[kParameterPRESENCE] = value;
presence.setPeakGain(value);
}
// High frequencies roll-off (lowpass)
float sample = in_lpf.process(inputs[AUDIO_INPUT].getVoltage() * 0.1f) * inlevel.process(stime, inlevelv);
// Equalizer section
if (!eq_bypass && eq_pos == kEqPre)
sample = applyToneControls(sample);
// run model
if (model != nullptr)
if (!net_bypass && model != nullptr)
{
activeModel.store(true);
sample = applyModel(model, sample);
sample = applyModel(model, sample,
params[kParameterPARAM1].getValue(),
params[kParameterPARAM2].getValue());
activeModel.store(false);
}
// DC blocker filter (highpass)
outputs[AUDIO_OUTPUT].setVoltage(dc_blocker.process(sample) * outlevel.process(stime, outlevelv) * 10.f);
sample = dc_blocker.process(sample);
// Equalizer section
if (!eq_bypass && eq_pos == kEqPost)
sample = applyToneControls(sample);
// Output volume
outputs[AUDIO_OUTPUT].setVoltage(sample * outlevel.process(stime, outlevelv) * 10.f);
}
void onSampleRateChange(const SampleRateChangeEvent& e) override
{
cachedParams[kParameterBASSGAIN] = params[kParameterBASSGAIN].getValue();
cachedParams[kParameterBASSFREQ] = params[kParameterBASSFREQ].getValue();
cachedParams[kParameterMIDGAIN] = params[kParameterMIDGAIN].getValue();
cachedParams[kParameterMIDFREQ] = params[kParameterMIDFREQ].getValue();
cachedParams[kParameterMIDQ] = params[kParameterMIDQ].getValue();
cachedParams[kParameterMTYPE] = params[kParameterMTYPE].getValue();
cachedParams[kParameterTREBLEGAIN] = params[kParameterTREBLEGAIN].getValue();
cachedParams[kParameterTREBLEFREQ] = params[kParameterTREBLEFREQ].getValue();
cachedParams[kParameterDEPTH] = params[kParameterDEPTH].getValue();
cachedParams[kParameterPRESENCE] = params[kParameterPRESENCE].getValue();
dc_blocker.setFc(35.0f / e.sampleRate);
bass.setBiquad(bq_type_lowshelf,
cachedParams[kParameterBASSFREQ] / e.sampleRate,
COMMON_Q,
cachedParams[kParameterBASSGAIN]);
mid.setBiquad(getMidType() == kMidEqBandpass ? bq_type_bandpass : bq_type_peak,
cachedParams[kParameterMIDFREQ] / e.sampleRate,
cachedParams[kParameterMIDQ],
cachedParams[kParameterMIDGAIN]);
treble.setBiquad(bq_type_highshelf,
cachedParams[kParameterTREBLEFREQ] / e.sampleRate,
COMMON_Q,
cachedParams[kParameterTREBLEGAIN]);
depth.setBiquad(bq_type_peak,
DEPTH_FREQ / e.sampleRate,
COMMON_Q,
cachedParams[kParameterDEPTH]);
presence.setBiquad(bq_type_highshelf,
PRESENCE_FREQ / e.sampleRate,
COMMON_Q,
cachedParams[kParameterPRESENCE]);
}
DISTRHO_DECLARE_NON_COPYABLE_WITH_LEAK_DETECTOR(AidaPluginModule)
@ -501,15 +809,11 @@ struct AidaKnob : app::SvgKnob {
};
struct AidaWidget : ModuleWidgetWithSideScrews<23> {
static constexpr const float previewBoxHeight = 80.0f;
static constexpr const float previewBoxBottom = 20.0f;
static constexpr const float previewBoxRect[] = {8.0f,
380.0f - previewBoxHeight - previewBoxBottom,
15.0f * 23 - 16.0f,
previewBoxHeight};
static constexpr const uint kPedalMargin = 10;
static constexpr const uint kPedalMarginTop = 50;
static constexpr const float startY_list = startY - 2.0f;
static constexpr const float fileListHeight = 380.0f - startY_list - previewBoxHeight - previewBoxBottom * 1.5f;
static constexpr const float startY_preview = startY_list + fileListHeight;
static constexpr const float fileListHeight = 380.0f - startY_list - 110.0f;
AidaPluginModule* const module;
@ -524,24 +828,97 @@ struct AidaWidget : ModuleWidgetWithSideScrews<23> {
addInput(createInput<PJ301MPort>(Vec(startX_In, 25), module, 0));
addOutput(createOutput<PJ301MPort>(Vec(startX_Out, 25), module, 0));
addChild(createParamCentered<AidaKnob>(Vec(box.size.x * 0.5f - 50, box.size.y - 60),
module, AidaPluginModule::PARAM_INPUT_LEVEL));
addChild(createParamCentered<AidaKnob>(Vec(50, box.size.y - 60),
module, AidaPluginModule::kParameterINLEVEL));
addChild(createParamCentered<AidaKnob>(Vec(box.size.x * 0.5f + 50, box.size.y - 60),
module, AidaPluginModule::PARAM_OUTPUT_LEVEL));
addChild(createParamCentered<AidaKnob>(Vec(100, box.size.y - 60),
module, AidaPluginModule::kParameterBASSGAIN));
addChild(createParamCentered<AidaKnob>(Vec(150, box.size.y - 60),
module, AidaPluginModule::kParameterMIDGAIN));
addChild(createParamCentered<AidaKnob>(Vec(200, box.size.y - 60),
module, AidaPluginModule::kParameterTREBLEGAIN));
addChild(createParamCentered<AidaKnob>(Vec(250, box.size.y - 60),
module, AidaPluginModule::kParameterDEPTH));
addChild(createParamCentered<AidaKnob>(Vec(300, box.size.y - 60),
module, AidaPluginModule::kParameterPRESENCE));
addChild(createParamCentered<AidaKnob>(Vec(350, box.size.y - 60),
module, AidaPluginModule::kParameterOUTLEVEL));
if (m != nullptr)
{
AidaModelListWidget* const listw = new AidaModelListWidget(m);
listw->box.pos = Vec(0, startY_list);
listw->box.size = Vec(box.size.x, fileListHeight);
listw->box.pos = Vec(kPedalMargin, startY_list);
listw->box.size = Vec(box.size.x - kPedalMargin * 2, fileListHeight);
addChild(listw);
}
}
void draw(const DrawArgs& args) override
{
drawBackground(args.vg);
const double widthPedal = box.size.x - kPedalMargin * 2;
const double heightPedal = box.size.y - kPedalMargin - kPedalMarginTop;
const int cornerRadius = 12;
// outer bounds gradient
nvgBeginPath(args.vg);
nvgRect(args.vg, 0, 0, box.size.x, box.size.y);
nvgFillPaint(args.vg,
nvgLinearGradient(args.vg,
0, 0, 0, box.size.y,
nvgRGB(0xff - 0xcd + 50, 0xff - 0xff + 50, 0xff),
nvgRGB(0xff - 0x8b + 50, 0xff - 0xf7 + 50, 0xff)));
nvgFill(args.vg);
// outer bounds pattern
// TODO
// box shadow
nvgBeginPath(args.vg);
nvgRect(args.vg,
kPedalMargin / 2,
kPedalMarginTop / 2,
kPedalMargin + widthPedal,
kPedalMarginTop + heightPedal);
nvgFillPaint(args.vg,
nvgBoxGradient(args.vg,
kPedalMargin,
kPedalMarginTop,
widthPedal,
heightPedal,
cornerRadius,
cornerRadius,
nvgRGBA(0,0,0,1.f),
nvgRGBA(0,0,0,0.f)));
nvgFill(args.vg);
// .rt-neural .grid
nvgBeginPath(args.vg);
nvgRoundedRect(args.vg, kPedalMargin, kPedalMarginTop, widthPedal, heightPedal, cornerRadius);
nvgFillPaint(args.vg,
nvgLinearGradient(args.vg,
kPedalMargin, kPedalMarginTop,
kPedalMargin + box.size.x * 0.52f, 0,
nvgRGB(28, 23, 12),
nvgRGB(42, 34, 15)));
nvgFill(args.vg);
nvgFillPaint(args.vg,
nvgLinearGradient(args.vg,
kPedalMargin + box.size.x * 0.5f, 0,
kPedalMargin + box.size.x, 0,
nvgRGB(42, 34, 15),
nvgRGB(19, 19, 19)));
nvgFill(args.vg);
// extra
nvgStrokeColor(args.vg, nvgRGBA(150, 150, 150, 0.25f));
nvgStroke(args.vg);
drawOutputJacksArea(args.vg);
ModuleWidget::draw(args);