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NeuralMidiFx
Home
VST Plugin Basics
Overview and Architecture
Installation
1. Model Preparation
A Guide on Serialization of PyTorch Models
Importing Your Serialized Models
2. Parameters and GUI
3. Deployment Thread (DPL)
Specify Host Events
deploy() Method
4. Preset Management
Data Types
CustomPresetDataDictionary
MidiVisualizersData
AudioVisualizersData
GuiParams
RealtimePlaybackInfo
EventFromHost
MidiFileEvent
PlaybackSequence
PlaybackPolicy
Demos
MidToMid
Uncond. Rand. Generation
Pattern Interpolation
Groove to Drum (Using MIDI File)
Groove to Drum (Real-Time)
Call and Response
Mid2Aud
Aud2Mid
Aud2Aud
V1.0.0 Documentation
Overview and Architecture
Installation
1. Model Preparation
A Guide on Serialization of PyTorch Models
Importing Your Serialized Models
2. Parameters and GUI
3. Input Preparation
A. Specify Host Events
B. Deploy() Method
4. Inference
Deploy() Method
5. Playback Preparation
Deploy() Method
Data Types
GuiParams
RealtimePlaybackInfo
EventFromHost
MidiFileEvent
CustomizableDataTypes
PlaybackSequence
PlaybackPolicy
Guides & References
Implementation Checklist
Data Flow
Tutorials
1 - Random Generation
2 - Pattern Interpolation
3 - Groove to Drum (Using MIDI File)
4 - Groove to Drum (Real-Time)
5 - Single Thread Implementation
6 - Call and Response
NeuralMidiFx on GitHub
NeuralMidiFx on GitHub
V1.0.0 Documentation
5. Playback Preparation
Prepare Generated Data for Playback
Table of contents
Table of contents
Deploy() Method