**Generative Music Composition using Neural Networks: A Step

Generative Music Composition using Neural Networks: A Step-by-Step Guide

In the realm of artificial intelligence and music, a fascinating application has emerged: generative music composition using neural networks. This innovative approach utilizes deep learning techniques to create original music, blurring the lines between human creativity and machine-generated art. In this post, we'll delve into the basics of this technology and provide a practical example using PyTorch.

Architecture Overview

Our neural network architecture, MusicGen, consists of an encoder and a decoder. The encoder takes in a sequence of musical features (e.g., notes, durations, and velocities) and reduces the dimensionality to a lower-dimensional representation. The decoder then generates new musical sequences based on this compressed representation.

python
import numpy as np
import torch
import torch.nn as nn

class MusicGen(nn.Module):
    def __init__(self):
        super().__init__()
     ...

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