Feature request: Generating 3D Voxel Designs (used for mechanical desigs) using advanced GAN Techniques

[Panchadip-128]

Is your feature request related to a problem? Please describe.
This project implements a Generative Adversarial Networks framework (GAN) to generate 3D voxel data. The goal is to train a GAN to produce synthetic 3D voxel-based structures that resemble real-world data, allowing for data augmentation and analysis of generated samples.
Describe the solution you'd like
This repository contains code for:

Generator: A neural network model that takes a latent vector (noise) as input and generates 3D voxel data.
Discriminator: A neural network model that distinguishes between real voxel data and generated voxel data.
GAN Model: A combination of the generator and discriminator models, trained together in an adversarial setup.
The model is trained on 3D voxel datasets and can generate new voxel structures by learning the underlying data distribution.

Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.

Approach to be followed (optional)
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Additional context
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[github-actions]

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[github-actions]

Hello @Panchadip-128! Your issue #834 has been closed. Thank you for your contribution!