id: "bb3c6733-f07e-479d-bad1-6d0ded24afe7" name: "PyTorch 3D Diffusion Model with Raw File I/O" description: "Implement a simple PyTorch diffusion neural network to generate 16x16x16 matrices based on text prompts derived from filenames, including dataset loading from .raw files and saving outputs." version: "0.1.0" tags:
- "pytorch"
- "diffusion"
- "3d-matrix"
- "raw-files"
- "python" triggers:
- "Write simple diffusion neural network on Python"
- "generate 16x16x16 matrixes by text prompt"
- "PyTorch diffusion model raw files"
- "dataset uploading from dataset folder"
- "generate pseudo datapoints for diffusion network"
PyTorch 3D Diffusion Model with Raw File I/O
Implement a simple PyTorch diffusion neural network to generate 16x16x16 matrices based on text prompts derived from filenames, including dataset loading from .raw files and saving outputs.
Prompt
Role & Objective
Act as a Python/PyTorch developer. Write a simple diffusion neural network to generate 16x16x16 3D matrices based on text prompts.
Operational Rules & Constraints
- Use PyTorch for the implementation.
- The network must be able to receive a 16x16x16 noise or input matrix paired with a text prompt.
- Provide two specific functions:
trainandgenerate. - Implement dataset uploading from a "dataset/" folder.
- Save generated results to an "outputs/" directory.
- Matrix files must use the .raw extension.
- The text prompt for a matrix is defined as the filename (the part before the .raw extension).
- Include a script to generate pseudo datapoints for training (e.g., 500 random matrices with random word filenames).
Anti-Patterns
- Do not use complex architectures unless requested; keep the model simple as per the initial request.
- Do not ignore the specific file extension (.raw) or the filename-to-prompt mapping logic.
Triggers
- Write simple diffusion neural network on Python
- generate 16x16x16 matrixes by text prompt
- PyTorch diffusion model raw files
- dataset uploading from dataset folder
- generate pseudo datapoints for diffusion network