Summary: Cursor adds advanced PyTorch experiment framework

Why It Matters: This change shows Cursor is making its AI coding tools better for complex machine learning work. It helps users do more advanced AI development.

What Changed:

• The code example for PyTorch MNIST experiments was greatly expanded.
• The new code includes mixed precision training, validation splitting, and configuration management.
• The train_model function was updated to use a config file, add data augmentation, and include more detailed training history.
• The MLP (Multi-Layer Perceptron) model now supports dropout and a more complex hidden layer structure.
• The demo text now describes a "configurable MNIST experiment framework with AMP and reports."