LWMTemporal Examples

This directory contains example scripts demonstrating how to use the LWMTemporal package.

Quick Start Examples

1. Masked Reconstruction (`example_reconstruction.py`)

Demonstrates how to:

Load wireless channel data
Tokenize complex channels
Mask random positions
Reconstruct using the pretrained model

python examples/example_reconstruction.py

2. Channel Prediction Inference (`inference_channel_prediction.py`)

Run inference with a fine-tuned channel prediction model:

python examples/inference_channel_prediction.py

Expected output: Per-step NMSE around -20 dB

3. Train Channel Prediction (`train_channel_prediction.py`)

Fine-tune the model for channel prediction:

python examples/train_channel_prediction.py

This will:

Load pretrained weights
Fine-tune on your dataset
Save checkpoints to models/
Generate visualizations in figs/predictions/

Using the CLI

The package also provides command-line interfaces:

Channel Prediction

python -m LWMTemporal.cli.channel_prediction \
  --data_path examples/data/city_8_tempe_3p5_20_32_32.p \
  --pretrained checkpoints/m18_cp.pth \
  --inference_only \
  --val_limit 100 \
  --device cpu

Pretraining

python -m LWMTemporal.cli.pretrain \
  --data_dir examples/data/ \
  --save_prefix models/pretrained \
  --epochs 100 \
  --batch_size 32 \
  --device cuda

Data Format

Example data files are in examples/data/. See examples/data/README.md for details on the expected format.

Checkpoints

Pretrained checkpoints are in checkpoints/. See checkpoints/README.md for available models and loading instructions.