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hao-ai-lab-FastVideo/examples/train/README.md
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# Training
## Quick Start
### Single-node
```bash
bash examples/train/run.sh <config.yaml> [--dotted.key value ...]
```
The script auto-detects available GPUs. Override with `NUM_GPUS`:
```bash
NUM_GPUS=4 bash examples/train/run.sh \
examples/train/configs/fine_tuning/wan/t2v.yaml
```
### Multi-node (Slurm)
```bash
bash examples/train/run_slurm.sh <config.yaml> <num_nodes> [--dotted.key value ...]
```
```bash
bash examples/train/run_slurm.sh \
examples/train/configs/fine_tuning/wan/t2v.yaml 4 \
--training.distributed.hsdp_shard_dim 8 \
--training.distributed.hsdp_replicate_dim 4
```
Slurm environment variables:
| Variable | Default | Description |
|---|---|---|
| `PARTITION` | `main` | Slurm partition |
| `NUM_GPUS` | `8` | GPUs per node |
| `CPUS_PER_TASK` | `128` | CPUs per task |
| `MEM` | `1440G` | Memory per node |
| `EXCLUDE` | `""` | Nodes to exclude |
### Overriding config values
Any config field can be overridden from the command line using dotted keys:
```bash
bash examples/train/run.sh examples/train/configs/fine_tuning/wan/t2v.yaml \
--training.optimizer.learning_rate 1e-5 \
--training.loop.max_train_steps 1000 \
--training.checkpoint.output_dir outputs/my_experiment
```
### Resuming from a checkpoint
```bash
bash examples/train/run.sh examples/train/configs/fine_tuning/wan/t2v.yaml \
--training.checkpoint.resume_from_checkpoint outputs/my_experiment/checkpoint-500
```
## W&B Logging
Training metrics and validation videos are logged to
[Weights & Biases](https://wandb.ai). Set your API key before launching:
```bash
export WANDB_API_KEY=your_key_here
```
To disable W&B (e.g. for local debugging):
```bash
export WANDB_MODE=offline
```
The project name and run name are set in the config under `training.tracker`:
```yaml
training:
tracker:
project_name: my_project
run_name: my_run
```
## Directory Layout
```
examples/train/
├── configs/ # Single-step training configs (by method and model)
├── scenario/ # Multi-step end-to-end training pipelines
├── run.sh # Single-node launcher
└── run_slurm.sh # Multi-node Slurm launcher
```
See `configs/README.md` and `scenario/README.md` for details.