add wall-oss-0.5

scripts/README.md

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+# Scripts
+
+This directory contains the public Wall-X command-line helpers. Run commands
+from the repository root unless noted otherwise.
+
+## Inference smoke test
+
+Use `fake_inference.py` to verify that a checkpoint can be loaded and can
+produce one action chunk from a synthetic LIBERO-style observation.
+
+```bash
+python scripts/fake_inference.py \
+  --checkpoint-path /path/to/checkpoint
+```
+
+If the training config is not stored next to the checkpoint as `config.yml` or
+`config.yaml`, pass it explicitly:
+
+```bash
+python scripts/fake_inference.py \
+  --checkpoint-path /path/to/checkpoint \
+  --train-config-path /path/to/config.yml
+```
+
+## LIBERO evaluation
+
+`run_libero.sh` is a small shell wrapper around `infer_libero.py`.
+
+```bash
+CHECKPOINT_PATH=/path/to/checkpoint bash scripts/run_libero.sh
+```
+
+Useful environment variables:
+
+```bash
+CHECKPOINT_PATH=/path/to/checkpoint
+TRAIN_CONFIG_PATH=/path/to/config.yml
+TASK_SUITE_NAME=libero_spatial
+TASK_INDICES=0,1,2
+NUM_TRIALS_PER_TASK=50
+CUDA_ID=0
+SMOKE=1
+```
+
+For full control, call the Python entry directly:
+
+```bash
+python scripts/infer_libero.py \
+  --checkpoint-path /path/to/checkpoint \
+  --task-suite-name libero_spatial \
+  --num-trials-per-task 50 \
+  --driver-mode in_process
+```
+
+You can also pass a complete harrix eval config:
+
+```bash
+python scripts/infer_libero.py --config /path/to/eval_config.yml
+```
+
+## Dataset and checkpoint utilities
+
+- `compute_norm_stats.py`: compute action normalization statistics for a
+  LeRobot dataset.
+- `merge_sharded_weights.py`: merge FSDP sharded checkpoint files into a single
+  checkpoint directory.
+- `normalize.py`: helper for generating normalization files from dataset
+  statistics.
+
+Most scripts support `--help` for their command-line options.