add libero

examples/5_train_libero.sh

@@ -0,0 +1,59 @@
+#!/bin/bash
+
+# config
+REPO_ID=physical-intelligence/libero
+TASK=libero_10
+OUTPUT_DIR=./outputs/train_run/smolvla2_libero
+
+# clean previous run
+rm -rf $OUTPUT_DIR
+
+# training params
+STEPS=100000
+BATCH_SIZE=4
+EVAL_FREQ=2000
+SAVE_FREQ=10000
+NUM_WORKERS=0
+
+# model params
+POLICY=smolvla
+USE_AMP=false
+OPTIMIZER_LR=1e-4
+PEFT_METHOD=lora
+LOAD_VLM_WEIGHTS=true
+VLM_REPO_ID=None
+MAX_ACTION_DIM=32
+MAX_STATE_DIM=32
+
+# dataset/image params
+USE_IMAGENET_STATS=false
+ENABLE_IMG_TRANSFORM=true
+MAX_NUM_IMAGES=2
+MAX_IMAGE_DIM=1024
+
+echo -e "\033[1;33m[WARNING]\033[0m LIBERO is not yet fully supported in this PR!"
+# launch
+MUJOCO_GL=egl python src/lerobot/scripts/train.py \
+  --policy.type=$POLICY \
+  --dataset.repo_id=$REPO_ID \
+  --env.type=libero \
+  --env.task=$TASK \
+  --output_dir=$OUTPUT_DIR \
+  --steps=$STEPS \
+  --batch_size=$BATCH_SIZE \
+  --eval_freq=$EVAL_FREQ \
+  --save_freq=$SAVE_FREQ \
+  --num_workers=$NUM_WORKERS \
+  --policy.max_action_dim=$MAX_ACTION_DIM \
+  --policy.max_state_dim=$MAX_STATE_DIM \
+  --policy.use_amp=$USE_AMP \
+  --policy.optimizer_lr=$OPTIMIZER_LR \
+  --policy.peft_method=$PEFT_METHOD \
+  --policy.load_vlm_weights=$LOAD_VLM_WEIGHTS \
+  --policy.repo_id=$VLM_REPO_ID \
+  --dataset.use_imagenet_stats=$USE_IMAGENET_STATS \
+  --dataset.image_transforms.enable=$ENABLE_IMG_TRANSFORM \
+  --dataset.max_num_images=$MAX_NUM_IMAGES \
+  --dataset.max_image_dim=$MAX_IMAGE_DIM \
+  # --policy.exclude_image_keys=wrist_image \
+  # --policy.use_env_state=false