File size: 5,479 Bytes
0d80452 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 | #!/usr/bin/env bash
set -euo pipefail
REPO_ID="NLTuan/diffusion_aloha_transfer_cube"
OUTPUT_DIR="outputs/train/diffusion_aloha_transfer_cube"
JOB_NAME="diffusion_aloha_transfer_cube"
CHUNK_SIZE=20000
FINAL_STEPS=100000
if ! command -v uv >/dev/null 2>&1; then
echo "uv is required but was not found on PATH." >&2
exit 1
fi
uv run hf auth whoami >/dev/null
uv run wandb status >/dev/null || true
remote_pretrained_revision_exists() {
local revision="$1"
uv run python - "${REPO_ID}" "${revision}" <<'PY'
import sys
from huggingface_hub import HfApi
from huggingface_hub.errors import RepositoryNotFoundError, RevisionNotFoundError
repo_id, revision = sys.argv[1:]
api = HfApi()
try:
files = set(api.list_repo_files(repo_id, repo_type="model", revision=revision))
except (RepositoryNotFoundError, RevisionNotFoundError):
raise SystemExit(1)
required = {"config.json", "model.safetensors"}
raise SystemExit(0 if required.issubset(files) else 1)
PY
}
export MUJOCO_GL="${MUJOCO_GL:-egl}"
export PYOPENGL_PLATFORM="${PYOPENGL_PLATFORM:-egl}"
upload_checkpoint() {
local step="$1"
local step_id
step_id="$(printf "%06d" "${step}")"
local checkpoint_dir="${OUTPUT_DIR}/checkpoints/${step_id}"
local revision="ckpt-${step_id}"
if [[ ! -d "${checkpoint_dir}/pretrained_model" || ! -d "${checkpoint_dir}/training_state" ]]; then
echo "Expected full checkpoint at ${checkpoint_dir}, but it is incomplete or missing." >&2
exit 1
fi
if remote_pretrained_revision_exists "${revision}"; then
echo "Checkpoint ${revision} already exists on Hugging Face; skipping upload."
return
fi
uv run python - "${REPO_ID}" "${revision}" "${checkpoint_dir}" "${step_id}" <<'PY'
import sys
from huggingface_hub import HfApi
repo_id, revision, checkpoint_dir, step_id = sys.argv[1:]
api = HfApi()
api.create_repo(repo_id, repo_type="model", private=False, exist_ok=True)
api.create_branch(repo_id, branch=revision, repo_type="model", exist_ok=True)
api.upload_folder(
repo_id=repo_id,
repo_type="model",
revision=revision,
folder_path=f"{checkpoint_dir}/pretrained_model",
path_in_repo=".",
commit_message=f"Upload pretrained model files for checkpoint {step_id}",
)
api.upload_folder(
repo_id=repo_id,
repo_type="model",
revision=revision,
folder_path=f"{checkpoint_dir}/training_state",
path_in_repo="training_state",
commit_message=f"Upload training state for checkpoint {step_id}",
)
PY
}
delete_checkpoint() {
local step="$1"
local step_id
step_id="$(printf "%06d" "${step}")"
local checkpoint_dir="${OUTPUT_DIR}/checkpoints/${step_id}"
if [[ -d "${checkpoint_dir}" ]]; then
rm -rf "${checkpoint_dir}"
fi
}
run_first_chunk() {
uv run lerobot-train \
--dataset.repo_id=lerobot/aloha_sim_transfer_cube_human \
--env.type=aloha \
--env.task=AlohaTransferCube-v0 \
--policy.type=diffusion \
--policy.repo_id="${REPO_ID}" \
--policy.push_to_hub=false \
--policy.private=false \
--policy.device=cuda \
--policy.use_amp=false \
--policy.n_obs_steps=2 \
--policy.horizon=64 \
--policy.n_action_steps=32 \
--policy.resize_shape=[224,224] \
--policy.num_train_timesteps=100 \
--policy.num_inference_steps=50 \
--policy.optimizer_lr=1e-4 \
--policy.optimizer_lr_backbone=1e-5 \
--batch_size=24 \
--steps="${CHUNK_SIZE}" \
--save_freq="${CHUNK_SIZE}" \
--env_eval_freq="${CHUNK_SIZE}" \
--eval.n_episodes=20 \
--eval.batch_size=10 \
--eval.use_async_envs=false \
--wandb.enable=true \
--wandb.disable_artifact=true \
--wandb.project=lerobot-diffusion \
--wandb.mode=online \
--job_name="${JOB_NAME}" \
--output_dir="${OUTPUT_DIR}"
}
run_resume_chunk() {
local previous_step="$1"
local target_step="$2"
local previous_id
previous_id="$(printf "%06d" "${previous_step}")"
uv run lerobot-train \
--config_path="${OUTPUT_DIR}/checkpoints/${previous_id}/pretrained_model/train_config.json" \
--resume=true \
--policy.push_to_hub=false \
--steps="${target_step}" \
--save_freq="${CHUNK_SIZE}" \
--env_eval_freq="${CHUNK_SIZE}" \
--eval.n_episodes=20 \
--eval.batch_size=10 \
--eval.use_async_envs=false \
--wandb.enable=true \
--wandb.disable_artifact=true \
--wandb.project=lerobot-diffusion \
--wandb.mode=online
}
main() {
local previous_step=0
local target_step="${CHUNK_SIZE}"
while [[ "${target_step}" -le "${FINAL_STEPS}" ]]; do
local target_id
target_id="$(printf "%06d" "${target_step}")"
local target_checkpoint="${OUTPUT_DIR}/checkpoints/${target_id}"
if [[ -d "${target_checkpoint}/pretrained_model" && -d "${target_checkpoint}/training_state" ]]; then
echo "Checkpoint ${target_id} already exists locally; skipping training for this chunk."
elif [[ "${previous_step}" -eq 0 ]]; then
run_first_chunk
else
run_resume_chunk "${previous_step}" "${target_step}"
fi
upload_checkpoint "${target_step}"
if [[ "${previous_step}" -gt 0 ]]; then
delete_checkpoint "${previous_step}"
fi
previous_step="${target_step}"
target_step=$((target_step + CHUNK_SIZE))
done
echo "Done. Final local checkpoint is ${OUTPUT_DIR}/checkpoints/$(printf "%06d" "${FINAL_STEPS}")"
echo "Uploaded revisions: ckpt-020000 ckpt-040000 ckpt-060000 ckpt-080000 ckpt-100000"
}
if [[ "${BASH_SOURCE[0]}" == "$0" ]]; then
main "$@"
fi
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