tao-train-dinov3

DINOv3

Standalone install? If this session was not initialized by the TAO skill bank plugin, run the tao-setup skill first.

Use this skill to continue self-supervised training of a DINOv3 backbone on unlabeled images, then convert, export, or run inference with a trained teacher checkpoint.

Quick Start (docker run)

Docker-native launch — no TAO SDK and no Python on the host. Use the local Docker/platform skill instead when it gives a stricter environment-specific command (non-root UID mapping, cache redirects, remote daemons).

TAO_PYT_IMAGE_DEFAULT=nvcr.io/nvstaging/tao/tao-toolkit-pyt:7.2.0-rc-36-multiarch  # versions-key: images.tao_toolkit.pyt
TAO_PYT_IMAGE="${TAO_PYT_IMAGE:-$TAO_PYT_IMAGE_DEFAULT}"
RUN_ROOT="${RUN_ROOT:-$PWD}"
DOCKER_COMMON=(
  --rm --gpus all --ipc=host
  --shm-size=8g
  --ulimit memlock=-1
  --ulimit stack=67108864
  -v "$RUN_ROOT/data:/data:ro"
  -v "$RUN_ROOT/specs:/specs:ro"
  -v "$RUN_ROOT/results:/results"
)

Train:

docker run "${DOCKER_COMMON[@]}" "$TAO_PYT_IMAGE" \
  dinov3 train -e /specs/train.yaml

Inference:

docker run "${DOCKER_COMMON[@]}" "$TAO_PYT_IMAGE" \
  dinov3 inference -e /specs/inference.yaml

Export:

docker run "${DOCKER_COMMON[@]}" "$TAO_PYT_IMAGE" \
  dinov3 export -e /specs/export.yaml

Convert:

docker run "${DOCKER_COMMON[@]}" "$TAO_PYT_IMAGE" \
  dinov3 convert -e /specs/convert.yaml

Every action takes its spec with -e; results_dir is set in the spec or overridden on the command line. Mount any pretrained-weights directory the spec references, and keep every in-container path consistent across actions.

Configuration

Use schemas/<action>.schema.json for supported fields, defaults, ranges, and options. Start from the matching references/spec_template_<action>.yaml.

Training is AutoML-enabled. Read references/skill_info.yaml and resolve an explicit automl_policy or user request before training. Default to automl_policy: on; requests such as "disable AutoML", "no HPO", or "plain training" mean off for that run. When it is on and the train schema and template are packaged, route training through tao-skill-bank:tao-run-automl. Use direct training only when the policy is off or those files are missing, and report the missing-file limitation. Non-train actions remain in this skill.