tao-train-dino
DINO
DINO (DETR with Improved DeNoising Anchor Boxes) for 2D object detection. Transformer-based detector with denoising training, multi-scale features, and optional distillation support.
Uses pretrained backbone weights (e.g. ResNet-50 ImageNet). Set model.pretrained_backbone_path for backbone-only or train.pretrained_model_path for full model.
For TAO Deploy TensorRT actions (gen_trt_engine, TensorRT evaluate, and
TensorRT inference), read references/tao-deploy-dino.md first. Deploy spec templates live
in this skill's references/ folder with the spec_template_deploy_*.yaml
prefix.
Generated TAO Core schemas are packaged in schemas/<action>.schema.json (with schemas/manifest.json listing actions); each schema emits a matching references/spec_template_<action>.yaml. See references/sdk_orchestration.md for the full dataclass-schema, spec-template, data-sources, and parent-model inference details used by SDK orchestration.
Train Action Policy
This model is AutoML-enabled at the model layer. Before handling any train-stage request, read references/skill_info.yaml and resolve the run override from either an explicit automl_policy value or the user's workflow request. Treat phrases like "turn off AutoML", "disable AutoML", "no HPO", or "plain training" as automl_policy: off for this run only; otherwise default to auto. When automl_policy: auto, automl_enabled: true, and both schemas/train.schema.json and references/spec_template_train.yaml are packaged, route the train action through tao-skill-bank:tao-run-automl by default with this model's skill_dir. Preserve workflow/application overrides for datasets, specs, output directories, GPU/platform settings, parent checkpoints, and automl_policy. Use direct model training only when automl_policy: off or the packaged train schema/template is missing; in the missing-schema case, report that AutoML is enabled but not runnable for this model until schemas are generated.
Non-train actions such as evaluate, inference, export, and deploy flows stay in this model skill. The per-run automl_policy override does not change model metadata.