executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
configuration-model-zooChoose, load, inspect, modify, and validate Detectron2 Yacs, LazyConfig, and model-zoo configurations without relying on the source checkout.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this sub-skill when a request mentions Detectron2 configs, _BASE_, Yacs/YAML, CfgNode, get_cfg, LazyConfig Python files, LazyCall, instantiate, model-zoo config names, checkpoint URLs, MODEL.WEIGHTS, train.init_checkpoint, or CPU/GPU config overrides.
get_cfg(), merge_from_file(), and merge_from_list().LazyConfig.load(), LazyConfig.apply_overrides(), LazyConfig.to_py(), LazyCall, and instantiate().--help first.This sub-skill owns configuration loading, config mutation, static inspection, and official model-zoo path/checkpoint selection. Route dataset registration, dataset dictionaries, COCO JSON schemas, and mappers to ../data-datasets/. Route training launch flags, evaluation commands, and distributed execution to ../training-evaluation/. Route custom component registries and project extensions to ../extension-projects/. Route TorchScript, tracing, Caffe2, and deployment format questions to ../deployment-export/.
model_zoo.get_config() or model_zoo.get_config_file() for config inspection; reserve model_zoo.get() for cases that intentionally build a model and may load checkpoint files.MODEL.DEVICE cpu; LazyConfig model-zoo configs typically require editing cfg.model.device = "cpu" or passing device="cpu" to model_zoo.get() when building.trained=True and model_zoo.get() when validating config syntax only; use get_checkpoint_url() to print a URL without downloading.KEY VALUE tokens, and LazyConfig overrides as key=value strings.