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name: deployment-export description: "Export, inspect, and benchmark Detectron2 models with TorchScript, optional Caffe2/ONNX paths, and safe command construction." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Detectron2 Deployment Export

Use this sub-skill when a task involves exporting a Detectron2 model for deployment, choosing between tracing/scripting/Caffe2 tracing, inspecting TorchScript IR, preparing ONNX/Caffe2 attempts, building export commands, analyzing FLOPs/parameters/activations, or planning benchmark runs.

Fast Routing

• Read references/export-workflows.md to choose tracing, scripting, or optional caffe2_tracing, and to understand format/runtime limits.
• Use scripts/export_command_builder.py to print a validated export command without importing Detectron2, loading weights, building a model, or writing output files.
• Read references/analysis-and-benchmarking.md before FLOP, activation, parameter, structure, data-loader, train, or eval benchmark work.
• Use scripts/analyze_command_builder.py to print a validated model-analysis command without building a model.
• Read references/model-conversion.md for TorchScript input schema, Caffe2/ONNX caveats, and torchvision checkpoint conversion guidance.
• Read references/troubleshooting.md when export fails, optional dependencies are missing, model families are unsupported, sample inputs are absent, or benchmark results are hardware-sensitive.

Safe Defaults

• Prefer --export-method tracing --format torchscript for a first deployable artifact when a valid sample image or dataset sample is available.
• Prefer --export-method scripting --format torchscript when dynamic batch size is required and the model family is scriptable.
• Treat caffe2_tracing, Caffe2 protobuf, and ONNX as optional paths that require extra dependency and runtime checks.
• Keep export and analysis dry-run planning separate from actual execution; the bundled scripts print commands only.
• Ask before running export, evaluation, benchmark, or analysis commands that load weights, touch datasets, write large output directories, or use GPU/accelerator resources.

Boundary Notes

This sub-skill owns deployment export method/format selection, TracingAdapter, scripting_with_instances, dump_torchscript_IR, optional Caffe2/ONNX planning, command construction, model analysis, and benchmark safety. Route config discovery and model-zoo checkpoint selection to ../configuration-model-zoo/. Route dataset registration and loaders to ../data-datasets/. Route training and evaluator semantics to ../training-evaluation/. Route custom trace/script compatibility design for new architectures or project extensions to ../extension-projects/.