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training-and-evaluation

training-and-evaluation

Compose safe distributed BEVFormer training, evaluation, and FP16 launch commands while explaining launcher, checkpoint, and runtime gates.

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Skill documentation

GitHub

name: training-and-evaluation description: "Compose safe distributed BEVFormer training, evaluation, and FP16 launch commands while explaining launcher, checkpoint, and runtime gates." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

training-and-evaluation

Compose command-only guidance for BEVFormer train/eval flows.

Use this sub-skill for

  • distributed training launches for tools/train.py
  • distributed evaluation launches for tools/test.py
  • FP16 training launches for tools/fp16/train.py
  • --work-dir, --resume-from, --cfg-options, launcher, and port questions
  • checkpoint and GPU/NCCL prerequisite triage

Route away when

  • data layout, CAN bus, or annotation files need validation -> dataset-preparation
  • config summaries, model-family choices, or install/import issues need analysis -> installation-and-configs
  • logs, plots, throughput, or visual outputs are the goal -> analysis-and-utilities

Bundled helpers

  • scripts/bevformer_train_command.py
  • scripts/bevformer_eval_command.py

Read first

  • references/training-and-evaluation.md
  • references/cli-reference.md
  • references/troubleshooting.md

Operating rules

  • Do not run training or evaluation from this sub-skill.
  • Prefer distributed launch commands; the repo's eval path does not support a non-distributed shortcut.
  • Keep data and checkpoint prerequisites explicit in every command handoff.
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