docs/guides/enterprise_deployment.md: broken example — docker run --gpus all … forgelm:full torchrun --nproc_per_node=4 -m forgelm.cli --config /workspace/config.yaml (DOC-D2B06-005) #201

Wave 1 · theme D1-10: Documentation-only fixes · highest severity High · 1 finding(s) · effort docs fix

Summary

The documented multi-GPU Docker command never starts training.

Primary finding

DOC-D2B06-005 — docs/guides/enterprise_deployment.md: broken example — docker run --gpus all … forgelm:full torchrun --nproc_per_node=4 -m forgelm.cli --config /workspace/config.yaml

severity High · already tracked: KNOWN-OPEN C31-DOCKER-RUNBOOK — docs/roadmap/phase-16-trust-surface-hardening.md:691-692

Where. docs/guides/enterprise_deployment.md:55-62 · type: broken example

The document says. docker run --gpus all … forgelm:full torchrun --nproc_per_node=4 -m forgelm.cli --config /workspace/config.yaml

What the code does. The image's ENTRYPOINT is ["forgelm"], so the trailing words become forgelm torchrun …, and argparse rejects 'torchrun' (invalid choice) with rc 2 (reproduced). It needs --entrypoint torchrun before the image name.

Code references. Dockerfile:112-113

User impact. The documented multi-GPU Docker command never starts training.

Proposed correction. Use docker run --gpus all --shm-size=16g --entrypoint torchrun … forgelm:full --nproc_per_node=4 -m forgelm.cli --config /workspace/config.yaml.

Acceptance criteria

• Each statement is re-checked against the code at fix time.
• Documentation listed above is corrected in English and in its Turkish mirror in the same PR.
• Every finding in this issue is resolved or explicitly closed with a reason.

_{Found by the October 2026 ForgeLM code and documentation review against commit cab2947. Code links point at that commit; line numbers may have moved since. Finding IDs (CR-…, DOC-…, TECH-…) are stable references for this backlog.}