[do-not-mirror][do-not-merge] chore(fork): give the gate a git identity - #20

The Linux CI jobs fail while installing the package:

    [Errno 122] Disk quota exceeded

Errno 122 is EDQUOT, hit while unpacking the CUDA torch stack that
`pip install -e .` resolves by default. torch alone is 554.6 MB and the
accompanying nvidia-* wheels add another ~2.4 GB, which no longer fits
the runner's quota. The failure occurs during "Installing build
dependencies", i.e. the isolated PEP 517 build environment is already
enough to exceed it on its own.

The trigger is a runner image change, not a code change:

  * upstream 11_bernhard_dev, 2026-10-20, Image: ubuntu-24.04 -> success
  * same workflows, 2026-10-23, Image: ubuntu-26.04 -> failure

Both resolve an identical wheel set (torch 2.14.1, 554.6 MB). The
`ubuntu-latest` label began migrating to Ubuntu 26 on 2026-10-19
(actions/runner-images#14748), between those two runs. Both workflows
already carry "Free up disk space" steps, so these jobs were running
close to the limit before the migration.

Fix: install CPU-only torch from download.pytorch.org, then build with
--no-build-isolation so the build reuses it instead of resolving torch
a second time. --no-build-isolation needs the build dependencies present
up front, hence the explicit setuptools/wheel/numpy install; the
`setuptools<81` bound matches the pin already in install_requires.

This loses no coverage: BUILD_CUDA_EXT keys off CUDA_HOME/ROCM_HOME,
which is unset on these runners, so the CUDA sources were never compiled
here. tests/smoke_tests/Dockerfile already installs torch this way.

macOS keeps the plain `pip install -e .` unchanged: its PyPI wheels are
already CPU-only, and leaving it alone keeps the default PEP 517
build-isolation path under test somewhere in the matrix.

The shipped puffer_drive.yaml sets policy.fused_slot_encoder=true, and
DriveBackbone raises ImportError when that is set without triton. Two CI
jobs build a policy straight from the shipped config, so Unit Tests and
Notebook Execution have been failing on every pull request:

  ImportError: fused_slot_encoder=true requires triton

The smoke and eval suites already pin the flag off for exactly this reason;
these two call sites were simply missed. test_action_selection only exercises
the discrete-to-continuous action table, which the fused kernel has no part
in, so it pins the flag off outright. The inference notebook keeps the kernel
whenever it has a CUDA device and drops it otherwise, which is also what a
reader running the notebook on a laptop needs.

Neither change touches the training path or the kernel itself: with triton
and a GPU present, both call sites behave exactly as before.

The first run of `Fork gates` on a real feature pull request failed on
every one of them. `forkctl mirror` cherry-picks the commit onto pure
upstream, a cherry-pick commits, and a runner has no git identity, so git
stopped with "Committer identity unknown" before it ever merged anything.
The chore path never caught this because section 4.8 exempts it from
Gate 2, and the feature path could not run in CI until the workflow
existed on the base branch.

`mirror` also reported that failure as "the commit is entangled with
fork-only state" and swallowed what git actually said, which is a false
accusation against a clean commit and sends the reader looking for
fork-only content that is not there. A cherry-pick that stops without
unmerged paths never reached the merge, so the two cases are now told
apart and git's own message is printed.