Run & Write CPU Tests

docs/contributing/testing_guide.md is authoritative for the layer hierarchy, the *_on_cpu.py naming rule, placement, coverage, the local pytest invocations, and the steps for adding a test. Follow it. This skill adds what it does not cover.

What CI does that the guide's local commands don't

• The CPU job exports TORCH_COMPILE_DISABLE=1 and TORCHINDUCTOR_DISABLE=1 (.github/workflows/cpu_unit_tests.yml). Set both locally when reproducing a failure that only CI sees.
• On pull requests the job triggers on types: [labeled] and only when the label is ci — a green checks page on an unlabelled PR means the tests never ran. The label is single-use: drop-ci-labels.yml removes it on every synchronize, so a new push does not re-run the job until you re-add ci.
• tests/special_sanity/ runs as its own job; those files are test_*.py, so the CPU job's python_files override deliberately skips them.

Idioms the guide leaves to the reader

Configs — construct normally:

cfg = DiffusionLossConfig(loss_mode="flow_dppo")

Bypass __init__ only when __post_init__ does I/O (loading tokenizers, resolving paths), as DiffusionModelConfig does:

cfg = object.__new__(DiffusionModelConfig)
object.__setattr__(cfg, "architecture", "QwenImagePipeline")
object.__setattr__(cfg, "algorithm", "dpo")

object.__setattr__ is needed because BaseConfig gates assignment through _mutable_fields, not because the dataclass is frozen (config.md). Reaching for this where plain construction works is a review comment.

Mocks and assertions — MagicMock the transformer and assert on call args and output shapes rather than on real model output. TensorDict batches usually carry metadata, not pixels (TensorDict({}, batch_size=2) plus the fields under test). Use torch.testing.assert_close(a, b, rtol=..., atol=...) for tensors and pytest.approx for scalars — never .equal() on floats.

Before opening a PR

Paste the command and its output into the PR body (mandatory — commit-and-pr), then run pre-commit run --all-files.