Trim the comments across the diffusion backend
Comment-only pass over the Python this PR touches: drop what the code already says, collapse multi-line explanations that still read on one line, and keep the reasoning that is not recoverable from the code. No code, docstring semantics or behaviour changes; verified with an AST comparison against the previous revision, and the backend suite is unchanged (same 37 environment failures as before: the API integration tests that need a live keyed server, the flash-attn install hooks, and the GPU memory fields).
This commit is contained in:
Daniel Han
parent
ea3c3822a1
commit
36df317293
113 changed files with 3389 additions and 4087 deletions
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@ -83,10 +83,10 @@ def _loaded_backend(fam_name = "z-image", engine = None):
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def test_loaded_repo_ids_includes_native_companions():
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# The one-shot native engine re-reads its companion VAE / text-encoder files from the HF
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# cache on every generation, so the delete-cached guard queries loaded_repo_ids() to refuse
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# deleting an in-use companion repo. It must surface the committed family's VAE + text-encoder
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# repos (plus the main + base repos), not just the loaded GGUF, and be empty once unloaded.
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# The one-shot native engine re-reads its companion VAE / text-encoder files from the HF cache on
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# every generation, so the delete-cached guard queries loaded_repo_ids() to refuse deleting an
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# in-use companion repo. It must surface the committed family's VAE + text-encoder repos (plus the
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# main + base repos), not just the loaded GGUF, and be empty once unloaded.
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b = _loaded_backend("flux.1")
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ids = set(b.loaded_repo_ids())
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fam = detect_family("flux.1")
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@ -207,8 +207,8 @@ def test_asset_specs_cover_required_files(fam_name, expect_kinds):
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def test_asset_specs_flux2_klein_selects_encoder_by_variant():
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# FLUX.2-klein 4B pairs with Qwen3-4B, 9B with Qwen3-8B; the encoder must be chosen from the
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# load identity, not the family's single default (a mismatched encoder fails deep in sd-cli).
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# FLUX.2-klein 4B pairs with Qwen3-4B, 9B with Qwen3-8B, so the encoder must be chosen from the
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# load identity, not the family default (a mismatched encoder fails deep in sd-cli).
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b = SdCppDiffusionBackend(engine = _FakeEngine())
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fam = detect_family("flux.2-klein")
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@ -323,9 +323,8 @@ def test_generate_progress_tracks_parsed_steps():
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def test_generate_publishes_progress_before_lora_resolution(monkeypatch):
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# LoRA resolution runs during pre-generate setup while _generate_lock is held, so a progress
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# probe in that window must read ACTIVE; _gen is published before it, mirroring the diffusers
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# path.
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# LoRA resolution runs during pre-generate setup while _generate_lock is held, so a progress probe
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# in that window must read ACTIVE; _gen is published before it, mirroring the diffusers path.
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from core.inference import diffusion_lora
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eng = _FakeEngine()
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@ -371,9 +370,8 @@ def test_begin_load_requires_gguf_filename():
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def test_begin_load_resolves_family_from_filename_only(monkeypatch):
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# A local .gguf pick whose family keyword lives only in the basename (parent dir
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# carries none) must resolve via the same filename fallback the route validated
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# with -- not dead-end with "Could not infer" on a native (no-GPU) host.
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# A local .gguf pick whose family keyword lives only in the basename must resolve via the same
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# filename fallback the route validated with, not dead-end with "Could not infer" on a native host.
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b = SdCppDiffusionBackend(engine = _FakeEngine())
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monkeypatch.setattr(b, "_run_load", lambda **kwargs: None) # skip the download thread
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b.begin_load("/models/gguf-store", gguf_filename = "Z-Image-Turbo-Q4_K_M.gguf")
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@ -402,8 +400,8 @@ def test_unload_clears_state_and_signals_cancel():
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def test_status_reports_offload_when_flags_active():
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# status must reflect the offload flags actually passed to sd-cli, not always "none",
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# so a balanced/low_vram (or cpu_offload) load is verifiable.
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# status must reflect the offload flags actually passed to sd-cli, not always "none", so a
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# balanced/low_vram (or cpu_offload) load is verifiable.
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b = _loaded_backend()
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# No flags (CPU default) -> none.
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assert b.status()["offload_policy"] == "none" and b.status()["cpu_offload"] is False
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@ -422,10 +420,9 @@ def test_status_reports_offload_when_flags_active():
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def test_run_load_cancels_and_waits_for_inflight_generation(monkeypatch):
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# A generation that started during the asset download is still running against the OLD
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# model. _run_load must cancel it AND wait on _generate_lock before committing the new
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# state, or a stale sd-cli run finishes afterward and persists an image from the previous
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# model once the new load reports ready.
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# A generation that started during the asset download is still running against the OLD model.
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# _run_load must cancel it AND wait on _generate_lock before committing the new state, or a stale
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# sd-cli run persists an image from the previous model once the new load reports ready.
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b = SdCppDiffusionBackend(engine = _FakeEngine())
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fam = detect_family("z-image")
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monkeypatch.setattr(b, "_asset_specs", lambda *a, **k: [])
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@ -435,8 +432,8 @@ def test_run_load_cancels_and_waits_for_inflight_generation(monkeypatch):
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"_fetch_assets",
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lambda *a, **k: {"diffusion_model": "/m/z.gguf", "vae": "/m/vae.sft", "llm": "/m/llm.sft"},
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)
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# Avoid importing torch from the worker thread (its first import deadlocks off the main
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# thread -- a test artifact, not a production path); the device only needs to be CPU here.
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# Avoid importing torch from the worker thread (its first import deadlocks off the main thread, a
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# test artifact); the device only needs to be CPU here.
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monkeypatch.setattr(
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bk, "resolve_diffusion_device_target", lambda: types.SimpleNamespace(device = "cpu")
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)
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@ -461,8 +458,8 @@ def test_run_load_cancels_and_waits_for_inflight_generation(monkeypatch):
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b._generate_lock.acquire() # simulate the live denoise holding _generate_lock
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try:
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threading.Thread(target = _load, daemon = True).start()
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# The commit must block behind the live generation and not publish the new state,
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# but must already have signalled the in-flight cancel.
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# The commit must block behind the live generation and not publish the new state, but must already
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# have signalled the in-flight cancel.
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assert not committed.wait(0.5)
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assert b._state is None
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assert cancel.is_set()
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@ -498,8 +495,8 @@ def test_resolve_backend_falls_back_to_oneshot_without_server(monkeypatch):
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def test_resolve_backend_cached_fallback_engine_does_not_pin_oneshot(monkeypatch):
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# A lazily cached fallback engine (NOT an explicit injection) must not force one-shot:
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# once a server is available again, the next load can use it.
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# A lazily cached fallback engine (NOT an explicit injection) must not force one-shot: once a
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# server is available again, the next load can use it.
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b = SdCppDiffusionBackend() # no injected engine
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b._engine = _FakeEngine() # simulate a prior lazy one-shot fallback caching the engine
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monkeypatch.setattr(bk, "find_sd_server_binary", lambda: "/x/sd-server")
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@ -571,8 +568,8 @@ def test_server_generate_uses_one_request_for_whole_batch(monkeypatch):
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def test_server_generate_splits_batches_above_server_limit(monkeypatch):
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# A batch above the server's per-job limit is chunked (the one-shot path did these
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# image-by-image); each chunk gets a timeout proportional to its image count.
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# A batch above the server's per-job limit is chunked (the one-shot path did these image-by-image);
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# each chunk gets a timeout proportional to its image count.
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b = SdCppDiffusionBackend()
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servers: list = []
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_run_server_load(monkeypatch, b, servers)
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@ -591,8 +588,8 @@ def test_server_generate_splits_batches_above_server_limit(monkeypatch):
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def test_server_generate_masks_large_seed(monkeypatch):
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# sd.cpp's image seed is signed int64; a larger explicit seed must be masked before it
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# reaches the server (the request model / diffusers accept up to 2**64 - 1).
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# sd.cpp's image seed is signed int64, so a larger explicit seed must be masked before it reaches
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# the server (the request model / diffusers accept up to 2**64 - 1).
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b = SdCppDiffusionBackend()
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servers: list = []
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_run_server_load(monkeypatch, b, servers)
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@ -684,7 +681,7 @@ def test_server_start_failure_falls_back_to_oneshot(monkeypatch):
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# A present-but-broken sd-server must not fail the load when sd-cli works.
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b = SdCppDiffusionBackend()
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monkeypatch.setattr(bk, "find_sd_server_binary", lambda: "/x/sd-server")
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# Probe passes; the failure we exercise here is in start(), not the up-front probe.
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# The probe passes; the failure exercised here is in start(), not the up-front probe.
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monkeypatch.setattr(bk, "_server_binary_runnable", lambda *_a, **_k: True)
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class _BadServer:
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@ -727,8 +724,8 @@ def test_server_start_failure_falls_back_to_oneshot(monkeypatch):
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def test_run_load_redacts_paths_in_progress_error(monkeypatch):
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# A load failure surfaced via load_progress() must run through redact_native_paths, the
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# same scrub the diffusers load path applies, so a registered native path can't leak.
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# A load failure surfaced via load_progress() must run through redact_native_paths, the same scrub
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# the diffusers load path applies, so a registered native path can't leak.
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from utils import native_path_leases as npl
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secret_root = "/managed/native/root"
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@ -811,9 +808,9 @@ def test_generate_oneshot_applies_loras_via_prompt_tags(monkeypatch):
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def test_generate_server_stages_loras_and_sends_structured_field(monkeypatch, tmp_path):
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# Server-mode LoRA rides the structured `lora` request field (the sdcpp API ignores
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# <lora:> prompt tags): adapters staged into the server's --lora-model-dir, referenced
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# by their path relative to it + the validated multiplier.
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# Server-mode LoRA rides the structured `lora` request field (the sdcpp API ignores <lora:> prompt
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# tags): adapters staged into the server's --lora-model-dir, referenced by their path relative to
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# it + the validated multiplier.
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from pathlib import Path as _P
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from core.inference import diffusion_lora as dl
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@ -843,8 +840,8 @@ def test_generate_rejects_loras_on_unsupported_family(monkeypatch):
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def test_generate_zero_weight_loras_are_noop(monkeypatch):
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# weight-0 rows are dropped BEFORE the support gate, so a request carrying only disabled
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# adapters stays a no-op even on a family where native LoRA is unsupported.
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# weight-0 rows are dropped BEFORE the support gate, so a request carrying only disabled adapters
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# stays a no-op even on a family where native LoRA is unsupported.
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eng = _FakeEngine()
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b = _loaded_backend(engine = eng)
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_patch_lora(monkeypatch, [], supported = False) # would raise if the gate were reached
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@ -854,9 +851,8 @@ def test_generate_zero_weight_loras_are_noop(monkeypatch):
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def test_generate_rejects_controlnet_on_native_engine():
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# ControlNet is diffusers-only. The route passes `controlnet` to whichever engine is
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# active, so the native backend must reject it with a clean ValueError (-> 400) rather
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# than TypeError on an unexpected kwarg (-> opaque 500).
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# ControlNet is diffusers-only. The route passes `controlnet` to whichever engine is active, so the
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# native backend must reject it with a clean ValueError (400) rather than TypeError (500).
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b = _loaded_backend(engine = _FakeEngine())
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with pytest.raises(ValueError, match = "ControlNet is not yet supported on the native"):
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b.generate(prompt = "x", steps = 4, seed = 1, controlnet = ("id", "img", "canny", 1.0, 0.0, 1.0))
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@ -864,9 +860,9 @@ def test_generate_rejects_controlnet_on_native_engine():
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@pytest.mark.parametrize("cn_strength", [0, 0.0, None])
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def test_generate_treats_zero_strength_controlnet_as_disabled(cn_strength):
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# strength 0 (or None) disables ControlNet -- the diffusers path treats it as plain
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# txt2img and the request model documents it -- so a strength-0 spec must succeed on the
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# native engine too, not 400. Only a genuinely active (strength > 0) ControlNet is rejected.
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# strength 0 (or None) disables ControlNet -- the diffusers path treats it as plain txt2img -- so a
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# strength-0 spec must succeed on the native engine too. Only a genuinely active ControlNet is
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# rejected.
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eng = _FakeEngine()
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b = _loaded_backend(engine = eng)
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out = b.generate(
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@ -879,8 +875,8 @@ def test_generate_treats_zero_strength_controlnet_as_disabled(cn_strength):
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def test_generate_rejects_image_conditioned_on_native_engine():
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# img2img / inpaint / reference / upscale are likewise diffusers-only; a direct API call
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# with an init image on the native engine gets a clean ValueError, not a silent txt2img.
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# img2img / inpaint / reference / upscale are likewise diffusers-only; a direct API call with an
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# init image on the native engine gets a clean ValueError, not a silent txt2img.
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b = _loaded_backend(engine = _FakeEngine())
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with pytest.raises(ValueError, match = "not yet supported on the native"):
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b.generate(prompt = "x", steps = 4, seed = 1, init_image = "data:image/png;base64,AAAA")
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