Jason HokuandClaude Fable 5.1
0e563a19cb
`base COUPLE left | right` (2-4 equal columns; COUPLE(rows) for bands; region ` :w` weight) splits a prompt into an unmasked base cond plus one masked cond per region, blended by ComfyUI's own mask/mask_strength path (latent-couple style, one extra UNet pass per region, works for every model family). COUPLE is parsed first; each part still takes AND/CAT/AVG/BREAK. - regional_prompt.py: parser, join helpers (byte-identical output without COUPLE, cache keys depend on it), size-independent region tags, latent-size mask builder with tile/crop frames, apply_regional_masks at sample time - batch_encoding: COUPLE prompts take the combinator path (never the batched TE path) - conditioning_cache: conditioning_v2 keeps every entry and extra key (the old format silently dropped AND prompts); legacy entries are a one-time miss - trigger words, model suffix and HiRes append_end land in the base, not the last region - tiled HiRes and Florence2 crops pass their frame; invalid syntax stops the run early; LTX video warns; Builder tooltip + README section + ProjectStructure/AI-CONTEXT - 107 new tests (parser, masks, encoding, cache round trip, source guards) Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
91 lines
3.3 KiB
Python
91 lines
3.3 KiB
Python
"""conditioning_cache v2: keeps every entry and every extra key (AND prompts, attention masks, region tags)."""
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import importlib.util
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import json
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import os
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import sys
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import pytest
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pytestmark = pytest.mark.requires_torch
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_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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_PKG = os.path.basename(_ROOT)
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sys.path.insert(0, _ROOT)
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torch = pytest.importorskip("torch")
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_spec = importlib.util.spec_from_file_location(f"{_PKG}.conditioning_cache_real",
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os.path.join(_ROOT, "conditioning_cache.py"))
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cc = importlib.util.module_from_spec(_spec)
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_spec.loader.exec_module(cc)
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TAG = {"v": 1, "index": 1, "count": 2, "axis": "cols", "weight": 1.3}
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def _cond():
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return [
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[torch.randn(1, 5, 8), {"pooled_output": torch.randn(1, 4)}],
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[torch.randn(1, 3, 8), {"pooled_output": None, "attention_mask": torch.ones(1, 3, dtype=torch.int64),
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"uscg_region": dict(TAG)}],
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[torch.randn(1, 7, 8), {"pooled_output": torch.randn(1, 4), "uscg_region": dict(TAG, index=0)}],
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]
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def _eq(a, b):
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assert len(a) == len(b)
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for (ta, da), (tb, db) in zip(a, b):
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assert torch.equal(ta, tb) and ta.dtype == tb.dtype
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assert set(da) == set(db)
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for k in da:
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if torch.is_tensor(da[k]):
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assert torch.equal(da[k], db[k]) and da[k].dtype == db[k].dtype
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else:
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assert da[k] == db[k]
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def test_round_trip_three_entries_through_disk(tmp_path):
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c = cc.ConditioningCache(str(tmp_path), "h")
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cond = _cond()
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c.set("p COUPLE a | b", cond)
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c.save()
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on_disk = json.loads((tmp_path / "conditioning_cache.json").read_text())
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assert all("conditioning_v2" in e and "conditioning" not in e for e in on_disk["entries"].values())
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c2 = cc.ConditioningCache(str(tmp_path), "h")
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got = c2.get("p COUPLE a | b")
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assert got is not None and got is not cond
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_eq(got, cond)
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assert c2.stats["hits"] == 1
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def test_legacy_only_entry_is_a_miss(tmp_path):
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c = cc.ConditioningCache(str(tmp_path), "h")
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legacy = c._conditioning_to_dict([[torch.randn(1, 5, 8), {"pooled_output": torch.randn(1, 4)}]])
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c.disk_cache["entries"][c._prompt_key("old")] = {"prompt": "old", "type": "positive", "conditioning": legacy}
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c.save()
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c2 = cc.ConditioningCache(str(tmp_path), "h")
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assert c2.get("old") is None
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assert c2.stats["misses"] == 1
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def test_unserializable_value_is_not_written_but_stays_in_memory(tmp_path):
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c = cc.ConditioningCache(str(tmp_path), "h")
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bad = [[torch.randn(1, 2, 3), {"pooled_output": None, "weird": object()}]]
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c.set("bad", bad)
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assert c.get("bad") is bad # memory cache
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assert c._prompt_key("bad") not in c.disk_cache["entries"]
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c.save()
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assert cc.ConditioningCache(str(tmp_path), "h").get("bad") is None
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def test_bfloat16_is_not_written(tmp_path):
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c = cc.ConditioningCache(str(tmp_path), "h")
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c.set("bf", [[torch.randn(1, 2, 3).to(torch.bfloat16), {"pooled_output": None}]])
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assert c._prompt_key("bf") not in c.disk_cache["entries"]
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def test_disk_cache_disabled_keeps_memory_only(tmp_path):
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c = cc.ConditioningCache(str(tmp_path), "h", enable_disk_cache=False)
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cond = _cond()
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c.set("m", cond)
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assert c.get("m") is cond
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assert c.disk_cache["entries"] == {}
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