150c974eed
* feat(phase3): PyTorch→MLX weight converter + safetensors output 365 keys mapped (367 source - 2 num_batches_tracked skipped). Conv weights transposed (O,I,H,W→O,H,W,I), refiner stem remapped, 4ch patch embed preserved. 12 conversion tests + diagnostic report. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(phase3): conv allowlist, unused var, test fixture - Replace _is_conv_weight heuristic with explicit CONV_WEIGHT_KEYS frozenset (15 keys) - Remove unused `skipped` list from convert_state_dict - Module-scoped pytest fixture eliminates 11 redundant checkpoint loads Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
60 lines
2.3 KiB
Markdown
60 lines
2.3 KiB
Markdown
---
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title: Fix converter review feedback (items 4, 1, 2)
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type: fix
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date: 2026-03-01
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---
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# Fix converter review feedback
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Three fixes from PR #1 review, ordered by simplicity.
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## Fix 4: Remove unused `skipped` list
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**File:** `src/corridorkey_mlx/convert/converter.py:105,110`
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Delete the `skipped` list variable and its `.append()` call. The skip logic already works via `continue` — the list serves no purpose.
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## Fix 1: Explicit conv key allowlist
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**File:** `src/corridorkey_mlx/convert/converter.py:60-66`
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Replace heuristic `_is_conv_weight()` with an explicit `CONV_WEIGHT_KEYS: frozenset[str]` allowlist. This matches the "no regex guessing, no silent fallbacks" philosophy.
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The 15 conv keys (from checkpoint analysis + tests):
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- `encoder.model.patch_embed.proj.weight` — (112,4,7,7)
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- `alpha_decoder.linear_fuse.weight` — (256,1024,1,1)
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- `fg_decoder.linear_fuse.weight` — (256,1024,1,1)
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- `refiner.stem.0.weight` (pre-remap) — (64,7,3,3)
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- `refiner.res{1-4}.conv{1-2}.weight` — 8 keys, all (64,64,3,3)
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- `refiner.final.weight` — (4,64,1,1)
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**Note:** Use pre-remap key names since `_is_conv_weight` is called before remapping in the loop. Total: 15 keys.
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Replace `_is_conv_weight(key, arr)` → simple `key in CONV_WEIGHT_KEYS` check. Remove the `arr` parameter.
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## Fix 2: Module-scoped test fixture
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**File:** `tests/test_conversion.py`
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Add a `@pytest.fixture(scope="module")` that loads + converts once, shared by all tests. This avoids 11 redundant `load_pytorch_checkpoint` + `convert_state_dict` calls.
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```python
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@pytest.fixture(scope="module")
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def converted_checkpoint():
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if not CHECKPOINT_PATH.exists():
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pytest.skip("Checkpoint not found")
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state_dict = load_pytorch_checkpoint(CHECKPOINT_PATH)
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converted, diagnostics = convert_state_dict(state_dict)
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return state_dict, converted, diagnostics
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```
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Each test method takes `converted_checkpoint` as param, destructures what it needs. Remove `_skip_if_no_checkpoint()` helper.
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## Acceptance Criteria
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- [ ] `skipped` list removed from `convert_state_dict`
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- [ ] `CONV_WEIGHT_KEYS` frozenset with 15 keys replaces `_is_conv_weight` heuristic
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- [ ] Module-scoped fixture eliminates repeated checkpoint loading
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- [ ] `uv run pytest tests/test_conversion.py -v` — 12/12 pass
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- [ ] `uv run ruff check .` — clean
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