chore: fix lint, format, type errors

- ruff format: 2 files reformatted
- ruff check: fix import sort in scripts/infer_pytorch.py
- ty: suppress tree_flatten arg-type (MLX stub imprecision) and
  optional torch import

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

scripts/infer_pytorch.py

@@ -15,10 +15,10 @@ from pathlib import Path
 import numpy as np
 import torch
 import torch.nn.functional as F
-from PIL import Image
 
 # Reuse the GreenFormer and loading logic from dump script
 from dump_pytorch_reference import IMG_SIZE, GreenFormer, load_checkpoint
+from PIL import Image
 
 IMAGENET_MEAN = torch.tensor([0.485, 0.456, 0.406]).reshape(1, 3, 1, 1)
 IMAGENET_STD = torch.tensor([0.229, 0.224, 0.225]).reshape(1, 3, 1, 1)
@@ -94,7 +94,7 @@ def main() -> None:
     # Composite over green
     alpha_f = alpha_np.astype(np.float32) / 255.0
     green = np.array([0, 177, 64], dtype=np.float32)
-    comp_np = (fg_np.astype(np.float32) * alpha_f[..., None] + green * (1 - alpha_f[..., None]))
+    comp_np = fg_np.astype(np.float32) * alpha_f[..., None] + green * (1 - alpha_f[..., None])
     comp_np = comp_np.clip(0, 255).astype(np.uint8)
 
     # Save

src/corridorkey_mlx/weights.py

@@ -116,9 +116,7 @@ def list_assets(release: dict[str, Any]) -> list[dict[str, Any]]:
     return release.get("assets", [])
 
 
-def find_asset(
-    release: dict[str, Any], asset_name: str | None = None
-) -> dict[str, Any]:
+def find_asset(release: dict[str, Any], asset_name: str | None = None) -> dict[str, Any]:
     """Find a specific asset in a release, or infer from platform."""
     assets = list_assets(release)
     target = asset_name or default_asset_name()
@@ -275,9 +273,7 @@ def download_asset(
                 )
             _console.print("[green]Checksum OK[/green]")
         else:
-            _console.print(
-                "[yellow]No checksum file found — skipping verification[/yellow]"
-            )
+            _console.print("[yellow]No checksum file found — skipping verification[/yellow]")
 
     # atomic rename
     partial_path.rename(final_path)

tests/test_conversion.py

@@ -23,7 +23,7 @@ EXPECTED_KEY_COUNT = 365
 
 def _torch_available() -> bool:
     try:
-        import torch  # noqa: F401
+        import torch  # noqa: F401  # type: ignore[import-not-found]
 
         return True
     except ImportError:

tests/test_model_contract.py

@@ -247,7 +247,7 @@ def test_fused_decode_matches_unfused() -> None:
     mx.eval(model_unfused.parameters())  # noqa: S307
 
     model_fused = GreenFormer(img_size=SMALL_IMG_SIZE, fused_decode=True)
-    model_fused.load_weights(tree_flatten(model_unfused.parameters()))
+    model_fused.load_weights(tree_flatten(model_unfused.parameters()))  # type: ignore[arg-type]
     mx.eval(model_fused.parameters())  # noqa: S307
 
     out_u = model_unfused(x)
@@ -276,7 +276,7 @@ def test_fp32_default_unchanged() -> None:
     # Same weights via flattened tree
     from mlx.utils import tree_flatten
 
-    model_explicit.load_weights(tree_flatten(model_default.parameters()))
+    model_explicit.load_weights(tree_flatten(model_default.parameters()))  # type: ignore[arg-type]
     mx.eval(model_explicit.parameters())  # noqa: S307
 
     out_default = model_default(x)