From f30ab9255b485ebd6e5ac051ae2c903859bc5d28 Mon Sep 17 00:00:00 2001 From: cmoyates Date: Sun, 8 Mar 2026 21:29:06 -0230 Subject: [PATCH] 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 --- scripts/infer_pytorch.py | 4 ++-- src/corridorkey_mlx/weights.py | 8 ++------ tests/test_conversion.py | 2 +- tests/test_model_contract.py | 4 ++-- 4 files changed, 7 insertions(+), 11 deletions(-) diff --git a/scripts/infer_pytorch.py b/scripts/infer_pytorch.py index b50b5a7..9e8787f 100644 --- a/scripts/infer_pytorch.py +++ b/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 diff --git a/src/corridorkey_mlx/weights.py b/src/corridorkey_mlx/weights.py index b5ae819..a3889db 100644 --- a/src/corridorkey_mlx/weights.py +++ b/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) diff --git a/tests/test_conversion.py b/tests/test_conversion.py index 1384d37..790229f 100644 --- a/tests/test_conversion.py +++ b/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: diff --git a/tests/test_model_contract.py b/tests/test_model_contract.py index f87c31f..2ed8899 100644 --- a/tests/test_model_contract.py +++ b/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)