8be8d003e7
Script + pytest tests to verify MLX inference works at CorridorKey's training resolution. Uses samples/ by default, synthetic fallback. Reports timing, peak memory, output diagnostics. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
52 lines
999 B
TOML
52 lines
999 B
TOML
[project]
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name = "corridorkey-mlx"
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version = "0.1.0"
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description = "MLX inference port of CorridorKey for Apple Silicon"
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readme = "README.md"
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requires-python = ">=3.11"
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dependencies = [
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"mlx>=0.31.0",
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"numpy>=2.0.0",
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"pillow>=10.0.0",
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"rich>=13.0.0",
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"safetensors>=0.4.0",
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]
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[dependency-groups]
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dev = [
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"mypy>=1.19.1",
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"pytest>=9.0.2",
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"pytest-xdist>=3.8.0",
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"ruff>=0.15.4",
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]
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reference = [
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"timm>=1.0.25",
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"torch>=2.10.0",
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"torchvision>=0.25.0",
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["src/corridorkey_mlx"]
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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markers = ["slow: heavy tests (2048 inference, etc.) — run with -m slow"]
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addopts = "-m 'not slow'"
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[tool.ruff]
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target-version = "py311"
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line-length = 99
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src = ["src"]
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[tool.ruff.lint]
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select = ["E", "F", "I", "UP", "B", "SIM", "TCH"]
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[tool.mypy]
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python_version = "3.11"
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strict = true
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mypy_path = "src"
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