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pixano_inference.frameworks.mlx

MLX framework adapter (Apple Silicon).

Provides framework-neutral device/dtype resolution and numpy interchange for custom models written in MLX. MLX runs on Apple-Silicon GPUs (Metal) and CPU. MLX is imported lazily; importing this module does not require it.

MlxAdapter

:class:~pixano_inference.frameworks.base.FrameworkAdapter for MLX.

from_numpy(array, device=None, dtype=None)

Convert a numpy array to an MLX array. MLX manages device placement implicitly.

Source code in pixano_inference/frameworks/mlx.py 
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def from_numpy(self, array: np.ndarray, device: Any = None, dtype: Any = None) -> Any:
    """Convert a numpy array to an MLX array. MLX manages device placement implicitly."""
    import mlx.core as mx

    result = mx.array(array)
    if dtype is not None:
        result = result.astype(dtype)
    return result

is_available()

Whether mlx is importable.

Source code in pixano_inference/frameworks/mlx.py 
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def is_available(self) -> bool:
    """Whether mlx is importable."""
    return is_mlx_installed()

resolve_device(num_gpus)

Return an MLX device: the Metal GPU when requested and available, else CPU.

Source code in pixano_inference/frameworks/mlx.py 
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def resolve_device(self, num_gpus: float) -> Any:
    """Return an MLX device: the Metal GPU when requested and available, else CPU."""
    import mlx.core as mx

    if num_gpus > 0:
        try:
            if mx.metal.is_available():
                return mx.gpu
        except Exception:
            pass
    return mx.cpu

resolve_dtype(dtype)

Resolve an mlx dtype from a string (e.g. "float32", "bfloat16").

Source code in pixano_inference/frameworks/mlx.py 
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def resolve_dtype(self, dtype: str) -> Any:
    """Resolve an mlx dtype from a string (e.g. ``"float32"``, ``"bfloat16"``)."""
    import mlx.core as mx

    mapping = {
        "float32": mx.float32,
        "float16": mx.float16,
        "bfloat16": mx.bfloat16,
    }
    if dtype not in mapping:
        raise ValueError(f"Unsupported mlx dtype '{dtype}'. Choose from {list(mapping)}.")
    return mapping[dtype]

to_numpy(array)

Convert an MLX array to a numpy array (host memory).

Source code in pixano_inference/frameworks/mlx.py 
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def to_numpy(self, array: Any) -> np.ndarray:
    """Convert an MLX array to a numpy array (host memory)."""
    return np.array(array)