wehub-resource-sync
89 lines
2.5 KiB
Python
89 lines
2.5 KiB
Python
"""
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Platform detection for backend selection.
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"""
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import platform
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import subprocess
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from functools import lru_cache
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from typing import Literal
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def is_apple_silicon() -> bool:
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"""
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Check if running on Apple Silicon (arm64 macOS).
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Returns:
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True if on Apple Silicon, False otherwise
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"""
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return platform.system() == "Darwin" and platform.machine() == "arm64"
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@lru_cache(maxsize=1)
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def is_amd_gpu_windows() -> bool:
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"""
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Check if the primary GPU on Windows is an AMD Radeon card.
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Uses WMI to query Win32_VideoController, with a fallback to
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torch.cuda.get_device_name(0) if WMI is unavailable. This is
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useful for deciding whether the ROCm backend is appropriate.
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Result is cached since it shells out to PowerShell and the GPU
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does not change at runtime — safe to call from the health path.
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Returns:
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True if an AMD GPU is detected on Windows, False otherwise.
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"""
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if platform.system() != "Windows":
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return False
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# Primary method: WMI query for AMD adapters
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try:
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result = subprocess.run(
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[
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"powershell",
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"-Command",
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"Get-CimInstance Win32_VideoController | "
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"Where-Object {$_.AdapterCompatibility -like '*AMD*'} | "
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"Measure-Object | Select-Object -ExpandProperty Count",
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],
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capture_output=True,
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text=True,
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check=True,
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)
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if int(result.stdout.strip()) > 0:
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return True
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except Exception:
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pass
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# Fallback: torch.cuda.get_device_name(0) (works for ROCm/HIP too)
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try:
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import torch
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if torch.cuda.is_available():
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name = torch.cuda.get_device_name(0)
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if "Radeon" in name or "AMD" in name:
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return True
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except Exception:
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pass
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return False
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def get_backend_type() -> Literal["mlx", "pytorch"]:
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"""
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Detect the best backend for the current platform.
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Returns:
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"mlx" on Apple Silicon (if MLX is available and functional), "pytorch" otherwise
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"""
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if is_apple_silicon():
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try:
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import mlx.core # noqa: F401 — triggers native lib loading
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return "mlx"
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except (ImportError, OSError, RuntimeError):
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# MLX not installed, or native libraries failed to load inside a
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# PyInstaller bundle (OSError on missing .dylib / .metallib).
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# Fall through to PyTorch.
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return "pytorch"
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return "pytorch"
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