Method __init__

tinygrad/runtime/ops_webgpu.py:196–221

(self, device:str)

class WebGpuDevice(Compiled):
  def __init__(self, device:str):
    # Requesting an adapter
    adapter_res = _run(webgpu.wgpuInstanceRequestAdapterF, webgpu.WGPURequestAdapterCallbackInfo, webgpu.WGPURequestAdapterCallback,
      webgpu.WGPURequestAdapterStatus, 1, 2, instance, webgpu.WGPURequestAdapterOptions(powerPreference=webgpu.WGPUPowerPreference_HighPerformance,
      backendType=backend_types.get(os.getenv("WEBGPU_BACKEND", ""), 0)))

    # Get supported features
    supported_features = webgpu.WGPUSupportedFeatures()
    webgpu.wgpuAdapterGetFeatures(adapter_res, supported_features)
    supported = [supported_features.features[i] for i in range(supported_features.featureCount)]
    features = [feat for feat in [webgpu.WGPUFeatureName_TimestampQuery, webgpu.WGPUFeatureName_ShaderF16] if feat in supported]
    dev_desc = webgpu.WGPUDeviceDescriptor(requiredFeatureCount=len(features),
                                           requiredFeatures=c.Array(webgpu.WGPUFeatureName, len(features))(*features)) # type: ignore

    # Limits
    supported_limits = webgpu.WGPUSupportedLimits()
    webgpu.wgpuAdapterGetLimits(adapter_res, ctypes.cast(ctypes.pointer(supported_limits),ctypes.POINTER(webgpu.struct_WGPUSupportedLimits)))
    limits = webgpu.WGPURequiredLimits(limits=supported_limits.limits)
    dev_desc.requiredLimits = c.pointer(limits)

    # Requesting a device
    self.device_res = _run(webgpu.wgpuAdapterRequestDeviceF, webgpu.WGPURequestDeviceCallbackInfo, webgpu.WGPURequestDeviceCallback,
      webgpu.WGPURequestDeviceStatus, 1, 2, adapter_res, dev_desc)

    super().__init__(device, WebGpuAllocator(self), [WGSLRenderer],
      functools.partial(WebGPUProgram, (self.device_res, webgpu.WGPUFeatureName_TimestampQuery in supported)))

  def synchronize(self):
    _run(webgpu.wgpuQueueOnSubmittedWorkDone2, webgpu.WGPUQueueWorkDoneCallbackInfo2, webgpu.WGPUQueueWorkDoneCallback2,