resnext101_32x8d

torchvision.models.quantization.resnext101_32x8d(*, weights: Optional[Union[ResNeXt101_32X8D_QuantizedWeights, ResNeXt101_32X8D_Weights]] = None, progress: bool = True, quantize: bool = False, **kwargs: Any) → QuantizableResNet

ResNeXt-101 32x8d model from Aggregated Residual Transformation for Deep Neural Networks

Note

Note that quantize = True returns a quantized model with 8 bit weights. Quantized models only support inference and run on CPUs. GPU inference is not yet supported.

Parameters:

• weights (ResNeXt101_32X8D_QuantizedWeights or ResNeXt101_32X8D_Weights, optional) – The pretrained weights for the model. See ResNet101_32X8D_QuantizedWeights below for more details, and possible values. By default, no pre-trained weights are used.

• progress (bool, optional) – If True, displays a progress bar of the download to stderr. Default is True.

• quantize (bool, optional) – If True, return a quantized version of the model. Default is False.

• **kwargs – parameters passed to the torchvision.models.quantization.QuantizableResNet base class. Please refer to the source code for more details about this class.

class torchvision.models.quantization.ResNeXt101_32X8D_QuantizedWeights(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

class torchvision.models.ResNeXt101_32X8D_Weights(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)