shufflenet_v2_x1_5¶

torchvision.models.shufflenet_v2_x1_5(*, weights: Optional[ShuffleNet_V2_X1_5_Weights] = None, progress: bool = True, **kwargs: Any) → ShuffleNetV2[source]¶

Constructs a ShuffleNetV2 architecture with 1.5x output channels, as described in ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design.

Parameters:

weights (ShuffleNet_V2_X1_5_Weights, optional) – The pretrained weights to use. See ShuffleNet_V2_X1_5_Weights 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.
**kwargs – parameters passed to the torchvision.models.shufflenetv2.ShuffleNetV2 base class. Please refer to the source code for more details about this class.

class torchvision.models.ShuffleNet_V2_X1_5_Weights(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶

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