docs/source/models/shufflenetv2_quant.rst
.. currentmodule:: torchvision.models.quantization
The Quantized ShuffleNet V2 model is based on the ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design <https://arxiv.org/abs/1807.11164>__ paper.
The following model builders can be used to instantiate a quantized ShuffleNetV2
model, with or without pre-trained weights. All the model builders internally rely
on the torchvision.models.quantization.shufflenetv2.QuantizableShuffleNetV2
base class. Please refer to the source code <https://github.com/pytorch/vision/blob/main/torchvision/models/quantization/shufflenetv2.py>_
for more details about this class.
.. autosummary:: :toctree: generated/ :template: function.rst
shufflenet_v2_x0_5
shufflenet_v2_x1_0
shufflenet_v2_x1_5
shufflenet_v2_x2_0