Quantized ShuffleNet V2
=======================

.. 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.


Model builders
--------------

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