sglang_v0.5.2/vision_0.22.1/docs/source/models/shufflenetv2_quant.rst

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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