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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
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