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