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Copy file name to clipboardExpand all lines: torchvision/models/quantization/mobilenetv3.py
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@@ -194,18 +194,33 @@ def mobilenet_v3_large(
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**kwargs: Any,
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) ->QuantizableMobileNetV3:
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"""
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Constructs a MobileNetV3 Large architecture from
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`"Searching for MobileNetV3" <https://arxiv.org/abs/1905.02244>`_.
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MobileNetV3 (Large) model from
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`Searching for MobileNetV3 <https://arxiv.org/abs/1905.02244>`_.
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Note that quantize = True returns a quantized model with 8 bit
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weights. Quantized models only support inference and run on CPUs.
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GPU inference is not yet supported
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.. note::
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Note that ``quantize = True`` returns a quantized model with 8 bit
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weights. Quantized models only support inference and run on CPUs.
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GPU inference is not yet supported
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Args:
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weights (MobileNet_V3_Large_QuantizedWeights or MobileNet_V3_Large_Weights, optional): The pretrained
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weights for the model
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progress (bool): If True, displays a progress bar of the download to stderr
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quantize (bool): If True, returns a quantized model, else returns a float model
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weights (:class:`~torchvision.models.quantization.MobileNet_V3_Large_QuantizedWeights` or :class:`~torchvision.models.MobileNet_V3_Large_Weights`, optional): The
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pretrained weights for the model. See
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:class:`~torchvision.models.quantization.MobileNet_V3_Large_QuantizedWeights` below for
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more details, and possible values. By default, no pre-trained
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weights are used.
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progress (bool): If True, displays a progress bar of the
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download to stderr. Default is True.
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quantize (bool): If True, return a quantized version of the model. Default is False.
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**kwargs: parameters passed to the ``torchvision.models.quantization.MobileNet_V3_Large_QuantizedWeights``
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