squeezenet1_1¶

paddle.vision.models. squeezenet1_1 ( pretrained: bool = False, **kwargs: Unpack[_SqueezeNetOptions] ) → SqueezeNet [source]

SqueezeNet v1.1 model from “SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size”.

Parameters

• pretrained (bool, optional) – Whether to load pre-trained weights. If True, returns a model pre-trained on ImageNet. Default: False.

• **kwargs (optional) – Additional keyword arguments. For details, please refer to SqueezeNet.

Returns

Layer. An instance of SqueezeNet v1.1 model.

Examples

>>> import paddle
>>> from paddle.vision.models import squeezenet1_1

>>> # build model
>>> model = squeezenet1_1()

>>> # build model and load imagenet pretrained weight
>>> # model = squeezenet1_1(pretrained=True)

>>> x = paddle.rand([1, 3, 224, 224])
>>> out = model(x)

>>> print(out.shape)
[1, 1000]