shufflenet_v2_x2_0 shufflenet_v2_x2_0 ( pretrained=False, **kwargs ) [source]

ShuffleNetV2 with 2.0x output channels, as described in “ShuffleNet V2: Practical Guidelines for Ecient CNN Architecture Design”.

  • 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 ShuffleNetV2.


Layer. An instance of ShuffleNetV2 with 2.0x output channels.


import paddle
from import shufflenet_v2_x2_0

# build model
model = shufflenet_v2_x2_0()

# build model and load imagenet pretrained weight
# model = shufflenet_v2_x2_0(pretrained=True)

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

# [1, 1000]