shufflenet_v2_swish shufflenet_v2_swish ( pretrained=False, **kwargs ) [source]

ShuffleNetV2 with 1.0x output channels and swish activation function, as described in “ShuffleNet V2: Practical Guidelines for Ecient CNN Architecture Design”


pretrained (bool) – If True, returns a model pre-trained on ImageNet. Default: False.


import paddle
from import shufflenet_v2_swish

# build model
model = shufflenet_v2_swish()

# build model and load imagenet pretrained weight
# model = shufflenet_v2_swish(pretrained=True)

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