shufflenet_v2_x1_0¶
- paddle.vision.models. shufflenet_v2_x1_0 ( pretrained=False, **kwargs ) [source]
-
ShuffleNetV2 with 1.0x output channels, as described in “ShuffleNet V2: Practical Guidelines for Ecient CNN Architecture Design” 。
- Parameters
-
pretrained (bool) – If True, returns a model pre-trained on ImageNet. Default: False.
Examples
import paddle from paddle.vision.models import shufflenet_v2_x1_0 # build model model = shufflenet_v2_x1_0() # build model and load imagenet pretrained weight # model = shufflenet_v2_x1_0(pretrained=True) x = paddle.rand([1, 3, 224, 224]) out = model(x) print(out.shape)