wide_resnet101_2¶
- paddle.vision.models. wide_resnet101_2 ( pretrained=False, **kwargs ) [source]
-
Wide ResNet-101-2 model from “Wide Residual Networks”.
- 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 ResNet.
- Returns
-
Layer. An instance of Wide ResNet-101-2 model.
Examples
import paddle from paddle.vision.models import wide_resnet101_2 # build model model = wide_resnet101_2() # build model and load imagenet pretrained weight # model = wide_resnet101_2(pretrained=True) x = paddle.rand([1, 3, 224, 224]) out = model(x) print(out.shape) # [1, 1000]