resnext101_32x4d¶
- paddle.vision.models. resnext101_32x4d ( pretrained=False, **kwargs ) [source]
-
ResNeXt-101 32x4d model from “Aggregated Residual Transformations for Deep Neural Networks”
- Parameters
-
pretrained (bool, optional) – If True, returns a model pre-trained on ImageNet. Default: False.
Examples
import paddle from paddle.vision.models import resnext101_32x4d # build model model = resnext101_32x4d() # build model and load imagenet pretrained weight # model = resnext101_32x4d(pretrained=True) x = paddle.rand([1, 3, 224, 224]) out = model(x) print(out.shape) # [1, 1000]