- paddle.vision.models. googlenet ( pretrained=False, **kwargs )
GoogLeNet (Inception v1) model architecture from “Going Deeper with Convolutions”.
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 GoogLeNet.
Layer. An instance of GoogLeNet (Inception v1) model.
import paddle from paddle.vision.models import googlenet # build model model = googlenet() # build model and load imagenet pretrained weight # model = googlenet(pretrained=True) x = paddle.rand([1, 3, 224, 224]) out, out1, out2 = model(x) print(out.shape, out1.shape, out2.shape) # [1, 1000] [1, 1000] [1, 1000]