googlenet¶

paddle.vision.models. googlenet ( pretrained=False, **kwargs ) [source]

GoogLeNet (Inception v1) model architecture from “Going Deeper with Convolutions”.

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 GoogLeNet.

Returns

Layer. An instance of GoogLeNet (Inception v1) model.

Examples

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]