GoogLeNet¶

class paddle.vision.models. GoogLeNet ( num_classes=1000, with_pool=True ) [source]

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

Parameters

• num_classes (int, optional) – Output dim of last fc layer. If num_classes <= 0, last fc layer will not be defined. Default: 1000.

• with_pool (bool, optional) – Use pool before the last fc layer or not. Default: True.

Returns

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

Examples

import paddle
from paddle.vision.models import GoogLeNet

# build model
model = GoogLeNet()

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]

forward ( inputs )

forward¶

Defines the computation performed at every call. Should be overridden by all subclasses.

Parameters

• *inputs (tuple) – unpacked tuple arguments

• **kwargs (dict) – unpacked dict arguments