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