SqueezeNet¶

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

SqueezeNet model from “SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size”.

Parameters

• version (str) – Version of SqueezeNet, which can be “1.0” or “1.1”.

• 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 SqueezeNet model.

Examples

import paddle
from paddle.vision.models import SqueezeNet

# build v1.0 model
model = SqueezeNet(version='1.0')

# build v1.1 model
# model = SqueezeNet(version='1.1')

x = paddle.rand([1, 3, 224, 224])
out = model(x)

print(out.shape)
# [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