resnet101

paddle.vision.models. resnet101 ( pretrained=False, **kwargs ) [源代码]

101 层的 ResNet 模型,来自论文 "Deep Residual Learning for Image Recognition"

参数

  • pretrained (bool,可选) - 是否加载预训练权重。如果为 True,则返回在 ImageNet 上预训练的模型。默认值为 False。

  • **kwargs (可选) - 附加的关键字参数,具体可选参数请参见 ResNet

返回

Layer,101 层的 ResNet 模型实例。

代码示例

>>> import paddle
>>> from paddle.vision.models import resnet101

>>> # build model
>>> model = resnet101()

>>> # build model and load imagenet pretrained weight
>>> # model = resnet101(pretrained=True)

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

>>> print(out.shape)
[1, 1000]