resnext101_32x4d

paddle.vision.models. resnext101_32x4d ( pretrained=False, **kwargs ) [源代码]

ResNeXt-101 32x4d 模型,来自论文 "Aggregated Residual Transformations for Deep Neural Networks"

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,ResNeXt-101 32x4d 模型实例。

代码示例

import paddle
from paddle.vision.models import resnext101_32x4d

# build model
model = resnext101_32x4d()

# build model and load imagenet pretrained weight
# model = resnext101_32x4d(pretrained=True)

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

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