Created by: chenlizhi-1013

class Encoder(nn.Module): """ Encoder. """

def __init__(self, encoded_image_size=14):
    super(Encoder, self).__init__()
    self.enc_image_size = encoded_image_size

    resnet = torchvision.models.resnet101(pretrained=True)  # pretrained ImageNet ResNet-101

    # Remove linear and pool layers (since we're not doing classification)
    modules = list(resnet.children())[:-2]
    self.resnet = nn.Sequential(*modules)

    # Resize image to fixed size to allow input images of variable size
    self.adaptive_pool = nn.AdaptiveAvgPool2d((encoded_image_size, encoded_image_size))

上面是用pytorch调用的模型，对模型进行更改，把最后两层去掉。老师，我现在想把这段代码用paddle框架实现，该如何写呢，我找不到方向。对于paddle的预训练模型，能不能访问每一层呢，请老师们帮忙解答一下。