AlexNet做猫狗分类时报错 has no attribute 'Pool2D'
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import paddle
import paddle.nn.functional
#组网
class AlexNet(paddle.nn.Layer):
def __init__(self, class_dim):
super(AlexNet, self).__init__()
self.conv1 = paddle.nn.Conv2D(3,96,11,stride=4,padding=2)
self.pool1 = paddle.nn.layer.Pool2D(pool_size=3,pool_type='max', pool_stride=2, pool_padding=0)
self.conv2 = paddle.nn.Conv2D(96,256,5,stride=1,padding=2)
self.pool2 = paddle.nn.layer.Pool2D(pool_size=3,pool_type='max', pool_stride=2, pool_padding=0)
self.conv3 = paddle.nn.Conv2D(256,384,3,stride=1,padding=1)
self.conv4 = paddle.nn.Conv2D(384,384,3,stride=1,padding=1)
self.conv5 = paddle.nn.Conv2D(384,256,3,stride=1,padding=1)
self.pool3 = paddle.nn.layer.Pool2D(pool_size=3,pool_type='max', pool_stride=2, pool_padding=0)
self.fc1 = paddle.nn.Linear(9216, 4096)
self.fc2 = paddle.nn.Linear(4096, 4096)
self.fc3 = paddle.nn.Linear(4096, class_dim)
self.relu = paddle.nn.ReLU()
self.softmax = paddle.nn.Softmax()
def forward(self, x):
x = self.conv1(x)
x = self.relu(x)
x = self.pool1(x)
x = self.conv2(x)
x = self.relu(x)
x = self.pool2(x)
x = self.conv3(x)
x = self.relu(x)
x = self.conv4(x)
x = self.relu(x)
x = self.conv5(x)
x = self.relu(x)
x = self.pool3(x)
x = paddle.flatten(x, start_axis= 1, stop_axis= 3)
x = self.fc1(x)
x = self.relu(x)
x = self.fc2(x)
x = self.relu(x)
x = self.fc3(x)
x = self.softmax(x)
return x
class_dim=train_parameters['class_dim']
model = paddle.Model(AlexNet(class_dim=class_dim))
model.summary((None,3, 224, 224))
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2.0版本后不用Pool2D这个api了，现在用的是这两个
https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/nn/AvgPool2D_cn.html
https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/nn/MaxPool2D_cn.html
平均池化和最大池化分成两个api了
确实没有这个Pool2D层呀，只有MaxPool2D和AvgPool2D，可以去看一下API文档，链接：https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/nn/Overview_cn.html
这里面有所有内置的子层。