英文:
Value Error: Shapes (None, 21) and (None, 7, 7, 21) are incompatible
问题
抱歉，以下是您要的代码部分的翻译：
# 冻结预训练模型层的权重
for layer in base_model.layers:
layer.trainable = False
# 用3个新层替换最后的3个全连接层
x = base_model.output
x = Dense(50, activation='relu')(x)
x = Dense(20, activation='relu')(x)
x = Dense(num_classes, activation='softmax')(x)
# 通过将VGG16的基本部分与新层连接来创建一个新模型
model = Model(inputs=base_model.input, outputs=x)
希望这有所帮助。如果您有更多问题，请随时提问。
英文:
Hello I am new to using keras. and I am doing an exercise with the VGG16 model.
I have loaded the model and now I have to Replace the last 3 fully connected layers with 3 new layers: the first 2 of 50 and 20 neurons respectively with ReLU activation, and a last layer with the appropriate number of neurons.
I have done the following:
enter code here
# Freeze the weights of the pretrained model layers
for layer in base_model.layers:
layer.trainable = False
# Replace the last 3 fully connected layers with 3 new layers
x = base_model.output
x = Dense(50, activation='relu')(x)
x = Dense(20, activation='relu')(x)
x = Dense(num_classes, activation='softmax')(x)
# Create a new model by joining the base of VGG16 with the new layers
model = Model(inputs=base_model.input, outputs=x)
the model.summary() is like this:
=================================================================
input_13 (InputLayer) [(None, 224, 224, 3)] 0
block1_conv1 (Conv2D) (None, 224, 224, 64) 1792
block1_conv2 (Conv2D) (None, 224, 224, 64) 36928
block1_pool (MaxPooling2D) (None, 112, 112, 64) 0
block2_conv1 (Conv2D) (None, 112, 112, 128) 73856
block2_conv2 (Conv2D) (None, 112, 112, 128) 147584
block2_pool (MaxPooling2D) (None, 56, 56, 128) 0
block3_conv1 (Conv2D) (None, 56, 56, 256) 295168
block3_conv2 (Conv2D) (None, 56, 56, 256) 590080
block3_conv3 (Conv2D) (None, 56, 56, 256) 590080
block3_pool (MaxPooling2D) (None, 28, 28, 256) 0
block4_conv1 (Conv2D) (None, 28, 28, 512) 1180160
block4_conv2 (Conv2D) (None, 28, 28, 512) 2359808
block4_conv3 (Conv2D) (None, 28, 28, 512) 2359808
block4_pool (MaxPooling2D) (None, 14, 14, 512) 0
block5_conv1 (Conv2D) (None, 14, 14, 512) 2359808
block5_conv2 (Conv2D) (None, 14, 14, 512) 2359808
block5_conv3 (Conv2D) (None, 14, 14, 512) 2359808
block5_pool (MaxPooling2D) (None, 7, 7, 512) 0
dense_6 (Dense) (None, 7, 7, 50) 25650
dense_7 (Dense) (None, 7, 7, 20) 1020
dense_8 (Dense) (None, 7, 7, 21) 441
=================================================================
Total params: 14,741,799
Trainable params: 27,111
Non-trainable params: 14,714,688
When I try to train the model it gives me the following error:
"ValueError: Shapes (None, 21) and (None, 7, 7, 21) are incompatible"
What could be the problem?
Thanks!
答案1
得分: 1
# 摊平输出层：
x = base_model.output
x = Flatten(name="flatten")(x)
x = Dense(50, activation='relu')(x)
x = Dense(20, activation='relu')(x)
x = Dense(num_classes, activation='softmax')(x)
英文:
Flatten the output layer:
x = base_model.output
x = Flatten(name="flatten")(x)
x = Dense(50, activation='relu')(x)
x = Dense(20, activation='relu')(x)
x = Dense(num_classes, activation='softmax')(x)
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