使用Keras版本2.1.0时，出现密集层形状错误。仅此版本的Keras（2.1.0）会发生此问题。由于该版本位于群集中，因此我无法升级该版本，因此我暂时尝试查找修复程序。我的模型定义如下。
model = Sequential()
model.add(Conv2D(32, kernel_size=(3, 3),
activation='relu',
input_shape=(32, 32, 3)))
model.add(Conv2D(64, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(10, activation='softmax'))
model.compile(loss='categorical_crossentropy',
optimizer=config["optimizer"],
metrics=['accuracy'])
我已经完成了一种热编码，如下所示。
y_train = keras.utils.to_categorical(y_train, 10)
y_test = keras.utils.to_categorical(y_test, 10)
模型摘要是
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 30, 30, 32) 896
_________________________________________________________________
conv2d_2 (Conv2D) (None, 28, 28, 64) 18496
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 14, 14, 64) 0
_________________________________________________________________
dropout_1 (Dropout) (None, 14, 14, 64) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 12544) 0
_________________________________________________________________
dense_1 (Dense) (None, 128) 1605760
_________________________________________________________________
dropout_2 (Dropout) (None, 128) 0
_________________________________________________________________
dense_2 (Dense) (None, 10) 1290
=================================================================
Total params: 1,626,442
Trainable params: 1,626,442
Non-trainable params: 0
_____________________________________
我得到的错误是：
ValueError：检查目标时出错：预期density_2具有2 尺寸，但数组的形状为（50000，1，10）
完全相同的代码可在Keras 2.2.4中完美地工作