Error when checking target: expected dense_2 to have shape (9,) but got array with shape (30,)

Question

I am having an issue when trying to train my model in Keras 2.0.8, Python 3.6.1, and a Tensorflow Backend.

Error Message: Error when checking target: expected dense_2 to have shape (9,) but got array with shape (30,) I am providing the shape of the input as well.

train_x.shape: (623, 30, 30, 1)
train_y.shape: (623, 30)
val_x.shape: (156, 30, 30, 1)
val_y.shape: (156, 30)


#building model
model = Sequential()
model.add(Conv2D(20, (5, 5), padding="same", input_shape=(30, 30, 1), activation="relu"))
model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))
model.add(Conv2D(50, (5, 5), padding="same", activation="relu"))
model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))
model.add(Flatten())
model.add(Dense(128, activation="relu"))
model.add(Dropout(0.3))
model.add(Dense(9, activation="softmax"))

model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])


estop = EarlyStopping(patience=10, mode='min', min_delta=0.001, monitor='val_loss')

model.fit(train_x, train_y, validation_data=(val_x, val_y), batch_size=32, epochs=50, verbose=1, callbacks = [estop])

Answer 1

Change the line of code:

model.add(Dense(9, activation="softmax"))

to the below line:

model.add(Dense(30, activation="softmax"))

so that the output dimension of the last (Dense) layer is (None, 30) instead of dimension (None, 9).