输入元素有3行，每行有199列，输出有46行和1列

Input.shape, output.shape((204563, 3, 199), (204563, 46, 1))

当输入时，会抛出以下错误：

from keras.layers import Densefrom keras.models import Sequentialfrom keras.layers.recurrent import SimpleRNNmodel = Sequential()model.add(SimpleRNN(100, input_shape = (Input.shape[1], Input.shape[2])))model.add(Dense(output.shape[1], activation = 'softmax'))model.compile(loss = 'categorical_crossentropy', optimizer = 'adam', metrics = ['accuracy'])model.fit(Input, output, epochs = 20, batch_size = 200)

抛出的错误：

Epoch 1/20---------------------------------------------------------------------------ValueError                                Traceback (most recent call last)<ipython-input-134-378dd431cf45> in <module>()      3 model.add(Dense(y_target.shape[1], activation = 'softmax'))      4 model.compile(loss = 'categorical_crossentropy', optimizer = 'adam', metrics = ['accuracy'])----> 5 model.fit(X_input, y_target, epochs = 20, batch_size = 200)...ValueError: Error when checking model target: expected dense_6 to have 2 dimensions, but got array with shape (204563, 46, 1)

请解释问题的原因和可能的解决方案

回答：

问题在于SimpleRNN(100)返回的张量形状为(204563, 100)，因此，Dense(46)（因为output.shape[1]=46）将返回形状为(204563, 46)的张量，但你的y_target的形状为(204563, 46, 1)。你需要移除最后一个维度，例如使用y_target = np.squeeze(y_target)，以确保维度一致