vocab_size = 1000
src_txt_length = 500
sum_txt_length = 100
inputs = Input(shape=(src_txt_length,))

encoder1 = Embedding(vocab_size, 128)(inputs)
encoder2 = LSTM(128)(encoder1)
encoder3 = RepeatVector(sum_txt_length)(encoder2)

decoder1 = LSTM(128, return_sequences=True)(encoder3)
outputs = TimeDistributed(Dense(100, activation='softmax'))(decoder1)

model = Model(inputs=inputs, outputs=outputs)
model.compile(loss='categorical_crossentropy', optimizer='adam')

hist = model.fit(x_train, y_train, verbose=1, validation_data=(x_test, y_test), batch_size=batch_size, epochs=5)

ValueError: Error when checking target: expected time_distributed_27 to have 3 dimensions, but got array with shape (28500, 100)