训练神经网络输入匹配错误时出现错误

Question

尝试建立一个Neuro_net时出现以下错误：

ValueError: Error when checking input: expected dense_6_input to have 2 dimensions, but got array with shape ()

这是我的代码：

print(np.shape(text_tf_train)) # shape=(70000, 73399)
vectorized_training=text_tf_train[0:60000]
y_train_neralnettr =y_train_neralnet[0:60000]
vectorized_validation=text_tf_train[60000:70000]
y_validation_neralnet=y_train_neralnet[60000:70000]




model = Sequential()
model.add(layers.Dense(4500, activation = "relu", input_shape=(73399, )))
# Hidden - Layers
model.add(layers.Dropout(0.3, noise_shape=None, seed=None))
model.add(layers.Dense(1500, activation = "relu"))
model.add(layers.Dropout(0.2, noise_shape=None, seed=None))
model.add(layers.Dense(500, activation = "relu"))
model.add(layers.Dropout(0.2, noise_shape=None, seed=None))
model.add(layers.Dense(50, activation = "relu"))
# Output- Layer
model.add(layers.Dense(20, activation = "sigmoid"))
model.summary()

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


model.fit( np.array(vectorized_training), np.array(y_train_neralnettr),
          batch_size=2000,
          epochs=10,
          verbose=1,
          validation_data=(np.array(vectorized_validation), np.array(y_validation_neralnet)))

我的输入是60000条矢量化消息和20种需要分类的标签。我不明白二维表示什么。它是维度73399的输入。