我用以下代码构建了一个模型：
model_input = Input(shape=(449, 8, 1))
x = Conv2D(64, (25, 20),padding='same', input_shape=( 449, 8, 1),activation="relu")(model_input)
x = BatchNormalization()(x)
x = Conv2D(128, (25, 20),padding='same', input_shape=( 449, 8, 1),activation="relu")(x)
x = BatchNormalization()(x)
x = Flatten()(x)
x = Dense(8, activation='relu')(x)
x = BatchNormalization()(x)
x = Dense(8, activation='softmax')(x)
model = Model(input=model_input ,output=x)
在导入以下Keras库时，它可以完美运行：
from keras.layers import Conv2D, Input, BatchNormalization, Flatten, Dense
from keras.models import Model
from keras.optimizers import Adam
但是当我尝试在tensorflow中使用内置的Keras API并构建相同的模型时：
from tensorflow.keras.layers import Conv2D, Input, BatchNormalization, Flatten, Dense
from tensorflow.keras.models import Model
from tensorflow.keras.optimizers import Adam
错误已合并：
TypeError：_init_subclassed_network（）获得了意外的关键字参数“输入”
我正在使用tensorflow-gpu 1.13.1。