Tensorflow:可用的**kwargs列表

import tensorflow as tf

def build_model(input_shape, output_units, **kwargs):
    model = tf.keras.models.Sequential()
    model.add(tf.keras.layers.Dense(units=64, activation='relu', input_shape=input_shape))
    model.add(tf.keras.layers.Dense(units=output_units, activation='softmax'))
    
    # 使用**kwargs传递额外的配置参数
    if 'learning_rate' in kwargs:
        optimizer = tf.keras.optimizers.Adam(learning_rate=kwargs['learning_rate'])
    else:
        optimizer = tf.keras.optimizers.Adam()
    
    model.compile(optimizer=optimizer, loss='categorical_crossentropy', metrics=['accuracy'])
    
    return model

# 构建模型并传递额外的配置参数
model = build_model(input_shape=(784,), output_units=10, learning_rate=0.001)