Question

我正在尝试将此模型转换为Keras线性回归器。当前的code：

run_config = tf.estimator.RunConfig(save_checkpoints_steps=500)

def build_model():
  model = keras.Sequential([
    keras.layers.Dense(64, activation=tf.nn.relu,
                       input_shape=(train_data.shape[1],)),
    keras.layers.Dense(64, activation=tf.nn.relu),
    keras.layers.Dense(1)
  ])
  optimizer = tf.train.RMSPropOptimizer(0.001)
  model.compile(loss='mse',
                optimizer=optimizer,
                metrics=['mae'])
  return model

我将其转换为：

  model = models.Sequential()
  model.add(Dense(1, activation='linear', input_shape=(num_features,)))  
  optimizer = keras.optimizers.SGD(lr=learning_rate)
  model.compile(optimizer=optimizer, loss='mse', metrics=['mae'])
  return tf.keras.estimator.model_to_estimator(
      keras_model=model, model_dir=model_dir, config=config)

有一个无限循环显示此内容：

WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.

我的学习率设置为.001 ：（尝试过.01和.1）结果相同。

Tensorflow / Keras LinearRegression警告错误

0 个答案: