我正在遵循sentdex的教程，但是我试图从一个新文件（run_test.py）加载保存的模型，并遇到以下错误。

ValueError: Could not find matching function to call loaded from the SavedModel. 
Got:
 Positional arguments (1 total):
  * Tensor("inputs:0", shape=(None, 28, 28), dtype=uint8)
 Keyword arguments: {}

Expected these arguments to match one of the following 1 option(s):

Option 1:
 Positional arguments (1 total):
  * TensorSpec(shape=(None, 28, 28), dtype=tf.float32, name='inputs')
 Keyword arguments: {}

main.py

import tensorflow as tf
import numpy as np

mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()

model = tf.keras.models.Sequential()
model.add(tf.keras.layers.Flatten())  
model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu)) 
model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu)) 
model.add(tf.keras.layers.Dense(10, activation=tf.nn.softmax))

model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'] ) 
model.fit(x_train, y_train, epochs=1) # run the training process 3 times

val_loss, val_acc = model.evaluate(x_test, y_test)

model.save('num_reader_basic.model')

run_test.py

import tensorflow as tf
import numpy as np

mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()

new_model = tf.keras.models.load_model('num_reader_basic.model')
predictions = new_model.predict(x_test)
print(np.argmax(predictions[0]))

在与模型训练文件（main.py）相同的文件中运行load命令时，不会导致任何错误，仅在从单独的文件运行时才会导致错误。我的第二个文件（run_test.py）中是否有错误，或者从新文件加载保存的模型时是否有其他方法？