tensorflow - 如何在 tensorflow 中将 TextVectorization 保存到磁盘？

Question

from tensorflow.keras.layers.experimental.preprocessing import TextVectorization 

text_dataset = tf.data.Dataset.from_tensor_slices(text_clean) 
    
vectorizer = TextVectorization(max_tokens=100000, output_mode='tf-idf',ngrams=None)
    
vectorizer.adapt(text_dataset.batch(1024))

我已经训练了一个 TextVectorization 并且我想将它保存到磁盘，以便我下次可以重新加载它？我试过 pickle 和joblib.dump。这是行不通的。
我怎样才能保存它？
生成的错误如下:

InvalidArgumentError: Cannot convert a Tensor of dtype resource to a NumPy array

Answer 1

不是 pickle 对象，而是 pickle 配置和权重。稍后解开它并使用配置来创建对象并加载保存的权重。办公文档 here .
代码

text_dataset = tf.data.Dataset.from_tensor_slices([
                                                   "this is some clean text", 
                                                   "some more text", 
                                                   "even some more text"]) 
# Fit a TextVectorization layer
vectorizer = TextVectorization(max_tokens=10, output_mode='tf-idf',ngrams=None)    
vectorizer.adapt(text_dataset.batch(1024))

# Vector for word "this"
print (vectorizer("this"))

# Pickle the config and weights
pickle.dump({'config': vectorizer.get_config(),
             'weights': vectorizer.get_weights()}
            , open("tv_layer.pkl", "wb"))

print ("*"*10)
# Later you can unpickle and use 
# `config` to create object and 
# `weights` to load the trained weights. 

from_disk = pickle.load(open("tv_layer.pkl", "rb"))
new_v = TextVectorization.from_config(from_disk['config'])
# You have to call `adapt` with some dummy data (BUG in Keras)
new_v.adapt(tf.data.Dataset.from_tensor_slices(["xyz"]))
new_v.set_weights(from_disk['weights'])

# Lets see the Vector for word "this"
print (new_v("this"))

输出:

tf.Tensor(
[[0.         0.         0.         0.         0.91629076 0.
  0.         0.         0.         0.        ]], shape=(1, 10), dtype=float32)
**********
tf.Tensor(
[[0.         0.         0.         0.         0.91629076 0.
  0.         0.         0.         0.        ]], shape=(1, 10), dtype=float32)