我为通用句子编码器提供了以下代码,一旦我将模型加载到烧瓶中并尝试将其加载,它就会给出以下错误(检查如下):'''
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
module_url = "https://tfhub.dev/google/universal-sentence-encoder-large/5"
model_2 = hub.load(module_url)
print ("module %s loaded" % module_url)
def embed(input):
return model_2(input)
def universalModel(messages):
accuracy = []
similarity_input_placeholder = tf.placeholder(tf.string, shape=(None))
similarity_message_encodings = embed(similarity_input_placeholder)
with tf.Session() as session:
session.run(tf.global_variables_initializer())
session.run(tf.tables_initializer())
message_embeddings_ = session.run(similarity_message_encodings, feed_dict={similarity_input_placeholder: messages})
corr = np.inner(message_embeddings_, message_embeddings_)
accuracy.append(corr[0,1])
# print(corr[0,1])
return "%.2f" % accuracy[0]
'''
使用烧瓶烧瓶api中的模型时出现以下错误:tensorflow.python.framework.errors_impl.InvalidArgumentError:图形无效,包含一个带有1个节点的循环,包括:StatefulPartitionedCall
尽管此代码可以正常运行,但在colab笔记本中。我正在使用tensorflow版本2.2.0。
我为通用语句编码器提供以下代码,一旦将模型加载到flask api中并尝试点击它,它就会产生以下错误(检查如下:'''import tensorflow.compat.v1 ...import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()