如何解决使用保存的模型导出Tensorflow实验模型
请我如何使用TensorFlow SaveModel保存该模型。
train_steps = int(0.5 + (1.0 * num_epochs * nusers) / batch_size)
steps_in_epoch = int(0.5 + nusers / batch_size)
print("Will train for {} steps,evaluating once every {} steps".format(train_steps,steps_in_epoch))
def experiment_fn(output_dir):
return tf.contrib.learn.Experiment(
tf.contrib.factorization.WALSMatrixFactorization(
num_rows = nusers,num_cols = nitems,embedding_dimension = n_embeds,model_dir = output_dir),train_input_fn = read_dataset(tf.estimator.ModeKeys.TRAIN,input_path,batch_size,nitems,nusers,num_epochs,n_embeds,output_dir),eval_input_fn = read_dataset(tf.estimator.ModeKeys.EVAL,train_steps = train_steps,eval_steps = 1,min_eval_frequency = steps_in_epoch,export_strategies = tf.contrib.learn.utils.saved_model_export_utils.make_export_strategy(serving_input_fn = create_serving_input_fn(nitems,nusers))
)
我尝试用 export_strategies=tf.export_saved_model(output_dir,serving_input_fn = create_serving_input_fn(nitems,nusers))
替换export_strategies,它返回以下错误消息
AttributeError: module 'tensorflow' has no attribute 'export_saved_model
还尝试了export_strategies=tf.saved_model(output_dir,nusers))
TypeError: 'DeprecationWrapper' object is not callable
版权声明:本文内容由互联网用户自发贡献,该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容, 请发送邮件至 dio@foxmail.com 举报,一经查实,本站将立刻删除。