AI开发平台MODELARTS-TensorFlow:保存模型（tf接口）

时间：2024-09-05 08:29:59

保存模型（tf接口）

  
   
     
     
       # 导出模型
# 模型需要采用saved_model接口保存
print('Exporting trained model to', export_path)
builder = tf.saved_model.builder.SavedModelBuilder(export_path)

tensor_info_x = tf.saved_model.utils.build_tensor_info(x)
tensor_info_y = tf.saved_model.utils.build_tensor_info(y)

# 定义预测接口的inputs和outputs
# inputs和outputs字典的key值会作为模型输入输出tensor的索引键
# 模型输入输出定义需要和推理自定义脚本相匹配
prediction_signature = (
    tf.saved_model.signature_def_utils.build_signature_def(
        inputs={'images': tensor_info_x},
        outputs={'scores': tensor_info_y},
        method_name=tf.saved_model.signature_constants.PREDICT_METHOD_NAME))

legacy_init_op = tf.group(tf.tables_initializer(), name='legacy_init_op')
builder.add_meta_graph_and_variables(
    # tag设为serve/tf.saved_model.tag_constants.SERVING
    sess, [tf.saved_model.tag_constants.SERVING],
    signature_def_map={
        'predict_images':
            prediction_signature,
    },
    legacy_init_op=legacy_init_op)

builder.save()

print('Done exporting!')

      

    

  
 