以下我下面的代码会生成常规的tensorflow模型,但是当我尝试将其转换为tensorflow lite却无法正常工作时,我遵循了以下文档。
https://www.tensorflow.org/tutorials/estimator/linear 1 https://www.tensorflow.org/lite/guide/get_started
export_dir = "tmp"
serving_input_fn = tf.estimator.export.build_parsing_serving_input_receiver_fn(
tf.feature_column.make_parse_example_spec(feat_cols))
estimator.export_saved_model(export_dir, serving_input_fn)
# Convert the model.
converter = tf.lite.TFLiteConverter.from_saved_model("tmp/1571728920/saved_model.pb")
tflite_model = converter.convert()
错误消息
Traceback (most recent call last):
File "C:/Users/Dacorie Smith/PycharmProjects/JamaicaClassOneNotifableModels/ClassOneModels.py", line 208, in <module>
tflite_model = converter.convert()
File "C:\Users\Dacorie Smith\PycharmProjects\JamaicaClassOneNotifableModels\venv\lib\site-packages\tensorflow_core\lite\python\lite.py", line 400, in convert
raise ValueError("This converter can only convert a single "
ValueError: This converter can only convert a single ConcreteFunction. Converting multiple functions is under development.
从文档中提取
TensorFlow Lite转换器TensorFlow Lite转换器是一个工具 作为Python API提供,可将经过训练的TensorFlow模型转换为 TensorFlow Lite格式。它还可以引入优化, 在第4节“优化模型”中进行了介绍。
以下示例显示了正在转换的TensorFlow SavedModel 转换为TensorFlow Lite格式:
将tensorflow导入为tf
转换器= tf.lite.TFLiteConverter.from_saved_model(saved_model_dir) tflite_model = converter.convert()open(“ converted_model.tflite”, “ wb”)。write(tflite_model)
答案 0 :(得分:3)
尝试使用具体功能:
export_dir = "tmp"
serving_input_fn = tf.estimator.export.build_parsing_serving_input_receiver_fn(
tf.feature_column.make_parse_example_spec(feat_cols))
estimator.export_saved_model(export_dir, serving_input_fn)
# Convert the model.
saved_model_obj = tf.saved_model.load(export_dir="tmp/1571728920/")
concrete_func = saved_model_obj.signatures['serving_default']
converter = tf.lite.TFLiteConverter.from_concrete_functions([concrete_func])
# print(saved_model_obj.signatures.keys())
# converter.optimizations = [tf.lite.Optimize.DEFAULT]
# converter.experimental_new_converter = True
tflite_model = converter.convert()
serving_default
是SavedModels中签名的默认密钥。
如果不起作用,请尝试取消注释converter.experimental_new_converter = True
及其上方的两行。
简短说明
TensorFlow 2中的急切执行将立即评估操作,而无需构建图形。 要保存模型,您需要将图形包装在可调用的python中:一个具体函数。