tf2onnx' has no attribute 'save_model'
时间: 2023-10-04 07:04:20 浏览: 52
This error message suggests that the 'save_model' function is not defined in the 'tf2onnx' module. This could be due to a version mismatch or a missing package.
To resolve this issue, you can try updating the 'tf2onnx' module to the latest version using the following command:
```
pip install --upgrade tf2onnx
```
If the issue persists, you can try importing the 'save_model' function from the 'tf2onnx.tools' module instead of the 'tf2onnx' module:
```
from tf2onnx.tools import save_model
```
Then, you can use the 'save_model' function to save the converted model in the ONNX format.
相关问题
AttributeError: 'Model' object has no attribute 'save_models'
AttributeError: 'Model' object has no attribute 'save_models'的意思是在调用Model对象的save_models方法时,没有找到该方法,导致了错误。
这通常是因为该Model对象并没有实现该方法,或者该方法名称拼写错误。请确保您使用的模型对象有save_models方法,并且正确拼写方法名。
如果您想要将模型保存到文件中,可以使用pickle模块或者Tensorflow自带的保存模型的方法。以下是一些可能有用的代码片段:
使用pickle模块保存模型:
```
import pickle
model = Model()
# 训练模型...
with open('model.pickle', 'wb') as f:
pickle.dump(model, f)
```
使用Tensorflow保存模型:
```
import tensorflow as tf
model = Model()
# 训练模型...
tf.saved_model.save(model, 'saved_model')
```
Traceback (most recent call last): File "D:\23101\yolov5-master\jjjjjj.py", line 2, in <module> converter = tf.lite.TFLiteConverter.from_onnx('best.onnx') AttributeError: type object 'TFLiteConverterV2' has no attribute 'from_onnx'
这错误提示是因为 TensorFlow 2.x 中的 `TFLiteConverter` 已经更新了 API,不再支持 `from_onnx` 方法。
你可以尝试使用如下代码来转换 ONNX 模型为 TensorFlow Lite 模型:
```python
import tensorflow as tf
# Load the ONNX model
onnx_model = onnx.load('best.onnx')
# Convert the ONNX model to a TensorFlow model
tf_model = onnx_tf.backend.prepare(onnx_model)
# Convert the TensorFlow model to a TensorFlow Lite model
converter = tf.lite.TFLiteConverter.from_keras_model(tf_model)
tflite_model = converter.convert()
# Save the TensorFlow Lite model to a file
with open('best.tflite', 'wb') as f:
f.write(tflite_model)
```
请确保你已经安装了 `onnx` 和 `onnx-tf` 包。如果还有问题,请提供完整的错误信息以便更好地帮助你。
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