# Can’t build keras model after Tensorflow update from 2.2 to 2.3

## post by erper14 on Aug 12, 2020

I have been using keras to train some models for the past few months, and everything has been running smoothly. A few days ago, we updated the workstation including a Tensorflow update that brought us from 2.2 to 2.3. Ever since then, I can no longer train my models. It gets to the line where I add a Conv1D layer to my Sequential model before I get the following error message:

```
AttributeError: module ‘tensorflow.python.framework.ops’ has no attribute ‘_TensorLike’
```

I have tried rebooting and changing the keras import statements from keras.models and keras.layers to tensorflow.keras.models and tensorflow.keras.layers, but this just gives me a different error:

```
TypeError: Parameter to MergeFrom() must be instance of same class: expected tensorflow.TensorShapeProto got tensorflow.TensorShapeProto.
```

I’m using a Lambda Quad AI workstation, and it’s running Ubuntu 20.04 with the Lambda software stack. I am also running this remotely using a jupyter notebook inside a virtual environment. Any help is greatly appreciated regarding what caused the sudden break with keras and tensorflow post-update.

## post by ebgoldst on Aug 17, 2020

Same issue, but on a TensorBook (w/ Ubuntu 20.04). Jupyter notebook using TF 2.2 was working as expected. Same notebook using TF 2.3 after Lambda Stack update gives the identical error message as mentioned above:

```
TypeError: Parameter to MergeFrom() must be instance of same class: expected tensorflow.TensorShapeProto got tensorflow.TensorShapeProto.
```

## post by jeremy on Aug 20, 2020

~~As [@ebgoldst](https://deeptalk.lambda.ai/u/ebgoldst) suggested, installing TF 2.2 is the fix here.

Since the TF 2.2 binary distributed by `pip` is linked against `libcudart10.1`, you may also want to install that as well:

`pip3 install tensorflow==2.2.0 && sudo apt -y install libcudart10.1`~~

New workaround:

```sh

pip3 install -U protobuf
```

## post by ebgoldst on Aug 20, 2020

thx [@jeremy](https://deeptalk.lambda.ai/u/jeremy) — downgrading helped w/ the `TypeError` — thank you. However the TF model is still failing to run. The Jupyter notebook error is:

```
UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
```

the terminal message is:

```
tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
```

## post by jeremy on Aug 20, 2020

See the new workaround. Also, try `pip3 uninstall tensorflow` to revert back to the version installed by Lambda Stack.

If the error message doesn’t change, try adding the following after importing tensorflow:

```python

for device in tf.config.experimental.list_physical_devices('GPU'):
    tf.config.experimental.set_memory_growth(device, True)
```

## post by ebgoldst on Aug 20, 2020

Cool. The new workaround (`protobuf`) was successful — `model.fit` now works for TF 2.3.

Thank you!

edit: I did not need `tf.config.experimental.set_memory_growth()` either

## post by mikyla on Jun 10, 2021

We had a similar problem once we updated our Lambda workstation. TensorFlow got updated to version 2.5 and we could no longer run any Tensorflow models. The command

```
pip install -U protobuf
```

fixed the problem though.