Error when using LSTM

Hello everybody, I’ve run into an error using tensorflow-gpu version 2.7.0. and I am looking for help. Whenever I try to use tensorflow.keras.layers LSTM the kernel of my Jupiter Notebook dies when trying to run model.fit(). I can compile the model and the cell gets executed without an error. I’ve gotten an error message only once and it said:

NotImplementedError: Cannot convert a symbolic Tensor (lstm/strided_slice:0) to a bumpy array. This error may indicate that you’re trying to pass a Tensor to a Num Py call, which is not supported

I’ve only ever gotten this error message once and never again since. I looked it up online and people said it was a compatibility issue with numpy > 1.19.5 so I downgraded numpy but my kernel still dies when trying to do model.fit(). I then tried to pass my training data as a tf tensor by converting the numpy array using tf.convert_to_tensor(). But that didn’t help either. Everything else using tf seems to work, it’s just LSTM giving me issues.

Has anyone an idea how I could fix the issue? Thank you.

Version in use: tensorflow-gpu 2.7.0, Num Py 1.20.3/1.19.5, Cuda 11.3.1 and cudnn 8.1.0.77; GPU: RTX 3090