I am using ssd_keras with tensorflow 1.15 backend (I was originally using tensorflow 2.20 but ran into this issue) and it throws an InvalidArgumentError the moment I start the training. It's very deep in the tensorflow backend and almost impossible to trace.
Full stack trace
As soon as I call model.fit(...) in the ssd300_training.ipynb tutorial, I get the following very long message:
keras: using tf.keras through tensorflow-gpu. I have converted to tf.keras in a standard way.
Which commit: latest
GPU: NVIDIA Corporation TU104GL [Quadro RTX 5000] (the error happens whether I am running on gpu or cpu)
Reproducible example
The error happens whenever I call model.fit(...) or model.fit_generator(...), where model is an ssd300 model, and where the backend is tf1. It happens whether I am using cpu or gpu. E.g. when I run the ssd300_training.ipynb tutorial, I get that error.
Sorry to open two issues at once. I've been trying to work through both of these for awhile but have found no solutions.
I am using ssd_keras with tensorflow 1.15 backend (I was originally using tensorflow 2.20 but ran into this issue) and it throws an InvalidArgumentError the moment I start the training. It's very deep in the tensorflow backend and almost impossible to trace.
Full stack trace
As soon as I call
model.fit(...)
in the ssd300_training.ipynb tutorial, I get the following very long message:System info
Reproducible example
The error happens whenever I call
model.fit(...)
ormodel.fit_generator(...)
, where model is an ssd300 model, and where the backend is tf1. It happens whether I am using cpu or gpu. E.g. when I run the ssd300_training.ipynb tutorial, I get that error.Sorry to open two issues at once. I've been trying to work through both of these for awhile but have found no solutions.