Davide Boschetto

same error for me. tensorflow.python.framework.errors_impl.InvalidArgumentError: Incompatible shapes: [80,1] vs. [160,1] [[Node: prediction/logistic_loss/mul = Mul[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](prediction/Squeeze, prediction/ToFloat)]]

Do we still need to freeze the model to load it in c++?

I think reopening the issue might be the right choice! ONNX provided this converter, in the meantime: https://github.com/onnx/tensorflow-onnx It only works with saved_model or .meta, though (usual drawbacks of freezing...

It would be great to have an update: are things still planned for a Keras2.0 upgrade?

This is great @sandeep-krishnamurthy ! Keep up the good work, having the backend in keras2 would be amazing, thanks! Do you by any chance have a ballpark estimation for when...