How to convert resnet50 network written in eager_execution mode into coreml?
Here is the tf resnet50 implementation: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/contrib/eager/python/examples/resnet50/resnet50.py
How to convert resnet50 network written in eager_execution mode into coreml?
Here is the tf resnet50 implementation: https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/contrib/eager/python/examples/resnet50/resnet50.py
At this point, coremltools and tfcoreml don't handle eager mode. You'll need to convert your TF model to a "frozen" .pb graph file first, and then you can use tfcoreml to convert it to Core ML.
If you can't turn your model into a frozen graph file, you can't use the automated conversion tools... But even in that case, you can still create a Core ML model using NeuralNetworkBuilder (part of coremltools), but you'll have to do all of this by hand.