Hello all,
I would like to use the modelAnalysis API for model debugging. I don't have a background in model serving and generating the model eval graph for it - so there might be basic background that I am missing. as a start, I would like to add the tfma to this colab (open to other suggestion that includes transfer learning) Transfer Learning with TensorFlow https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/image_feature_vector.ipynb Could someone direct me, where should the graph eval generation call added? The code below is for estimator model (taken from medium <https://medium.com/tensorflow/introducing-tensorflow-model-analysis-scaleable-sliced-and-full-pass-metrics-5cde7baf0b7b>) and, to my understanding, is not relevant for the colab implementation # use TFMA to export an eval graph from the TensorFlow Estimator tfma.export.export_eval_savedmodel(estimator=estimator, eval_input_receiver_fn=eval_input_fn, …) The colab requires python3 - I will make that the required code adaptation will be applied to match apache beam python 2 requirement. Thanks for any help, -- Eila www.orielresearch.org https://www.meetu <https://www.meetup.com/Deep-Learning-In-Production/>p.co <https://www.meetup.com/Deep-Learning-In-Production/> m/Deep-Learning-In-Production/ <https://www.meetup.com/Deep-Learning-In-Production/>
