3 Commits

Author	SHA1	Message	Date
Michelle Casbon	70a22d6d7b	[GH Issue Summarization] Upgrade to kf v0.4.0-rc.2 (#450) ... * Update tfjob components to v1beta1 Remove old version of tensor2tensor component * Combine UI into a single jsonnet file * Upgrade GH issue summarization to kf v0.4.0-rc.2 Use latest ksonnet v0.13.1 Use latest seldon v1alpha2 Remove ksonnet app with full kubeflow platform & replace with components specific to this example. Remove outdated scripts Add cluster creation links to Click-to-deploy & kfctl Add warning not to use the Training with an Estimator guide Replace commandline with bash for better syntax highlighting Replace messy port-forwarding commands with svc/ambassador Add modelUrl param to ui component Modify teardown instructions to remove the deployment Fix grammatical mistakes * Rearrange tfjob instructions	2018-12-30 20:05:29 -08:00
Jeremy Lewi	1043bc0c26	A bunch of changes to support distributed training using tf.estimator (#265) ... * Unify the code for training with Keras and TF.Estimator Create a single train.py and trainer.py which uses Keras inside TensorFlow Provide options to either train with Keras or TF.TensorFlow The code to train with TF.estimator doesn't worki See #196 The original PR (#203) worked around a blocking issue with Keras and TF.Estimator by commenting certain layers in the model architecture leading to a model that wouldn't generate meaningful predictions We weren't able to get TF.Estimator working but this PR should make it easier to troubleshoot further We've unified the existing code so that we don't duplicate the code just to train with TF.estimator We've added unitttests that can be used to verify training with TF.estimator works. This test can also be used to reproduce the current errors with TF.estimator. Add a Makefile to build the Docker image Add a NFS PVC to our Kubeflow demo deployment. Create a tfjob-estimator component in our ksonnet component. changes to distributed/train.py as part of merging with notebooks/train.py * Add command line arguments to specify paths rather than hard coding them. * Remove the code at the start of train.py to wait until the input data becomes available. * I think the original intent was to allow the TFJob to be started simultaneously with the preprocessing job and just block until the data is available * That should be unnecessary since we can just run the preprocessing job as a separate job. Fix notebooks/train.py (#186) The code wasn't actually calling Model Fit Add a unittest to verify we can invoke fit and evaluate without throwing exceptions. * Address comments.	2018-11-07 16:23:59 -08:00
Michał Jastrzębski	35786ed9cb	Add estimator example for github issues (#203) ... * Add estimator example for github issues This is code input for doc about writing Keras for tfjob. There are few todos: 1. bug in dataset injection, can't raise number of steps 2. intead of adding hostpath for data, we should have quick job + pvc for this * pyling * wip * confirmed working on minikube * pylint * remove t2t, add documentation * add note about storageclass * fix link * remove code redundancy * adress review * small language fix	2018-08-24 18:10:27 -07:00