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Keras support? #23
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I haven't actually tried this, but I am guessing you could use tf.keras.layers (and maybe the default keras layers? Not sure). The optimizers will still need to be tensorflow though. We provided an abstraction for some of the optimizers in sparkflow.graph_utils, and just like keras, you can specify by string the optimizer that you want to use. |
tf.keras should work I guess, will check. Thanks. |
Hi, are there any updates on this thread? Has tf.keras been tried and does this work? Thanks |
When I get some time, I can provide an example. Since the graph gets created the same tf.leras should definitely work. You just won't be able to use the model.compile, etc from keras. I am currently working on some updates for tensorflow 2.0, where keras is a major feature in that release. |
I think you are on the right track by focusing on TF 2.0 where Keras is a first-class citizen. Also, TF 2.0 is much cleaner and much easier to use, so thanks for working on it @dmmiller612 👍 |
Hi Devs,
I really liked the clean API of sparkflow for distributed training. Is it possible to run keras code using sparkflow?
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