ecosystem
TensorFlowOnSpark
| ecosystem | TensorFlowOnSpark | |
|---|---|---|
| 4 | 2 | |
| 1,365 | 3,864 | |
| 0.1% | 0.1% | |
| 0.0 | 1.4 | |
| about 2 months ago | 10 months ago | |
| Scala | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ecosystem
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[D] What is the recommended approach to training NN on big data set?
I have a big data set that I would like to train on, so my thought is that I am going to do distributed training , but I am currently setting up MultiWorkerMirroredStrategy on tensorflow and i find it hard to use even with https://github.com/tensorflow/ecosystem/tree/master/spark/spark-tensorflow-distributor
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What is the distributed version of model.save in tensorflow using MultiWorkerMirroredStrategy?
I am using https://github.com/tensorflow/ecosystem/tree/master/spark/spark-tensorflow-distributor
- [D] Plug or Integrate a GNN Pytorch code base into Spark Cluster
TensorFlowOnSpark
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[D]Speed up inference on Spark
Currently I use TensorflowOnSpark frame to train and predict model. When prediction, I have billions of samples to predict which is time-consuming. I wonder if there is some good practices on this.
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[D] Plug or Integrate a GNN Pytorch code base into Spark Cluster
https://github.com/yahoo/TensorFlowOnSpark : check out if this project is useful for you.
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