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Since tensorflow.tensor also support protobuf
https://github.com/tensorflow/tensorflow/blob/754048a0453a04a761e112ae5d99c149eb9910dd/tensorflow/core/framework/tensor.proto
I saw there would be a performance issue here
about 80% of this time is spent on slow data conversions between Spark and TensorFlow
would it worth it to convert data into proto and cache it if needed
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oh.. nice nice, maybe we can update this https://github.com/databricks/tensorframes#acknowledgements
and... can we cache the tensors? for the k means example would do multiple passes. it would save the convert time
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Since tensorflow.tensor also support protobuf
https://github.com/tensorflow/tensorflow/blob/754048a0453a04a761e112ae5d99c149eb9910dd/tensorflow/core/framework/tensor.proto
I saw there would be a performance issue here
would it worth it to convert data into proto and cache it if needed
The text was updated successfully, but these errors were encountered: