Missing converter for HashingTF

[sansr]

Hello everyone!

I am trying to convert an instance of HashingTF sparkml transformer. When I invoke convert_sparkml function I get an error that says that 'pyspark.ml.feature.HashingTF' is not supported.

I was looking into the source code and I discovered that 'pyspark.ml.feature.HashingTF' is a transformer built into get_sparkml_operator_name (inside ops_names.py) but later it doesn't appear into the map created in get_input_names function (that is inside ops_input_output.py), that is where it is check if a transformer/estimator is valir or not. Does this have any explanation why it is not supported? Or is a bug?

Any help is well appreciated. Thank you!

[bipin2295]

Hi @sansr , Did you find the solution, I too have ran into same issue. I can see that HashingTF is present as a key in the build_sparkml_operator_name_map() in ops_names.py, yet it's throwing keyerror.

[xadupre]

There is no easy way to do hashes with ONNX. There is no dedicated operator and hashing with current operator is not straightforward. This implementation may take some time.