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[Tracking Issue] Pre-quantized RNN Operators Support (e.g., UnidirectionalSequenceLSTM from TFlite)

Open dftercero opened this issue 3 years ago • 3 comments

This issue is to track progress for Pre-quantized RNN Operators

It'd be great to expand support for recurrent quantized operators, such as the UnidirectionalSequenceLSTM from TensorFlow. Are there any timelines for this in the current roadmap?

Resources:

  • TFlite frontend: https://github.com/apache/tvm/blob/main/python/tvm/relay/frontend/tflite.py
  • Tensorflow fused RNN Operator: https://www.tensorflow.org/lite/models/convert/rnn

dftercero avatar Oct 20 '22 01:10 dftercero

@lhutton1 @leandron You guys have done a lot of work recently with quantized operators from TFLite based on #9187. Any thoughts on this? Thanks in advanced

dftercero avatar Oct 20 '22 01:10 dftercero

Hi @dftercero, I don't believe there is any ongoing work to support it yet. I don't know much about this operator, although, after a quick search of the codebase it looks like a bit more work would be needed to support the quantized variant of LSTM in TVM rather than simply making a conversion in the frontend

lhutton1 avatar Oct 24 '22 16:10 lhutton1

Hi @hpanda-naut @lhutton1, is there any ongoing work to support the quantized version of it ? if no, can you give hints about the needed work to do so, I would like to contribute...

amroceva avatar May 21 '24 05:05 amroceva