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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/03/29 18:15:58 UTC
[GitHub] [incubator-tvm] siju-samuel opened a new pull request #5167:
[RELAY][QNN]Add support for QNN Div operator
siju-samuel opened a new pull request #5167: [RELAY][QNN]Add support for QNN Div operator
URL: https://github.com/apache/incubator-tvm/pull/5167
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[GitHub] [incubator-tvm] siju-samuel commented on issue #5167:
[RELAY][QNN]Add support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
siju-samuel commented on issue #5167: [RELAY][QNN]Add support for QNN Div operator
URL: https://github.com/apache/incubator-tvm/pull/5167#issuecomment-606714956
HI @anijain2305 I was trying to run quantized Mobilenetv3, it has a hard_swish node, which will need a div op.
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[GitHub] [incubator-tvm] masahi commented on issue #5167: [RELAY][QNN]Add
support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
masahi commented on issue #5167: [RELAY][QNN]Add support for QNN Div operator
URL: https://github.com/apache/incubator-tvm/pull/5167#issuecomment-609003422
@siju-samuel What frontend are you using? Torch frontend can already convert and run quantized mobilnet v3. I didn't have a need for QNN div op. For hswish, Torch uses `quantized::mul_scalar` op, which is a scaling by 1/6.
For scaling by positive scalar, I didn't have to do anything. Just changing the "interpretation" of the input quantized tensor is all I needed. See
https://github.com/apache/incubator-tvm/blob/03cbf78e3e8cc910c5a9c95cd3fcafa19959644f/python/tvm/relay/frontend/qnn_torch.py#L697-L701
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[GitHub] [incubator-tvm] siju-samuel commented on issue #5167:
[RELAY][QNN]Add support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
siju-samuel commented on issue #5167: [RELAY][QNN]Add support for QNN Div operator
URL: https://github.com/apache/incubator-tvm/pull/5167#issuecomment-609405224
@masahi Thanks a lot for your suggestion. i was using tflite frontend. As of now i used dequantize/quantize methods and i was able to run mobilenetv3 models, there are variations in output, still accuracy is not hit very badly.
We can use `mul_scalar` method since its scalar, still i suggest, we can keep the `qnn.div` op for non scalar multiplications.
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[GitHub] [incubator-tvm] anijain2305 commented on issue #5167:
[RELAY][QNN]Add support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
anijain2305 commented on issue #5167: [RELAY][QNN]Add support for QNN Div operator
URL: https://github.com/apache/incubator-tvm/pull/5167#issuecomment-606777410
Thanks @siju-samuel I will read it and review the PR today. Thanks for increasing the coverage :)
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[GitHub] [incubator-tvm] anijain2305 commented on issue #5167:
[RELAY][QNN]Add support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
anijain2305 commented on issue #5167: [RELAY][QNN]Add support for QNN Div operator
URL: https://github.com/apache/incubator-tvm/pull/5167#issuecomment-606314013
Hi @siju-samuel Thanks for the effort. Can you please give a usecase where we use quantized division? is there any quantized division operator?
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[GitHub] [incubator-tvm] tqchen commented on pull request #5167: [RELAY][QNN]Add support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
tqchen commented on pull request #5167:
URL: https://github.com/apache/incubator-tvm/pull/5167#issuecomment-678339747
@siju-samuel @masahi @anijain2305 please comment on the status of the PR, we should act or close it to keep the issue tracker up to date
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[GitHub] [incubator-tvm] tqchen closed pull request #5167: [RELAY][QNN]Add support for QNN Div operator
Posted by GitBox <gi...@apache.org>.
tqchen closed pull request #5167:
URL: https://github.com/apache/incubator-tvm/pull/5167
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