Comments (2)
Indeed at the moment only Conv2d
is explicitly supported in the code, as we haven't had a chance to experiment with quantization of models that have 1D convolutions. But I don't see anything that should prevent Conv1d
from working, seeing as Conv1d
and Conv2d
are both sub-classes of the same parent (_ConvNd
).
To test, please make the following changes:
-
https://github.com/NervanaSystems/distiller/blob/c247b57f6f14e609b39cb3e8c1fbae29ca0fe049/distiller/quantization/quantizer.py#L141-L142
Addnn.Conv1d
to the list in the if condition. -
Depending on which quantization method you are using, you might need to map
Conv1d
to a "replacement factory" function. At the moment onlySymmetricLinearQuantizer
replaces convolution modules. If this is the one you use, add a line here:
https://github.com/NervanaSystems/distiller/blob/master/distiller/quantization/range_linear.py#L195-L196
If and when you find this works, feel free to make a PR with the changes. Let me know if you have additional questions.
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Hi,
Closing issue since it seems resolved and stale. Feel free to reopen.
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