Replies: 3 comments
|
QAT is going through the same code path as PTQ. if you don't have some special handling for conv-bn, you could start with adding the configuration for QAT, like: https://github.com/pytorch/pytorch/blob/a0429c01ad665ffb2faa04a411913ecee9962566/torch/ao/quantization/quantizer/xnnpack_quantizer.py#L116 |
0 replies
|
@cccclai can you tag qualcomm POC to see if they want to support QAT? |
0 replies
|
Yeah QAT is supported. cc: @shewu-quic @chunit-quic @haowhsu-quic @winskuo-quic let's add some docs |
0 replies
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
I want to use qat method for my model, but i can only find ptq quantizer in executorch, are there some examples of how to implement Quantization Aware Training (QAT) for qnn backend?
All reactions