masahi commented on pull request #9164:
URL: https://github.com/apache/tvm/pull/9164#issuecomment-937591028


   @apeskov Please see this PR https://github.com/apache/tvm/pull/9135. I 
understand why you want to do this, namely, constant fold 
`quantize(weight_fp32)` in a QNN graph. Returning float32 weights from the 
PyTorch frontend and relying on Relay constant folding to recover quantized 
weights was my design mistake. Now you can directly obtain quantized weights 
from the frontend (we do quantize at numpy level).


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