OK to answer my own question:
The easiest way to disable weight transformations is to exclude winograd tasks from the optimization process. After calling `extract_from_program`, you can filter the returned tasks based on whether `winograd` is in the task name (hacky but simple). Alternatively, if you have logged the tuning history to a file, you can manually edit it to remove the winograd optimizations. Here are some quick performance for resnet18_v2 on a tesla v100 using the same tuning history, just removing the winograds. Model size (bytes) * normal size = 46737836 * winograd size = 77408684 (+66%) Execution latency (batch size 1) * winograd = 0.95ms * non-winograd = 1.33ms (+40%) --- [Visit Topic](https://discuss.tvm.ai/t/inconsistent-params-size-of-optimized-models-vs-non-optimized/6444/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.ai/email/unsubscribe/3e77f825cb194627488ca9898592a48f6d41dd7426d0484f407958da7f33a523).
