The following two images show the tuning results of the same model
- The first one resulted in ~171ms latency after 61440 trials. After validating the output, all the output values from the model match the Keras model. Best tune records: working_autoscheduler_mali - Pastebin.com
- The second one resulted in ~71ms latency after 29632 trials. After validating the output, all the output values are completely mismatched Keras model. Best tune records: broken_autoscheduler_mali - Pastebin.com
This is the description of all tasks that had been tuned: 1/14 fused_nn_conv2d_multiply_expand_dims_add_nn_relu_negative_nn_relu_multiply_ - Pastebin.com
My observations are:
- First, this happens randomly, but if I include all the simple tasks for tuning, it definitely going to happen!
- For example, task #3: normally achieved 66.29 GFLOPS but suddenly jumped to 6308.76 GFLOPS. There are only different in the SP (SplitStep) of the record, for example
"SP", 3, 5, 256, [1, 2, 1, 1]to
"SP", 3, 5, 256, [1, 2, 16, 2]
- In task#8, also there is differences in the PragmaStep auto unroll:
["PR", 3, 0, "auto_unroll_max_step$64"]→
["PR", 3, 0, "auto_unroll_max_step$16"]
- In task#13, again only there are differences in the SplitStep.
I have tried to update TVM to the newest version on GitHub but the same things still happen. Please help me in understanding why such things happen.
Thanks in advance!