Hello~ I am facing the similar problem!
I use autotvm tuned a CNN model trained by tensorflow, all the ops in the model
were tuned.
After that, I load log file by relay, and test it’s performence, I found the
whole TVM infer time is bigger than the tensofrflow far away.
The "mod.get_out(0).asnumpy()" time is about 240ms!!!
I observe the following information when I test the TVM tuned model.
Extract tasks...
Compile...
Cannot find config for target=cuda -keys=cuda,gpu -max_num_threads=1024
-model=unknown -
thread_warp_size=32, workload=('dense_small_batch.cuda', ('TENSOR', (2500,
512), 'float32'),
('TENSOR', (6600, 512), 'float32'), None, 'float32'). A fallback
configuration is used, which may bring
great performance regression.
How to fix this non-exists configuration for workload named
"dense_small_batch.cuda" ?
Looking for your reply! Thank you very much!
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