Comments (6)
I did not tune the tile size for this workload. A possible quick fix can be adding these lines before this assertion.
if OW % VW != 0:
while OW % VW != 0:
VW //= 2
if CO % (2 * VC) == 0:
VC *= 2
OW
is the output width of this conv layer, VW
is the tile size on this dimension.
from tvm-mali.
Which file to change?
Thanks,
from tvm-mali.
Add before this line
File "build/bdist.linux-x86_64/egg/topi/mali/conv2d.py", line 184, in _decl_direct
assert OW % VW == 0, "OW: %d VW : %d" % (OW, VW)
AssertionError: OW: 22 VW : 4
from tvm-mali.
It works with your change. However, the performance of this model on firefly is not very good (0.75sec/frame on average). I can reproduce your data of Mobilenet on my firefly3399.
My main application is object detection and not able to find any object detection model which NNVM can support (missing operators in NNVM frontend). I am hoping that NNVM can support SSD-Mobilenet very soon.
Thanks,
from tvm-mali.
Thanks for your report. The performance may not be very good for all workloads.
Because currently I only tune for vgg, mobilenet, resnet on 224x224 imagenet images. For other workloads, you need re-tune parameters like tiling factor and unroll flag to get the best performance. I do not have plan to tune for your workloads manually in the near future. But an auto-tuner for tvm is on the plan. Once the auto-tuner is released, we can try it for your task.
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Thanks
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