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First of all, thanks for great work.
I re-train with model_type as LMTCNN-2-1 and freeze model as pb with inference.py.
My target is to use this frozen pb and run with Intel Openvino sdk in x86 machine.
It takes 2 steps to complete. First step is convert pb file into openvino format.
I always got error related to is_training can't be true in batch_norm like below.
FusedBatchNorm doesn't support is_training=True. Node multitaskdpcnn/convdp1/dw_batch_norm/FusedBatchNorm
I also try to modify LMTCNN-2-1 and gives batch_norm_param {is_training} True/False for Training and inference respectively. But still can't make anything different.
However, when i convert all pb files inside androidversion/TF_FACE, convert process goes well without any problem.
Would you help hint how androidversion/TF_FACE/ pb files are frozen?
Thanks a lot
The text was updated successfully, but these errors were encountered:
Hi,
First of all, thanks for great work.
I re-train with model_type as LMTCNN-2-1 and freeze model as pb with inference.py.
My target is to use this frozen pb and run with Intel Openvino sdk in x86 machine.
It takes 2 steps to complete. First step is convert pb file into openvino format.
I always got error related to is_training can't be true in batch_norm like below.
FusedBatchNorm doesn't support is_training=True. Node multitaskdpcnn/convdp1/dw_batch_norm/FusedBatchNorm
I also try to modify LMTCNN-2-1 and gives batch_norm_param {is_training} True/False for Training and inference respectively. But still can't make anything different.
However, when i convert all pb files inside androidversion/TF_FACE, convert process goes well without any problem.
Would you help hint how androidversion/TF_FACE/ pb files are frozen?
Thanks a lot
The text was updated successfully, but these errors were encountered: