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License: MIT License
This repo contains the official Pytorch reimplementation of the paper "NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications".
License: MIT License
Hi!
I've tried running the code you've provided on MobileNet, the pretrained model, which was given by you as an example. I believe that calculating LUTs went correctly. Then I've tried applying the algorithm with 0,5 latency, by running:
sh scripts/netadapt_mobilenet-0.5latency.sh
but after some time the algorithm stopped proceeding on:
Launch a worker for block 13 ['/usr/local/bin/python', 'worker.py', 'models/mobilenet/prune-by-latency/worker', 'models/mobilenet/prune-by-latency/master/iter_0_best_model.pth.tar', '13', 'LATENCY', '0.033316052734851845', '1', '500', '0', 'latency_lut/lut_mobilenet.pkl', 'data/', '3', '224', '224', 'mobilenet', '0.001'] Update job list: [{'iteration': 1, 'block': 1, 'gpu': 1}, {'iteration': 1, 'block': 2, 'gpu': 2}, {'iteration': 1, 'block': 3, 'gpu': 3}, {'iteration': 1, 'block': 4, 'gpu': 4}, {'iteration': 1, 'block': 5, 'gpu': 5}, {'iteration': 1, 'block': 6, 'gpu': 6}, {'iteration': 1, 'block': 13, 'gpu': 0}] Update available gpu: []
Despite of 3 days of computing it didn't progress more. Could you advise me if something is wrong there?
Regards,
Piotrek
Hi!
Is there a possibility that you provide tensorflow implementation of NetAdapt?
Or, is it possible to run that pytorch implementation on tensorflow saved_model or frozen graph?
Regards,
Piotrek
raise ValueError('target_resource {} is not achievable in iter {}.'.format(target_resource, current_iter))
ValueError: target_resource 718242470.4 is not achievable in iter 1.
Hi,thank you for your work.I trained the code in my project, and I can not find the long-term fine tune in the master.py.Can you help me?Thank you very much!
Hi,
Thanks for you excellent work.
When will you release netadaptv2?
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