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# Start training |
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# Start training |
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t0 = time.time() |
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t0 = time.time() |
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nw = max(round(hyp['warmup_epochs'] * nb), 1000) # number of warmup iterations, max(3 epochs, 1k iterations) |
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nw = max(round(hyp['warmup_epochs'] * nb), 100) # number of warmup iterations, max(3 epochs, 100 iterations) |
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# nw = min(nw, (epochs - start_epoch) / 2 * nb) # limit warmup to < 1/2 of training |
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# nw = min(nw, (epochs - start_epoch) / 2 * nb) # limit warmup to < 1/2 of training |
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last_opt_step = -1 |
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last_opt_step = -1 |
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maps = np.zeros(nc) # mAP per class |
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maps = np.zeros(nc) # mAP per class |