Improved model+EMA checkpointing 2 (#2295)

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Glenn Jocher authored and GitHub committed 2021-02-24 21:03:21 -08:00
1 parent ec1d8496ba
commit 71dd2768f2
2 files changed
+4 -4

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@@ -269,6 +269,7 @@ def test(data,
print(f'pycocotools unable to run: {e}') print(f'pycocotools unable to run: {e}')
# Return results # Return results
model.float() # for training
if not training: if not training:
s = f"\n{len(list(save_dir.glob('labels/*.txt')))} labels saved to {save_dir / 'labels'}" if save_txt else '' s = f"\n{len(list(save_dir.glob('labels/*.txt')))} labels saved to {save_dir / 'labels'}" if save_txt else ''
print(f"Results saved to {save_dir}{s}") print(f"Results saved to {save_dir}{s}")
+3 -4
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@@ -4,6 +4,7 @@ import math
import os import os
import random import random
import time import time
from copy import deepcopy
from pathlib import Path from pathlib import Path
from threading import Thread from threading import Thread
@@ -381,8 +382,8 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
ckpt = {'epoch': epoch, ckpt = {'epoch': epoch,
'best_fitness': best_fitness, 'best_fitness': best_fitness,
'training_results': results_file.read_text(), 'training_results': results_file.read_text(),
'model': (model.module if is_parallel(model) else model).half(), 'model': deepcopy(model.module if is_parallel(model) else model).half(),
'ema': (ema.ema.half(), ema.updates), 'ema': (deepcopy(ema.ema).half(), ema.updates),
'optimizer': optimizer.state_dict(), 'optimizer': optimizer.state_dict(),
'wandb_id': wandb_run.id if wandb else None} 'wandb_id': wandb_run.id if wandb else None}
@@ -392,8 +393,6 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
torch.save(ckpt, best) torch.save(ckpt, best)
del ckpt del ckpt
model.float(), ema.ema.float()
# end epoch ---------------------------------------------------------------------------------------------------- # end epoch ----------------------------------------------------------------------------------------------------
# end training # end training