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@ -47,29 +47,30 @@ for idx, params in enumerate(search_params): |
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a, lr, bs, me, s, w = params |
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a, lr, bs, me, s, w = params |
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cmd = f"cd ~/colors && python main.py --alpha {a} --lr {lr} --bs {bs} --max_epochs {me} --seed {s} --width {w}" |
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cmd = f"cd ~/colors && python main.py --alpha {a} --lr {lr} --bs {bs} --max_epochs {me} --seed {s} --width {w}" |
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cmd = f""" |
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cmd = f""" |
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python newmain.py fit \ |
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python newmain.py fit \ |
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--seed_everything {s} \ |
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--seed_everything {s} \ |
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--data.batch_size {bs} \ |
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--data.batch_size {bs} \ |
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--data.train_size 0 \ |
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--data.train_size 0 \ |
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--data.val_size 100000 \ |
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--data.val_size 100000 \ |
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--model.alpha {a} \ |
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--model.alpha {a} \ |
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--model.width {w} \ |
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--model.width {w} \ |
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--trainer.fast_dev_run 1 \ |
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--trainer.min_epochs 10 \ |
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--trainer.min_epochs 10 \ |
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--trainer.max_epochs {me} \ |
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--trainer.max_epochs {me} \ |
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--trainer.log_every_n_steps 3 \ |
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--trainer.check_val_every_n_epoch 1 \ |
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--trainer.check_val_every_n_epoch 10 \ |
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--trainer.callbacks callbacks.SaveImageCallback \ |
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--trainer.limit_val_batches 50 \ |
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--trainer.callbacks.init_args.final_dir out \ |
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--trainer.callbacks callbacks.SaveImageCallback \ |
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--trainer.callbacks.init_args.save_interval 0 \ |
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--trainer.callbacks.init_args.final_dir out \ |
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--optimizer torch.optim.Adam \ |
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--trainer.callbacks.init_args.save_interval 0 \ |
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--optimizer.init_args.lr {lr} \ |
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--optimizer torch.optim.Adam \ |
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--lr_scheduler lightning.pytorch.cli.ReduceLROnPlateau \ |
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--optimizer.init_args.lr {lr} \ |
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--lr_scheduler.init_args.patience 5 \ |
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--lr_scheduler lightning.pytorch.cli.ReduceLROnPlateau \ |
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--lr_scheduler.init_args.cooldown 10 \ |
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--lr_scheduler.init_args.monitor hp_metric \ |
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--lr_scheduler.init_args.factor 0.05 \ |
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--lr_scheduler.init_args.factor 0.05 \ |
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--lr_scheduler.init_args.verbose true \ |
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--lr_scheduler.init_args.patience 5 \ |
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--print_config |
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--lr_scheduler.init_args.cooldown 10 \ |
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""" |
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--lr_scheduler.init_args.verbose true |
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""" |
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# job_name = f"color2_{bs}_{a}_{lr:2.2e}" |
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# job_name = f"color2_{bs}_{a}_{lr:2.2e}" |
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# job_plugin.run(cmd, machine=Machine.T4, name=job_name) |
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# job_plugin.run(cmd, machine=Machine.T4, name=job_name) |
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