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🐺 add checkpoint argument for finetuning #5

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🐺 add checkpoint argument for finetuning #5

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3 changes: 3 additions & 0 deletions avocodo/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,7 @@ def log_metrics(self, metrics, step):
parser.add_argument('--config', default='avocodo/configs/avocodo_v1.json')
parser.add_argument('--training_epochs', default=5000, type=int)
parser.add_argument('--fine_tuning', default=False, type=bool)
parser.add_argument('--resume_checkpoint_path', default=None, type=str, help="Path to the checkpoint to resume training/finetune on")

a = parser.parse_args()
OmegaConf.register_new_resolver(
Expand All @@ -44,6 +45,8 @@ def log_metrics(self, metrics, step):

dm = AvocodoData(conf.data)
model = Avocodo(conf.model)
if a.resume_checkpoint_path is not None:
model.load_from_checkpoint(a.resume_checkpoint_path)

limit_train_batches = 1.0
limit_val_batches = 1.0
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