A function wrapper for launching model training according to cfg. Because we need different eval_hook in runner. Should be deprecated in the future.
(model,
dataset,
cfg,
distributed=False,
validate=False,
timestamp=None,
eval_model=None,
meta=None)
| 9 | from mmdet.apis import train_detector |
| 10 | |
| 11 | def custom_train_model(model, |
| 12 | dataset, |
| 13 | cfg, |
| 14 | distributed=False, |
| 15 | validate=False, |
| 16 | timestamp=None, |
| 17 | eval_model=None, |
| 18 | meta=None): |
| 19 | """A function wrapper for launching model training according to cfg. |
| 20 | |
| 21 | Because we need different eval_hook in runner. Should be deprecated in the |
| 22 | future. |
| 23 | """ |
| 24 | if cfg.model.type in ['EncoderDecoder3D']: |
| 25 | assert False |
| 26 | else: |
| 27 | custom_train_detector( |
| 28 | model, |
| 29 | dataset, |
| 30 | cfg, |
| 31 | distributed=distributed, |
| 32 | validate=validate, |
| 33 | timestamp=timestamp, |
| 34 | eval_model=eval_model, |
| 35 | meta=meta) |
| 36 | |
| 37 | |
| 38 | def train_model(model, |
no test coverage detected