diff options
| -rw-r--r-- | models/model.py | 22 |
1 files changed, 13 insertions, 9 deletions
diff --git a/models/model.py b/models/model.py index 89b34aa..5966ae1 100644 --- a/models/model.py +++ b/models/model.py @@ -392,12 +392,12 @@ class Model: dataset_selectors: dict[ str, dict[str, Union[ClipClasses, ClipConditions, ClipViews]] ], - dataloader_config: DataloaderConfiguration + dataloader_config: DataloaderConfiguration, + is_train: bool = False ): - self.is_train = False # Split gallery and probe dataset gallery_dataloader, probe_dataloaders = self._split_gallery_probe( - dataset_config, dataloader_config + dataset_config, dataloader_config, is_train ) # Get pretrained models at iter_ checkpoints = self._load_pretrained( @@ -506,10 +506,11 @@ class Model: ] ) -> dict[str, str]: checkpoints = {} - for (iter_, (condition, selector)) in zip( - iters, dataset_selectors.items() + for (iter_, total_iter, (condition, selector)) in zip( + iters, self.total_iters, dataset_selectors.items() ): self.curr_iter = iter_ + self.total_iter = total_iter self._dataset_sig = self._make_signature( dict(**dataset_config, **selector), popped_keys=['root_dir', 'cache_on'] @@ -521,26 +522,29 @@ class Model: self, dataset_config: DatasetConfiguration, dataloader_config: DataloaderConfiguration, + is_train: bool = False ) -> tuple[DataLoader, dict[str, DataLoader]]: dataset_name = dataset_config.get('name', 'CASIA-B') if dataset_name == 'CASIA-B': + self.is_train = is_train gallery_dataset = self._parse_dataset_config( dict(**dataset_config, **self.CASIAB_GALLERY_SELECTOR) ) - self._gallery_dataset_meta = gallery_dataset.metadata - gallery_dataloader = self._parse_dataloader_config( - gallery_dataset, dataloader_config - ) probe_datasets = { condition: self._parse_dataset_config( dict(**dataset_config, **selector) ) for (condition, selector) in self.CASIAB_PROBE_SELECTORS.items() } + self._gallery_dataset_meta = gallery_dataset.metadata self._probe_datasets_meta = { condition: dataset.metadata for (condition, dataset) in probe_datasets.items() } + self.is_train = False + gallery_dataloader = self._parse_dataloader_config( + gallery_dataset, dataloader_config + ) probe_dataloaders = { condition: self._parse_dataloader_config( dataset, dataloader_config |