summaryrefslogtreecommitdiff
path: root/models/model.py
diff options
context:
space:
mode:
Diffstat (limited to 'models/model.py')
-rw-r--r--models/model.py31
1 files changed, 14 insertions, 17 deletions
diff --git a/models/model.py b/models/model.py
index 1154d7f..7cf6ed0 100644
--- a/models/model.py
+++ b/models/model.py
@@ -13,9 +13,6 @@ from torch.utils.tensorboard import SummaryWriter
from tqdm import tqdm
from models.rgb_part_net import RGBPartNet
-from utils.configuration import DataloaderConfiguration, \
- HyperparameterConfiguration, DatasetConfiguration, ModelConfiguration, \
- SystemConfiguration
from utils.dataset import CASIAB, ClipConditions, ClipViews, ClipClasses
from utils.sampler import TripletSampler
@@ -23,9 +20,9 @@ from utils.sampler import TripletSampler
class Model:
def __init__(
self,
- system_config: SystemConfiguration,
- model_config: ModelConfiguration,
- hyperparameter_config: HyperparameterConfiguration
+ system_config: Dict,
+ model_config: Dict,
+ hyperparameter_config: Dict
):
self.disable_acc = system_config['disable_acc']
if self.disable_acc:
@@ -89,11 +86,11 @@ class Model:
def fit_all(
self,
- dataset_config: DatasetConfiguration,
+ dataset_config: Dict,
dataset_selectors: Dict[
str, Dict[str, Union[ClipClasses, ClipConditions, ClipViews]]
],
- dataloader_config: DataloaderConfiguration,
+ dataloader_config: Dict,
):
for (condition, selector) in dataset_selectors.items():
print(f'Training model {condition} ...')
@@ -104,8 +101,8 @@ class Model:
def fit(
self,
- dataset_config: DatasetConfiguration,
- dataloader_config: DataloaderConfiguration,
+ dataset_config: Dict,
+ dataloader_config: Dict,
):
self.is_train = True
dataset = self._parse_dataset_config(dataset_config)
@@ -184,11 +181,11 @@ class Model:
def predict_all(
self,
iter_: int,
- dataset_config: DatasetConfiguration,
+ dataset_config: dict,
dataset_selectors: Dict[
str, Dict[str, Union[ClipClasses, ClipConditions, ClipViews]]
],
- dataloader_config: DataloaderConfiguration,
+ dataloader_config: dict,
) -> Dict[str, torch.Tensor]:
self.is_train = False
# Split gallery and probe dataset
@@ -296,7 +293,7 @@ class Model:
def _load_pretrained(
self,
iter_: int,
- dataset_config: DatasetConfiguration,
+ dataset_config: Dict,
dataset_selectors: Dict[
str, Dict[str, Union[ClipClasses, ClipConditions, ClipViews]]
]
@@ -313,8 +310,8 @@ class Model:
def _split_gallery_probe(
self,
- dataset_config: DatasetConfiguration,
- dataloader_config: DataloaderConfiguration,
+ dataset_config: Dict,
+ dataloader_config: Dict,
) -> Tuple[DataLoader, Dict[str: DataLoader]]:
dataset_name = dataset_config.get('name', 'CASIA-B')
if dataset_name == 'CASIA-B':
@@ -364,7 +361,7 @@ class Model:
def _parse_dataset_config(
self,
- dataset_config: DatasetConfiguration
+ dataset_config: Dict
) -> Union[CASIAB]:
self.train_size = dataset_config.get('train_size', 74)
self.in_channels = dataset_config.get('num_input_channels', 3)
@@ -385,7 +382,7 @@ class Model:
def _parse_dataloader_config(
self,
dataset: Union[CASIAB],
- dataloader_config: DataloaderConfiguration
+ dataloader_config: Dict
) -> DataLoader:
config: Dict = dataloader_config.copy()
(self.pr, self.k) = config.pop('batch_size')