Add evaluation script, code review and fix some bugs

1. Add new `train_all` method for one shot calling
2. Print time used in 1k iterations
3. Correct label dimension in predict function
4. Transpose distance matrix for convenient indexing
5. Sort dictionary before generate signature
6. Extract visible CUDA setting function

1 files changed, 4 insertions, 12 deletions

diff --git a/train.py b/train.py
index cdb2fb0..d91dcd0 100644
--- a/train.py
+++ b/train.py
@@ -1,14 +1,9 @@
-import os
-
 from config import config
 from models import Model
 from utils.dataset import ClipConditions
+from utils.misc import set_visible_cuda
 
-# Set environment variable CUDA device(s)
-CUDA_VISIBLE_DEVICES = config['system'].get('CUDA_VISIBLE_DEVICES', None)
-if CUDA_VISIBLE_DEVICES:
-    os.environ['CUDA_VISIBLE_DEVICES'] = CUDA_VISIBLE_DEVICES
-
+set_visible_cuda(config['system'])
 model = Model(config['system'], config['model'], config['hyperparameter'])
 
 # 3 models for different conditions
@@ -17,8 +12,5 @@ dataset_selectors = {
     'bg': {'conditions': ClipConditions({r'nm-0\d', r'bg-0\d'})},
     'cl': {'conditions': ClipConditions({r'nm-0\d', r'cl-0\d'})},
 }
-for selector in dataset_selectors.values():
-    model.fit(
-        dict(**config['dataset'], **{'selector': selector}),
-        config['dataloader']
-    )
+
+model.fit_all(config['dataset'], dataset_selectors, config['dataloader'])