feat: retain best checkpoints and support alternate output roots

opengait/main.py

@@ -4,7 +4,14 @@ import argparse
 import torch
 import torch.nn as nn
 from modeling import models
-from opengait.utils import config_loader, get_ddp_module, init_seeds, params_count, get_msg_mgr
+from opengait.utils import (
+    config_loader,
+    get_ddp_module,
+    get_msg_mgr,
+    init_seeds,
+    params_count,
+    resolve_output_path,
+)
 
 parser = argparse.ArgumentParser(description='Main program for opengait.')
 parser.add_argument('--local_rank', type=int, default=0,
@@ -25,8 +32,7 @@ def initialization(cfgs, training):
     msg_mgr = get_msg_mgr()
     engine_cfg = cfgs['trainer_cfg'] if training else cfgs['evaluator_cfg']
     logger_cfg = cfgs.get('logger_cfg', {})
-    output_path = os.path.join('output/', cfgs['data_cfg']['dataset_name'],
-                               cfgs['model_cfg']['model'], engine_cfg['save_name'])
+    output_path = resolve_output_path(cfgs, engine_cfg)
     if training:
         msg_mgr.init_manager(
             output_path,