Add timestamp and elapsed time for epoch (#273)

* add timestamp and epoch elapsed time

* don't need a class

* Revert "add timestamp and epoch elapsed time"

This reverts commit 93b8d4a7af.

* adjust class def

* delete duplicate import

---------

Co-authored-by: Ftps <63702646+Tps-F@users.noreply.github.com>
Co-authored-by: 源文雨 <41315874+fumiama@users.noreply.github.com>

train_nsf_sim_cache_sid_load_pretrain.py

@@ -4,6 +4,7 @@ now_dir = os.getcwd()
 sys.path.append(os.path.join(now_dir))
 sys.path.append(os.path.join(now_dir, "train"))
 import utils
+import datetime
 
 hps = utils.get_hparams()
 os.environ["CUDA_VISIBLE_DEVICES"] = hps.gpus.replace("-", ",")
@@ -50,6 +51,18 @@ from process_ckpt import savee
 
 global_step = 0
 
+class EpochRecorder:
+    def __init__(self):
+        self.last_time = ttime()
+    
+
+    def record(self):
+        now_time = ttime()
+        elapsed_time = now_time - self.last_time
+        self.last_time = now_time
+        elapsed_time_str = str(datetime.timedelta(seconds=elapsed_time))
+        current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        return f"[{current_time}] | ({elapsed_time_str})"
 
 def main():
     # n_gpus = torch.cuda.device_count()
@@ -323,6 +336,7 @@ def train_and_evaluate(
         data_iterator = enumerate(train_loader)
 
     # Run steps
+    epoch_recorder = EpochRecorder()
     for batch_idx, info in data_iterator:
         # Data
         ## Unpack
@@ -542,7 +556,7 @@ def train_and_evaluate(
             )
 
     if rank == 0:
-        logger.info("====> Epoch: {}".format(epoch))
+        logger.info("====> Epoch: {} {}".format(epoch, epoch_recorder.record()))
     if epoch >= hps.total_epoch and rank == 0:
         logger.info("Training is done. The program is closed.")