Merge remote-tracking branch 'Melanpan/master'

1 files changed, 15 insertions, 0 deletions

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index e5cb1817..edb8cba1 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -5,6 +5,7 @@ import os
 import sys

 import traceback

 import tqdm

+import csv

 

 import torch

 

@@ -262,6 +263,20 @@ def train_hypernetwork(hypernetwork_name, learn_rate, data_root, log_directory,
             last_saved_file = os.path.join(hypernetwork_dir, f'{hypernetwork_name}-{hypernetwork.step}.pt')

             hypernetwork.save(last_saved_file)

 

+        if write_csv_every > 0 and hypernetwork_dir is not None and hypernetwork.step % write_csv_every == 0:

+            write_csv_header = False if os.path.exists(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv")) else True

+            

+            with open(os.path.join(hypernetwork_dir, "hypernetwork_loss.csv"), "a+") as fout:

+

+                csv_writer = csv.DictWriter(fout, fieldnames=["step", "loss", "learn_rate"])

+                

+                if write_csv_header:

+                    csv_writer.writeheader()

+

+                csv_writer.writerow({"step": hypernetwork.step, 

+                    "loss": f"{losses.mean():.7f}",

+                    "learn_rate": scheduler.learn_rate})

+

         if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0:

             last_saved_image = os.path.join(images_dir, f'{hypernetwork_name}-{hypernetwork.step}.png')