Use tqdm.write in order to not break progress bar

main.py

@@ -526,7 +526,7 @@ for iteration in range(n_iter):
     # In case we reached the last 75% of iterations,
     # decrease the learning rate of the optimizer 10-fold.
     if iteration == round(n_iter * 0.75):
-        print("Decreasing LR 10-fold ...")
+        tqdm.write("Decreasing LR 10-fold ...")
         optimizer = torch.optim.Adam(
             neural_radiance_field.parameters(), lr=lr * 0.1
         )
@@ -596,7 +596,7 @@ for iteration in range(n_iter):
 
     # Every 10 iterations, print the current values of the losses.
     if iteration % 10 == 0:
-        print(
+        tqdm.write(
             f"Iteration {iteration:05d}:"
             + f" loss color = {float(color_err):1.2e}"
             + f" loss silhouette = {float(sil_err):1.2e}"