diff --git a/library/train_util.py b/library/train_util.py
index 4ae9201d..bb774792 100644
--- a/library/train_util.py
+++ b/library/train_util.py
@@ -2894,6 +2894,12 @@ def add_training_arguments(parser: argparse.ArgumentParser, support_dreambooth:
         default=None,
         help="enable multires noise with this number of iterations (if enabled, around 6-10 is recommended) / Multires noiseを有効にしてこのイテレーション数を設定する（有効にする場合は6-10程度を推奨）",
     )
+    parser.add_argument(
+        "--ip_noise_gamma",
+        type=float,
+        default=None,
+        help="enable input perturbation noise. used for regularization. recommended value: around 0.1 (from arxiv.org/abs/2301.11706) /  ",
+    )
     # parser.add_argument(
     #     "--perlin_noise",
     #     type=int,
@@ -4347,9 +4353,12 @@ def get_noise_noisy_latents_and_timesteps(args, noise_scheduler, latents):
     timesteps = torch.randint(min_timestep, max_timestep, (b_size,), device=latents.device)
     timesteps = timesteps.long()
 
-    # Add noise to the latents according to the noise magnitude at each timestep
-    # (this is the forward diffusion process)
-    noisy_latents = noise_scheduler.add_noise(latents, noise, timesteps)
+    if args.ip_noise_gamma:
+        noisy_latents = noise_scheduler.add_noise(latents, noise + args.ip_noise_gamma * torch.randn_like(latents), timesteps)
+    else:
+        # Add noise to the latents according to the noise magnitude at each timestep
+        # (this is the forward diffusion process)
+        noisy_latents = noise_scheduler.add_noise(latents, noise, timesteps)
 
     return noise, noisy_latents, timesteps