diff --git a/src/diffusers/training_utils.py b/src/diffusers/training_utils.py
index 0e0d0ce5b568..8de9f876b4a2 100644
--- a/src/diffusers/training_utils.py
+++ b/src/diffusers/training_utils.py
@@ -43,6 +43,9 @@ def set_seed(seed: int):
 
     Args:
         seed (`int`): The seed to set.
+
+    Returns:
+        `None`
     """
     random.seed(seed)
     np.random.seed(seed)
@@ -56,8 +59,18 @@ def set_seed(seed: int):
 
 def compute_snr(noise_scheduler, timesteps):
     """
-    Computes SNR as per
-    https://github.com/TiankaiHang/Min-SNR-Diffusion-Training/blob/521b624bd70c67cee4bdf49225915f5945a872e3/guided_diffusion/gaussian_diffusion.py#L847-L849
+    Computes SNR as per https://github.com/TiankaiHang/Min-SNR-Diffusion-Training/blob/521b624bd70c67cee4bdf49225915f5945a872e3/guided_diffusion/gaussian_diffusion.py#L847-L849
+    for the given timesteps using the provided noise scheduler.
+
+    Args:
+        noise_scheduler (`NoiseScheduler`):
+            An object containing the noise schedule parameters, specifically `alphas_cumprod`, which is used
+            to compute the SNR values.
+        timesteps (`torch.Tensor`):
+            A tensor of timesteps for which the SNR is computed.
+
+    Returns:
+        `torch.Tensor`: A tensor containing the computed SNR values for each timestep.
     """
     alphas_cumprod = noise_scheduler.alphas_cumprod
     sqrt_alphas_cumprod = alphas_cumprod**0.5