fix typo

library/sd3_models.py

@@ -1643,7 +1643,7 @@ class T5LayerNorm(torch.nn.Module):
     # copy from transformers' T5LayerNorm
     def forward(self, hidden_states):
         # T5 uses a layer_norm which only scales and doesn't shift, which is also known as Root Mean
-        # Square Layer Normalization https://arxiv.org/abs/1910.07467 thus varience is calculated
+        # Square Layer Normalization https://arxiv.org/abs/1910.07467 thus variance is calculated
         # w/o mean and there is no bias. Additionally we want to make sure that the accumulation for
         # half-precision inputs is done in fp32
         variance = hidden_states.to(torch.float32).pow(2).mean(-1, keepdim=True)

library/sd3_train_utils.py

@@ -279,7 +279,7 @@ def sample_images(*args, **kwargs):
     return train_util.sample_images_common(SdxlStableDiffusionLongPromptWeightingPipeline, *args, **kwargs)
 
 
-class Sd3LatensCachingStrategy(train_util.LatentsCachingStrategy):
+class Sd3LatentsCachingStrategy(train_util.LatentsCachingStrategy):
     SD3_LATENTS_NPZ_SUFFIX = "_sd3.npz"
 
     def __init__(self, vae: sd3_models.SDVAE, cache_to_disk: bool, batch_size: int, skip_disk_cache_validity_check: bool) -> None: