diff --git a/src/diffusers/pipelines/chroma/pipeline_chroma.py b/src/diffusers/pipelines/chroma/pipeline_chroma.py
index b47a67dc77..0274c3e5d0 100644
--- a/src/diffusers/pipelines/chroma/pipeline_chroma.py
+++ b/src/diffusers/pipelines/chroma/pipeline_chroma.py
@@ -304,6 +304,7 @@ class ChromaPipeline(
 
         return prompt_embeds, text_ids
 
+    # Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.encode_image
     def encode_image(self, image, device, num_images_per_prompt):
         dtype = next(self.image_encoder.parameters()).dtype
 
@@ -315,6 +316,7 @@ class ChromaPipeline(
         image_embeds = image_embeds.repeat_interleave(num_images_per_prompt, dim=0)
         return image_embeds
 
+    # Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.prepare_ip_adapter_image_embeds
     def prepare_ip_adapter_image_embeds(
         self, ip_adapter_image, ip_adapter_image_embeds, device, num_images_per_prompt
     ):
@@ -395,6 +397,7 @@ class ChromaPipeline(
         if max_sequence_length is not None and max_sequence_length > 512:
             raise ValueError(f"`max_sequence_length` cannot be greater than 512 but is {max_sequence_length}")
 
+    # Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.prepare_latent_image_ids
     @staticmethod
     def _prepare_latent_image_ids(batch_size, height, width, device, dtype):
         latent_image_ids = torch.zeros(height, width, 3)
@@ -409,6 +412,7 @@ class ChromaPipeline(
 
         return latent_image_ids.to(device=device, dtype=dtype)
 
+    # Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline._pack_latents
     @staticmethod
     def _pack_latents(latents, batch_size, num_channels_latents, height, width):
         latents = latents.view(batch_size, num_channels_latents, height // 2, 2, width // 2, 2)
@@ -417,6 +421,7 @@ class ChromaPipeline(
 
         return latents
 
+    # Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline._unpack_latents
     @staticmethod
     def _unpack_latents(latents, height, width, vae_scale_factor):
         batch_size, num_patches, channels = latents.shape
@@ -462,6 +467,8 @@ class ChromaPipeline(
         """
         self.vae.disable_tiling()
 
+
+    # Copied from diffusers.pipelines.flux.pipeline_flux.FluxPipeline.prepare_latents
     def prepare_latents(
         self,
         batch_size,