update

Author: DN6

src/diffusers/pipelines/flux/pipeline_flux_controlnet_image_to_image.py

@@ -554,6 +554,7 @@ def prepare_latents(
                 f"You have passed a list of generators of length {len(generator)}, but requested an effective batch"
                 f" size of {batch_size}. Make sure the batch size matches the length of the generators."
             )
+
         # VAE applies 8x compression on images but we must also account for packing which requires
         # latent height and width to be divisible by 2.
         height = 2 * (int(height) // (self.vae_scale_factor * 2))

tests/pipelines/controlnet_flux/test_controlnet_flux_img2img.py

@@ -224,7 +224,7 @@ def test_flux_image_output_shape(self):
         pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
         inputs = self.get_dummy_inputs(torch_device)
 
-        height_width_pairs = [(32, 32), (72, 57)]
+        height_width_pairs = [(32, 32), (72, 56)]
         for height, width in height_width_pairs:
             expected_height = height - height % (pipe.vae_scale_factor * 2)
             expected_width = width - width % (pipe.vae_scale_factor * 2)