Handle latent dim difference for image model in the VAE instead

This commit is contained in:
kijai 2025-11-27 19:27:53 +02:00
parent 653ad84203
commit 4acd51abab
2 changed files with 2 additions and 3 deletions

View File

@ -1690,6 +1690,3 @@ class Kandinsky5_image(Kandinsky5):
def concat_cond(self, **kwargs):
return None
def process_latent_out(self, latent): # input is still 5D, return single frame to decode with Flux VAE
return self.latent_format.process_out(latent)[:, :, 0]

View File

@ -742,6 +742,8 @@ class VAE:
self.throw_exception_if_invalid()
pixel_samples = None
do_tile = False
if self.latent_dim == 2 and samples_in.ndim == 5:
samples_in = samples_in[:, :, 0]
try:
memory_used = self.memory_used_decode(samples_in.shape, self.vae_dtype)
model_management.load_models_gpu([self.patcher], memory_required=memory_used, force_full_load=self.disable_offload)