diff --git a/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py b/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py index de41e82..7d1f154 100644 --- a/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py +++ b/hyvideo/diffusion/pipelines/pipeline_hunyuan_video.py @@ -512,7 +512,7 @@ class HunyuanVideoPipeline(DiffusionPipeline): self._num_timesteps = len(timesteps) - logger.info(f"Sampling {video_length} frames in {latents.shape[2]} latents at {width}x{height} with {num_inference_steps} inference steps") + logger.info(f"Sampling {video_length} frames in {latents.shape[2]} latents at {width}x{height} with {len(timesteps)} inference steps") comfy_pbar = ProgressBar(len(timesteps)) with self.progress_bar(total=len(timesteps)) as progress_bar: for i, t in enumerate(timesteps): diff --git a/hyvideo/vae/autoencoder_kl_causal_3d.py b/hyvideo/vae/autoencoder_kl_causal_3d.py index 1793eb0..b809989 100644 --- a/hyvideo/vae/autoencoder_kl_causal_3d.py +++ b/hyvideo/vae/autoencoder_kl_causal_3d.py @@ -486,9 +486,9 @@ class AutoencoderKLCausal3D(ModelMixin, ConfigMixin, FromOriginalVAEMixin): B, C, T, H, W = x.shape overlap_size = int(self.tile_sample_min_tsize * - (1 - self.tile_overlap_factor)) + (1 - self.t_tile_overlap_factor)) blend_extent = int(self.tile_latent_min_tsize * - self.tile_overlap_factor) + self.t_tile_overlap_factor) t_limit = self.tile_latent_min_tsize - blend_extent # Split the video into tiles and encode them separately. diff --git a/nodes.py b/nodes.py index e01c7f4..39d1c70 100644 --- a/nodes.py +++ b/nodes.py @@ -893,7 +893,7 @@ class HyVideoDecode: vae.t_tile_overlap_factor = 0.25 else: #defaults - vae.tile_latent_min_tsize = 64 + vae.tile_latent_min_tsize = 16 vae.tile_sample_min_size = 256 vae.tile_latent_min_size = 32 @@ -976,7 +976,7 @@ class HyVideoEncode: vae.t_tile_overlap_factor = 0.25 else: #defaults - vae.tile_latent_min_tsize = 64 + vae.tile_latent_min_tsize = 16 vae.tile_sample_min_size = 256 vae.tile_latent_min_size = 32