update

Author: a-r-r-o-w

src/diffusers/models/transformers/transformer_mochi.py

@@ -269,6 +269,8 @@ def __init__(
         time_embed_dim: int = 256,
         activation_fn: str = "swiglu",
         max_sequence_length: int = 256,
+        sample_height: int = 60,
+        sample_width: int = 106,
     ) -> None:
         super().__init__()
 

src/diffusers/pipelines/mochi/pipeline_mochi.py

@@ -207,8 +207,6 @@ def __init__(
         self.tokenizer_max_length = (
             self.tokenizer.model_max_length if hasattr(self, "tokenizer") and self.tokenizer is not None else 77
         )
-        self.default_height = 480
-        self.default_width = 848
 
     # Adapted from diffusers.pipelines.cogvideo.pipeline_cogvideox.CogVideoXPipeline._get_t5_prompt_embeds
     def _get_t5_prompt_embeds(
@@ -577,8 +575,8 @@ def __call__(
         if isinstance(callback_on_step_end, (PipelineCallback, MultiPipelineCallbacks)):
             callback_on_step_end_tensor_inputs = callback_on_step_end.tensor_inputs
 
-        height = height or self.default_height
-        width = width or self.default_width
+        height = height or self.transformer.config.sample_height * self.vae_spatial_scale_factor
+        width = width or self.transformer.config.sample_width * self.vae_spatial_scale_factor
 
         # 1. Check inputs. Raise error if not correct
         self.check_inputs(