complete ddim integration of diffusion prior as well as decoder for each unet, feature complete for https://github.com/lucidrains/DALLE2-pytorch/issues/157

dalle2_pytorch/train_configs.py

@@ -234,7 +234,7 @@ class DecoderConfig(BaseModel):
     clip: Optional[AdapterConfig]   # The clip model to use if embeddings are not provided
     channels: int = 3
     timesteps: int = 1000
-    sample_timesteps: Optional[SingularOrIterable(int)] = None
+    sampling_timesteps: Optional[SingularOrIterable(int)] = None
     loss_type: str = 'l2'
     beta_schedule: ListOrTuple(str) = 'cosine'
     learned_variance: bool = True

dalle2_pytorch/version.py

@@ -1 +1 @@
-__version__ = '0.19.1'
+__version__ = '0.19.0'