Improve Components API

README.md

@@ -6,22 +6,22 @@ Lightning Diffusion provides components to finetune and serve diffusion model on
 ### Serve ANY Diffusion Models
 
 ```python
-# !pip install torch diffusers lightning_diffusion@git+https://github.com/Lightning-AI/lightning-diffusion.git
+# !pip install lightning_diffusion@git+https://github.com/Lightning-AI/lightning-diffusion.git
 import lightning as L
-import torch, diffusers
+import diffusers
 from lightning_diffusion import BaseDiffusion, models
 
 
 class ServeDiffusion(BaseDiffusion):
 
     def setup(self, *args, **kwargs):
-        self._model = diffusers.StableDiffusionPipeline.from_pretrained(
+        self.model = diffusers.StableDiffusionPipeline.from_pretrained(
             "CompVis/stable-diffusion-v1-4",
             **models.extras
         ).to(self.device)
 
     def predict(self, data):
-        out = self.model(prompt=data.prompt)
+        out = self.model(prompt=data.prompt, num_inference_steps=23)
         return {"image": self.serialize(out[0][0])}
 
 
@@ -36,12 +36,13 @@ Use the DreamBooth fine-tuning methodology from the paper `Fine Tuning Text-to-I
 ```python
 import lightning as L
 from lightning_diffusion import BaseDiffusion, DreamBoothTuner, models
-import torch, diffusers
+from diffusers import StableDiffusionPipeline
+
 
 class ServeDreamBoothDiffusion(BaseDiffusion):
 
     def setup(self):
-        self._model = diffusers.StableDiffusionPipeline.from_pretrained(
+        self.model = StableDiffusionPipeline.from_pretrained(
             **models.get_kwargs("CompVis/stable-diffusion-v1-4", self.weights_drive),
         ).to(self.device)
 

dreambooth_component.py

@@ -6,7 +6,7 @@
 class ServeDreamBoothDiffusion(BaseDiffusion):
 
     def setup(self):
-        self._model = StableDiffusionPipeline.from_pretrained(
+        self.model = StableDiffusionPipeline.from_pretrained(
             **models.get_kwargs("CompVis/stable-diffusion-v1-4", self.weights_drive),
         ).to(self.device)
 

lightning_diffusion/base_diffusion.py

@@ -87,6 +87,10 @@ def model(self) -> StableDiffusionPipeline:
         assert self._model
         return self._model
 
+    @model.setter
+    def model(self, model) -> None:
+        self._model = model
+
     @property
     def device(self):
         import torch

requirements.txt

@@ -3,7 +3,6 @@ jsonargparse[signatures]
 pyyaml==5.4.0
 protobuf<4.21.0
 lightning_hpo
-lightning
 Pillow>=2.9.0
 numpy>=1.9.2
 diffusers==0.7.2
@@ -12,6 +11,6 @@ deepspeed
 ftfy
 lightning-api-access
 clip@git+https://github.com/openai/CLIP.git
-lightning==1.8.1
+lightning==1.8.3
 redis
 

serve_diffusion_component.py

@@ -1,13 +1,13 @@
 # !pip install lightning_diffusion@git+https://github.com/Lightning-AI/lightning-diffusion.git
 import lightning as L
-import torch, diffusers
+import diffusers
 from lightning_diffusion import BaseDiffusion, models
 
 
 class ServeDiffusion(BaseDiffusion):
 
     def setup(self, *args, **kwargs):
-        self._model = diffusers.StableDiffusionPipeline.from_pretrained(
+        self.model = diffusers.StableDiffusionPipeline.from_pretrained(
             "CompVis/stable-diffusion-v1-4",
             **models.extras
         ).to(self.device)