cr fixes 3

Author: ilanbria

invokeai/app/invocations/bria_decoder.py renamed to invokeai/app/invocations/bria_latents_to_image.py

@@ -9,14 +9,14 @@
 
 
 @invocation(
-    "bria_decoder",
-    title="Decoder - Bria",
+    "bria_latents_to_image",
+    title="Latents to Image - Bria",
     tags=["image", "bria"],
     category="image",
     version="1.0.0",
     classification=Classification.Prototype,
 )
-class BriaDecoderInvocation(BaseInvocation):
+class BriaLatentsToImageInvocation(BaseInvocation):
     """
     Decode Bria latents to an image.
     """

invokeai/backend/bria/pipeline_bria_controlnet.py

@@ -228,8 +228,6 @@ def get_control_start_end(self, control_guidance_start, control_guidance_end):
     def __call__(
         self,
         prompt: Union[str, List[str]] = None,
-        height: Optional[int] = None,
-        width: Optional[int] = None,
         num_inference_steps: int = 30,
         timesteps: List[int] = None,
         guidance_scale: float = 3.5,
@@ -259,10 +257,6 @@ def __call__(
             prompt (`str` or `List[str]`, *optional*):
                 The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
                 instead.
-            height (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
-                The height in pixels of the generated image. This is set to 1024 by default for the best results.
-            width (`int`, *optional*, defaults to self.unet.config.sample_size * self.vae_scale_factor):
-                The width in pixels of the generated image. This is set to 1024 by default for the best results.
             num_inference_steps (`int`, *optional*, defaults to 50):
                 The number of denoising steps. More denoising steps usually lead to a higher quality image at the
                 expense of slower inference.
@@ -323,8 +317,6 @@ def __call__(
             `tuple`. When returning a tuple, the first element is a list with the generated images.
         """
 
-        height = height or self.default_sample_size * self.vae_scale_factor
-        width = width or self.default_sample_size * self.vae_scale_factor
         control_guidance_start, control_guidance_end = self.get_control_start_end(
             control_guidance_start=control_guidance_start, control_guidance_end=control_guidance_end
         )
@@ -335,8 +327,6 @@ def __call__(
         )
         self.check_inputs(
             prompt,
-            height,
-            width,
             negative_prompt=negative_prompt,
             prompt_embeds=prompt_embeds,
             negative_prompt_embeds=negative_prompt_embeds,
@@ -517,7 +507,7 @@ def __call__(
                             order=1,
                             total_steps=num_inference_steps,
                             timestep=int(t),
-                            latents=latents.view(1, 64, 64, 4, 2, 2).permute(0, 3, 1, 4, 2, 5).reshape(1, 4, 128, 128),
+                            latents=self._unpack_latents(latents, height, width, self.vae_scale_factor),
                         ),
                     )