fix(app): step callbacks for SD, FLUX, MultiDiffusion

Each of these was a bit off:
- The SD callback started at `-1` and ended at `i`. Combined w/ the weird math on the previous `calc_percentage` util, this caused the progress bar to never finish.
- The MultiDiffusion callback had the same problems as SD.
- The FLUX callback didn't emit a pre-denoising step 0 image. It also reported total_steps as 1 higher than the actual step count.

Each of these now emit the expected events to the frontend:
- The initial latents at 0%
- Progress at each step, ending at 100%

invokeai/backend/flux/denoise.py

@@ -22,7 +22,18 @@ def denoise(
     guidance: float,
     traj_guidance_extension: TrajectoryGuidanceExtension | None,  # noqa: F821
 ):
-    step = 0
+    # step 0 is the initial state
+    total_steps = len(timesteps) - 1
+    step_callback(
+        PipelineIntermediateState(
+            step=0,
+            order=1,
+            total_steps=total_steps,
+            timestep=int(timesteps[0]),
+            latents=img,
+        ),
+    )
+    step = 1
     # guidance_vec is ignored for schnell.
     guidance_vec = torch.full((img.shape[0],), guidance, device=img.device, dtype=img.dtype)
     for t_curr, t_prev in tqdm(list(zip(timesteps[:-1], timesteps[1:], strict=True))):
@@ -49,7 +60,7 @@ def denoise(
             PipelineIntermediateState(
                 step=step,
                 order=1,
-                total_steps=len(timesteps),
+                total_steps=total_steps,
                 timestep=int(t_curr),
                 latents=preview_img,
             ),

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -366,7 +366,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         with attn_ctx:
             callback(
                 PipelineIntermediateState(
-                    step=-1,
+                    step=0,  # initial latents
                     order=self.scheduler.order,
                     total_steps=len(timesteps),
                     timestep=self.scheduler.config.num_train_timesteps,
@@ -395,7 +395,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
 
                 callback(
                     PipelineIntermediateState(
-                        step=i,
+                        step=i + 1,  # final latents
                         order=self.scheduler.order,
                         total_steps=len(timesteps),
                         timestep=int(t),

invokeai/backend/stable_diffusion/multi_diffusion_pipeline.py

@@ -81,7 +81,7 @@ class MultiDiffusionPipeline(StableDiffusionGeneratorPipeline):
 
         callback(
             PipelineIntermediateState(
-                step=-1,
+                step=0,
                 order=self.scheduler.order,
                 total_steps=len(timesteps),
                 timestep=self.scheduler.config.num_train_timesteps,
@@ -182,7 +182,7 @@ class MultiDiffusionPipeline(StableDiffusionGeneratorPipeline):
 
             callback(
                 PipelineIntermediateState(
-                    step=i,
+                    step=i + 1,
                     order=self.scheduler.order,
                     total_steps=len(timesteps),
                     timestep=int(t),