From e5abb1b9bc27cfe7f05562651aa23f14bba3d5e9 Mon Sep 17 00:00:00 2001
From: DeepBeepMeep <deepbeepmeep@yahoo.com>
Date: Thu, 4 Sep 2025 01:10:42 +0200
Subject: [PATCH] fixed pytorch compilation

---
 models/wan/any2video.py | 7 ++++---
 requirements.txt        | 2 +-
 wgp.py                  | 6 +++---
 3 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/models/wan/any2video.py b/models/wan/any2video.py
index 8eb2ffe..e7d54ef 100644
--- a/models/wan/any2video.py
+++ b/models/wan/any2video.py
@@ -454,7 +454,8 @@ class WanAny2V:
             timesteps.append(0.)
             timesteps = [torch.tensor([t], device=self.device) for t in timesteps]
             if self.use_timestep_transform:
-                timesteps = [timestep_transform(t, shift=shift, num_timesteps=self.num_timesteps) for t in timesteps][:-1]    
+                timesteps = [timestep_transform(t, shift=shift, num_timesteps=self.num_timesteps) for t in timesteps][:-1]
+            timesteps = torch.tensor(timesteps)
             sample_scheduler = None                  
         elif sample_solver == 'causvid':
             sample_scheduler = FlowMatchScheduler(num_inference_steps=sampling_steps, shift=shift, sigma_min=0, extra_one_step=True)
@@ -1016,8 +1017,8 @@ class WanAny2V:
             
             if sample_solver == "euler":
                 dt = timesteps[i] if i == len(timesteps)-1 else (timesteps[i] - timesteps[i + 1])
-                dt = dt / self.num_timesteps
-                latents = latents - noise_pred * dt[:, None, None, None, None]
+                dt = dt.item() / self.num_timesteps
+                latents = latents - noise_pred * dt
             else:
                 latents = sample_scheduler.step(
                     noise_pred[:, :, :target_shape[1]],
diff --git a/requirements.txt b/requirements.txt
index cdc21ad..0ae0ab3 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -44,7 +44,7 @@ pydantic==2.10.6
 # Math & modeling
 torchdiffeq>=0.2.5
 tensordict>=0.6.1
-mmgp==3.5.12
+mmgp==3.6.0
 peft==0.15.0
 matplotlib
 
diff --git a/wgp.py b/wgp.py
index a3cc510..c57cc48 100644
--- a/wgp.py
+++ b/wgp.py
@@ -59,8 +59,8 @@ global_queue_ref = []
 AUTOSAVE_FILENAME = "queue.zip"
 PROMPT_VARS_MAX = 10
 
-target_mmgp_version = "3.5.12"
-WanGP_version = "8.33"
+target_mmgp_version = "3.6.0"
+WanGP_version = "8.34"
 settings_version = 2.29
 max_source_video_frames = 3000
 prompt_enhancer_image_caption_model, prompt_enhancer_image_caption_processor, prompt_enhancer_llm_model, prompt_enhancer_llm_tokenizer = None, None, None, None
@@ -8509,7 +8509,7 @@ def generate_configuration_tab(state, blocks, header, model_family, model_choice
                         ("Off", "" ),
                     ],
                     value= compile,
-                    label="Compile Transformer (up to 50% faster and 30% more frames but requires Linux / WSL and Flash or Sage attention)",
+                    label="Compile Transformer : up to 10-20% faster, useful only if multiple gens at same frames no / resolution",
                     interactive= not lock_ui_compile
                 )