diff --git a/ltx_video/pipelines/pipeline_ltx_video.py b/ltx_video/pipelines/pipeline_ltx_video.py
index b69c443..8bb6d27 100644
--- a/ltx_video/pipelines/pipeline_ltx_video.py
+++ b/ltx_video/pipelines/pipeline_ltx_video.py
@@ -1412,7 +1412,7 @@ class LTXVideoPipeline(DiffusionPipeline):
         sigmoid_term = torch.sigmoid(4.0 * scale_factor * (abs_latents - 1.0))
         # DeepBeepMeep special touch to allow a smooth transition with tone mapping
         if start > 0:
-            gradient_tensor = torch.linspace(0, 1, latents.shape[2])
+            gradient_tensor = torch.linspace(0, 1, latents.shape[2],dtype= sigmoid_term.dtype, device=sigmoid_term.device)
             gradient_tensor = gradient_tensor ** 0.5
             gradient_tensor = gradient_tensor[ None, None, :, None, None ]
             sigmoid_term *= gradient_tensor
diff --git a/wgp.py b/wgp.py
index ccb1a0f..eef96a0 100644
--- a/wgp.py
+++ b/wgp.py
@@ -4468,7 +4468,7 @@ def generate_video(
                 status_info = "Extracting " + processes_names[preprocess_type]
                 send_cmd("progress", [0, get_latest_status(state, status_info)])
                 # start one frame ealier to faciliate latents merging later
-                src_video, _ = preprocess_video_with_mask(video_guide, video_mask, height=image_size[0], width = image_size[1], max_frames= len(keep_frames_parsed) + (0 if guide_start_frame == 0 else 1), start_frame = guide_start_frame - (0 if guide_start_frame == 0 else 1), fit_canvas = sample_fit_canvas, target_fps = fps,  process_type = preprocess_type, inpaint_color = 0, proc_no =1, negate_mask = "N" in video_prompt_type, process_outside_mask = "inpaint" if "X" in video_prompt_type else "identity" )
+                src_video, _ = preprocess_video_with_mask(video_guide, video_mask, height=image_size[0], width = image_size[1], max_frames= len(keep_frames_parsed) + (0 if guide_start_frame == 0 else 1), start_frame = guide_start_frame - (0 if guide_start_frame == 0 else 1), fit_canvas = sample_fit_canvas, target_fps = fps,  process_type = preprocess_type, inpaint_color = 0, proc_no =1, negate_mask = "N" in video_prompt_type, process_outside_mask = "inpaint" if "X" in video_prompt_type else "identity", block_size =32 )
                 if src_video !=  None:
                     src_video = src_video[ :(len(src_video)-1)// latent_size * latent_size +1 ]
                     refresh_preview["video_guide"] = Image.fromarray(src_video[0].cpu().numpy())