Match Modal exactly: upsampler 1.0 + inference_mode workaround

app.py

@@ -47,6 +47,10 @@ import torch
 torch._dynamo.config.suppress_errors = True
 torch._dynamo.config.disable = True
 
+# Critical workaround: Replace inference_mode with no_grad
+# Avoids "inference tensor" failures in spatial upsampler and VAE decoder
+torch.inference_mode = torch.no_grad
+
 import spaces
 import gradio as gr
 import numpy as np
@@ -113,7 +117,7 @@ print("=" * 80)
 
 checkpoint_path = hf_hub_download(repo_id=CHECKPOINT_REPO, filename="sulphur_dev_bf16.safetensors")
 distilled_lora_path = hf_hub_download(repo_id=DISTILL_LORA_REPO, filename="distill_loras/ltx-2.3-22b-distilled-lora-1.1_fro90_ceil72_condsafe.safetensors")
-spatial_upsampler_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename="ltx-2.3-spatial-upscaler-x2-1.1.safetensors")
+spatial_upsampler_path = hf_hub_download(repo_id=LTX_MODEL_REPO, filename="ltx-2.3-spatial-upscaler-x2-1.0.safetensors")
 gemma_root = snapshot_download(repo_id=GEMMA_REPO)
 
 print(f"Checkpoint: {checkpoint_path}")