Upload ltx_server.py

api/ltx_server.py

@@ -71,9 +71,9 @@ def _query_gpu_processes_via_nvidiasmi(device_index: int) -> List[Dict]:
         parts = [p.strip() for p in line.split(",")]
         if len(parts) >= 3:
             try:
-                pid = int(parts[^21_0])
-                name = parts[^21_1]
-                used_mb = int(parts[^21_2])
+                pid = int(parts[0])
+                name = parts[1]
+                used_mb = int(parts[2])
                 user = "unknown"
                 try:
                     import psutil
@@ -389,7 +389,7 @@ class VideoService:
                                  padding_values, progress_callback=None):
         print(f"[DEBUG] Decodificando latentes → vídeo: {output_video_path}")
         pad_left, pad_right, pad_top, pad_bottom = padding_values
-        T = latents.shape[^21_2]
+        T = latents.shape[2]
         print(f"[DEBUG] Latentes shape={tuple(latents.shape)} frames={T}")
         start = time.perf_counter()
         with imageio.get_writer(output_video_path, fps=frame_rate, codec="libx264", quality=8) as writer:
@@ -407,12 +407,12 @@ class VideoService:
                             print(f"[DEBUG] vae.decode frame={i}")
                     else:
                         raise RuntimeError("Pipeline não possui decode_latents/vae.decode.")
-                pixel_chw = pixel_bchw[^21_0]
+                pixel_chw = pixel_bchw[0]
                 if pixel_chw.min() < 0:
                     pixel_chw = (pixel_chw.clamp(-1, 1) + 1.0) / 2.0
                 else:
                     pixel_chw = pixel_chw.clamp(0, 1)
-                H, W = pixel_chw.shape[^21_1], pixel_chw.shape[^21_2]
+                H, W = pixel_chw.shape[2]
                 h_end = H - pad_bottom if pad_bottom > 0 else H
                 w_end = W - pad_right if pad_right > 0 else W
                 pixel_chw = pixel_chw[:, pad_top:h_end, pad_left:w_end]
@@ -632,7 +632,7 @@ class VideoService:
             else:
                 print("[DEBUG] Escrevendo vídeo a partir de pixels (sem latentes)...")
                 with imageio.get_writer(output_video_path, fps=call_kwargs["frame_rate"], codec="libx264", quality=8) as writer:
-                    T = result_tensor.shape[^21_2]
+                    T = result_tensor.shape[2]
                     for i in range(T):
                         frame_chw = result_tensor[0, :, i]
                         frame_hwc_u8 = (frame_chw.permute(1, 2, 0)