Automated PR - 2026-02-09

packages/ltx-pipelines/src/ltx_pipelines/ic_lora.py

@@ -13,6 +13,7 @@ from ltx_core.model.audio_vae import decode_audio as vae_decode_audio
 from ltx_core.model.upsampler import upsample_video
 from ltx_core.model.video_vae import TilingConfig, VideoEncoder, get_video_chunks_number
 from ltx_core.model.video_vae import decode_video as vae_decode_video
+from ltx_core.quantization import QuantizationPolicy
 from ltx_core.text_encoders.gemma import encode_text
 from ltx_core.types import LatentState, VideoPixelShape
 from ltx_pipelines.utils import ModelLedger
@@ -55,7 +56,7 @@ class ICLoraPipeline:
         gemma_root: str,
         loras: list[LoraPathStrengthAndSDOps],
         device: torch.device = device,
-        fp8transformer: bool = False,
+        quantization: QuantizationPolicy | None = None,
     ):
         self.dtype = torch.bfloat16
         self.stage_1_model_ledger = ModelLedger(
@@ -65,7 +66,7 @@ class ICLoraPipeline:
             spatial_upsampler_path=spatial_upsampler_path,
             gemma_root_path=gemma_root,
             loras=loras,
-            fp8transformer=fp8transformer,
+            quantization=quantization,
         )
         self.stage_2_model_ledger = ModelLedger(
             dtype=self.dtype,
@@ -74,7 +75,7 @@ class ICLoraPipeline:
             spatial_upsampler_path=spatial_upsampler_path,
             gemma_root_path=gemma_root,
             loras=[],
-            fp8transformer=fp8transformer,
+            quantization=quantization,
         )
         self.pipeline_components = PipelineComponents(
             dtype=self.dtype,
@@ -314,7 +315,7 @@ def main() -> None:
         spatial_upsampler_path=args.spatial_upsampler_path,
         gemma_root=args.gemma_root,
         loras=args.lora,
-        fp8transformer=args.enable_fp8,
+        quantization=args.quantization,
     )
     tiling_config = TilingConfig.default()
     video_chunks_number = get_video_chunks_number(args.num_frames, tiling_config)