Add zero-copy TensorRT PyTorch runtime and AniGen hybrid loader

runtime/trt_torch.py

@@ -33,7 +33,7 @@ class TorchTensorRTEngine:
         return outs
 
 class DinoTRT(torch.nn.Module):
-    def __init__(self, engine_path): super().__init__(); self.engine=TorchTensorRTEngine(engine_path)
+    def __init__(self, engine_path): super().__init__(); self.engine=TorchTensorRTEngine(engine_path); self.device=torch.device('cuda')
     def forward(self, pixel_values, is_training=True):
         out=self.engine.run({'pixel_values':pixel_values})['x_prenorm']; return {'x_prenorm':out}
     def to(self,*a,**k): return self
@@ -41,7 +41,7 @@ class DinoTRT(torch.nn.Module):
     def eval(self): return self
 
 class DsineTRT(torch.nn.Module):
-    def __init__(self, engine_path): super().__init__(); self.engine=TorchTensorRTEngine(engine_path)
+    def __init__(self, engine_path): super().__init__(); self.engine=TorchTensorRTEngine(engine_path); self.device=torch.device('cuda')
     def forward(self, image, intrins):
         out=self.engine.run({'image':image,'intrins':intrins})['normal']; return [out]
     def to(self,*a,**k): return self