linting error fixes and rebase fix

Author: apbose

py/torch_tensorrt/dynamo/_compiler.py

@@ -518,11 +518,8 @@ def compile(
         enable_weight_streaming (bool): Enable weight streaming.
         tiling_optimization_level (str): The optimization level of tiling strategies. A higher level allows TensorRT to spend more time searching for better tiling strategy. We currently support ["none", "fast", "moderate", "full"].
         l2_limit_for_tiling (int): The target L2 cache usage limit (in bytes) for tiling optimization (default is -1 which means no limit).
-<<<<<<< HEAD
         offload_module_to_cpu (bool): Offload the module to CPU. This is useful when we need to minimize GPU memory usage.
-=======
         use_distributed_mode_trace (bool):  Using aot_autograd to trace the graph. This is enabled when DTensors or distributed tensors are present in distributed model
->>>>>>> c3b62d239 (TensorRT-LLM import fix and aot_joint_export specify as explicit setting in dynamo.compile)
         **kwargs: Any,
     Returns:
         torch.fx.GraphModule: Compiled FX Module, when run it will execute via TensorRT

py/torch_tensorrt/dynamo/conversion/converter_utils.py

@@ -1048,4 +1048,3 @@ def promote_trt_tensors_to_same_dtype(
     rhs_cast = cast_trt_tensor(ctx, rhs, promoted_dtype, f"{name_prefix}rhs_cast")
 
     return lhs_cast, rhs_cast
-