infrastructure-conditional-import-g-using-transformers-4-52-2-with-pytorch-versions-be-1a93b8d9

THEN Fix the conditional import in `tensor_parallel.py` to either import 'Replicate' unconditionally with a version guard only at usage points, or define a placeholder when torch < 2.5. Ensure all references to 'Replicate' are protected behind the same conditional logic to prevent runtime errors on older PyTorch installations.

# Instead of:
if is_torch_greater_or_equal('2.5') and _torch_distributed_available:
    from torch.distributed.tensor import DTensor, Placement, Replicate, Shard
# Ensure Replicate is defined for lower versions, e.g.:
if is_torch_greater_or_equal('2.5') and _torch_distributed_available:
    from torch.distributed.tensor import DTensor, Placement, Replicate, Shard
else:
    from torch.distributed.tensor import DTensor, Placement, Shard
    Replicate = lambda: None  # or appropriate fallback