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Upgrading
torchto2.8.0while keepingapache-beamat2.49.0introduces a high risk of compatibility issues.\n\n1. Breaking Change intorch.load: Starting with PyTorch 2.4,torch.loaddefaults toweights_only=True. The version ofapache-beamused here (2.49.0) does not expose theweights_onlyparameter inPytorchModelHandlerTensor, which may cause the pipeline to fail if the model's state dict contains non-tensor objects.\n2. Dependency Conflicts: There is a significant age gap between these versions, which often leads to conflicts in shared dependencies likenumpyorprotobuf.\n\nTo ensure stability, it is strongly recommended to upgradeapache-beamto a more recent version (e.g.,2.60.0or later) andtransformersto a version compatible with PyTorch 2.8.0.