Adding torch accelerator to ddp-tutorial-series example

[dggaytan]

Adding accelerator to ddp tutorials examples

Support for multiple accelerators:

• Updated ddp_setup functions in multigpu.py, multigpu_torchrun.py, and multinode.py to use torch.accelerator for device management. The initialization of process groups now dynamically selects the backend based on the device type, with a fallback to CPU if no accelerator is available.
• Modified Trainer classes in multigpu_torchrun.py and multinode.py to accept a device parameter and use it for model placement and snapshot loading.

Improvements to example execution:

• Added run_example.sh to simplify running tutorial examples with configurable GPU counts and node settings.
• Updated run_distributed_examples.sh to include a new function for running all DDP tutorial series examples.

Dependency updates:

• Increased the minimum PyTorch version requirement in requirements.txt to 2.7 to ensure compatibility with the new torch.accelerator API.

CC: @msaroufim @malfet @dvrogozh

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