build(deps): update torch requirement from <2.3 to <2.8

[dependabot]

Updates the requirements on torch to permit the latest version.

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Sourced from torch's releases.

PyTorch 2.7.0 Release Notes

• Highlights
• Tracked Regressions
• Backwards Incompatible Changes
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Highlights

... (truncated)

Changelog

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Releasing PyTorch

• Release Compatibility Matrix
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Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

... (truncated)

Commits

• 1341794 Gracefully handle optree less than minimum version, part 2 (#151323)
• 0739127 Gracefully handle optree less than minimum version (#150977)
• 0c236f3 Update triton wheel build, setuptools pin (#150953)
• c7ff78d Fix inplacing with multiple, fused uses (#150892)
• 894909a Revert "[CUDA] Only use vec128 if CUDA version is newer than 12.8" (#150855)
• ef2b139 [Manylinux 2.28] Correct Linux aarch64 cuda binaries wheel name (#150820)
• 3f236f1 [CUDA] Only use vec128 if CUDA version is newer than 12.8 (#150818)
• 35f1e76 Reland of "[ROCm] change preferred blas lib defaults (#150249)"" (#150707)
• a6321d6 Revert "Dont exclude constant_pad_nd in prologue fusion" (#150699)
• 1cc51c6 [CUDA][avgpool2d] Fix backward launch bounds again for sm100, sm120 (#150...
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[Borda]

need to be fixed:

Hint: make sure your test modules/packages have valid Python names.
Traceback:
/opt/conda/lib/python3.10/importlib/__init__.py:126: in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
test_strategy.py:8: in <module>
    import hivemind
/opt/conda/lib/python3.10/site-packages/hivemind/__init__.py:12: in <module>
    from hivemind.optim import GradScaler, Optimizer, TrainingAverager
/opt/conda/lib/python3.10/site-packages/hivemind/optim/__init__.py:1: in <module>
    from hivemind.optim.grad_scaler import GradScaler, HivemindGradScaler
/opt/conda/lib/python3.10/site-packages/hivemind/optim/grad_scaler.py:8: in <module>
    from torch.cuda.amp.grad_scaler import OptState, _refresh_per_optimizer_state
E   ImportError: cannot import name '_refresh_per_optimizer_state' from 'torch.cuda.amp.grad_scaler' (/opt/conda/lib/python3.10/site-packages/torch/cuda/amp/grad_scaler.py)

[Borda]

reported in learning-at-home/hivemind#643

[Borda]

hitting (also not sure why it install all CUDA packages since I requested Torch CPU version):

src/lightning_hivemind/strategy.py:188: in __init__
    self.dht = hivemind.DHT(
/opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/site-packages/hivemind/dht/dht.py:87: in __init__
    self.run_in_background(await_ready=await_ready)
/opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/site-packages/hivemind/dht/dht.py:148: in run_in_background
    self.wait_until_ready(timeout)
/opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/site-packages/hivemind/dht/dht.py:151: in wait_until_ready
    self._ready.result(timeout=timeout)
/opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/site-packages/hivemind/utils/mpfuture.py:254: in result
    return super().result(timeout)
/opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/concurrent/futures/_base.py:458: in result
    return self.__get_result()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
self = None
    def __get_result(self):
        if self._exception:
            try:
>               raise self._exception
E               hivemind.p2p.p2p_daemon_bindings.utils.P2PDaemonError: Daemon failed to start: /opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/site-packages/hivemind/hivemind_cli/p2pd: 2: Syntax error: "(" unexpected
/opt/hostedtoolcache/Python/3.10.17/x64/lib/python3.10/concurrent/futures/_base.py:403: P2PDaemonError

and reporting it in learning-at-home/hivemind#655

[dependabot]

A newer version of torch exists, but since this PR has been edited by someone other than Dependabot I haven't updated it. You'll get a PR for the updated version as normal once this PR is merged.