Fix scalar parameter byte-view broadcasts (#8642)
Fixes #8639.
PyTorch rejects reinterpreting a zero-dimensional tensor as `uint8` when
the element sizes differ. DeepSpeed uses that byte view in model and
ZeRO parameter broadcasts, so a scalar parameter fails during
initialization. Unsqueezing only scalar tensors creates a
one-dimensional view of the same storage before the byte
reinterpretation; non-scalar tensors keep the existing path.
Tested with a two-rank CPU/Gloo regression on Python 3.12 and PyTorch
2.12.1: ZeRO stages 0 and 3 both pass with this change. The same stage-0
test fails on the unmodified base with the reported `self.dim() cannot
be 0` error. Repository formatting/static hooks, `py_compile`, and `git
diff --check` pass. A newer Linux flake8 reports three warnings already
present on the base; excluding only those unchanged warnings leaves no
lint findings in the changed files. GPU distributed execution was not
tested.
Prepared with AI assistance; I reviewed the diff and ran the tests
above.
Signed-off-by: Xucheng Zhou <aden1350@outlook.com>
