Add minimal nn.functional.log_softmax support for NestedTensor

[alanhdu]

This only works for the jagged layout and for the non-batch and non-jagged dimensions.

I did this mostly by copy-pasting from the existing softmax implementation, but it seems fairly straightforward and I think it should work.

[pytorch-bot]

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✅ You can merge normally! (1 Unrelated Failure)

As of commit 613c86e with merge base aeb5321 ():

UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:

• pull / linux-jammy-py3_9-clang9-xla / test (xla, 1, 1, lf.linux.12xlarge, unstable) (gh) (#158876)
  /var/lib/jenkins/workspace/xla/torch_xla/csrc/runtime/BUILD:476:14: Compiling torch_xla/csrc/runtime/xla_util_test.cpp failed: (Exit 1): gcc failed: error executing CppCompile command (from target //torch_xla/csrc/runtime:xla_util_test) /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 229 arguments skipped)

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[jbschlosser]

Looks fine AFAICT, thanks for the contribution :)

[jbschlosser]

@pytorchbot merge

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