[fp8 blockwise] wrap triton quantization kernels in custom ops for torch.compile compatibility

[danielvegamyhre]

Stacked PRs:

• ->[fp8 blockwise] wrap triton quantization kernels in custom ops for torch.compile compatibility #2829
• [fp8 blockwise] load 2d chunks for groupwise quant to enable coalesced gmem accesses #2827
• use shared bench + profile utils in blockwise fwd bwd bench script #2826
• integrate torch._scaled_mm into Float8BlockwiseLinear and add bench script #2785

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[fp8 blockwise] wrap triton quantization kernels in custom ops for torch.compile compatibility

[pytorch-bot]

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🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2829

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✅ You can merge normally! (3 Unrelated Failures)

As of commit a75457b with merge base 253d65a ():

BROKEN TRUNK - The following jobs failed but were present on the merge base:

👉 Rebase onto the `viable/strict` branch to avoid these failures

• Run 1xH100 Tests / test (H100, linux.aws.h100, --pre torch torchvision torchaudio fbgemm-gpu-genai --index-url https... / linux-job (gh) (trunk failure)
  test/integration/test_integration.py::TestAutoQuant::test_autoquant_hp_float
• Run 1xL4 Tests / test (SM-89, linux.g6.4xlarge.experimental.nvidia.gpu, --pre torch --index-url https://download.p... / linux-job (gh) (trunk failure)
  test/integration/test_integration.py::TestAutoQuant::test_autoquant_hp_float
• Run Regression Tests / test-nightly (CUDA Nightly, linux.g5.12xlarge.nvidia.gpu, --pre torch --index-url https://downloa... / linux-job (gh) (trunk failure)
  test/integration/test_integration.py::TestAutoQuant::test_autoquant_hp_float

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