add slice op in _is_share_obs_or_fq_op function to fix staticslice op in quantization

[barbecacov]

Summary

Caz xnnpack require the zero point of staticslice are same in inputs/outputs, so add slice op in _is_share_obs_or_fq_op to share quantization parameters

[pytorch-bot]

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❌ 1 New Failure, 4 Unrelated Failures

As of commit 82080f4 with merge base 9591978 ():

NEW FAILURE - The following job has failed:

• Lint / lintrunner / linux-job (gh)
  >>> Lint for backends/xnnpack/quantizer/xnnpack_quantizer_utils.py:

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

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

• pull / unittest / linux / linux-job (gh) (trunk failure)
  devtools/inspector/tests/inspector_utils_test.py::TestInspectorUtils::test_equip_debug_handle_to_export_program_success
• pull / unittest / macos / macos-job (gh) (trunk failure)
  devtools/inspector/tests/inspector_utils_test.py::TestInspectorUtils::test_equip_debug_handle_to_export_program_success
• pull / unittest-editable / linux / linux-job (gh) (trunk failure)
  devtools/inspector/tests/inspector_utils_test.py::TestInspectorUtils::test_equip_debug_handle_to_export_program_success
• pull / unittest-editable / macos / macos-job (gh) (trunk failure)
  devtools/inspector/tests/inspector_utils_test.py::TestInspectorUtils::test_equip_debug_handle_to_export_program_success

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[mcr229]

did you need all of these? I think slice.Tensor should be sufficient right?

[barbecacov]

Sorry, i am not sure. May just torch.ops.aten.slice.Tensor