[executorch] Remove obsolete VGF slice xfail

[JacobSzwejbka]

The VGF converter 0.10 upgrade makes the arange_fp32_2d_step4 slice case pass. Remove its stale strict xfail so the successful result is not reported as an XPASS failure.

Test plan: buck test @fbcode//mode/dev fbcode//executorch/backends/arm/test:slice -- --exact "fbcode//executorch/backends/arm/test:slice - test_slice.py::test_slice_tensor_vgf_no_quant_step[arange_fp32_2d_step4]"

Local OSS test was not run because pytest is not installed in this checkout environment.

This PR was authored with Codex.

cc @digantdesai @freddan80 @per @zingo @oscarandersson8218 @mansnils @Sebastian-Larsson @robell @rascani

[pytorch-bot]

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❌ 2 New Failures, 1 Unclassified Failure

As of commit a208817 with merge base 2287a8b ():

NEW FAILURES - The following jobs have failed:

• Test Vulkan Backend / test-vulkan / test-backend-linux (vulkan, models) / linux-job (gh)
  ##[error]fatal: unable to access 'https://github.com/pytorch/ao.git/': Error in the HTTP2 framing layer
• trunk / test-arm-backend-vkml (test_pytest_ops_vkml) / linux-job (gh)
  RuntimeError: Command docker exec -t fa50725ff8fa2bcd0f942e9fa7b7a6e963cb854a5811ca3b16200055545d4b2c /exec failed with exit code 1

UNCLASSIFIED FAILURE - DrCI could not classify the following job because the workflow did not run on the merge base. The failure may be pre-existing on trunk or introduced by this PR:

• trunk / test-multimodal-macos (gemma3-4b) / macos-job (gh) (this job did not run on the merge base, so DrCI cannot tell whether the failure is pre-existing)
  pytorch_tokenizers

This comment was automatically generated by Dr. CI and updates every 15 minutes.

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[zingo]

Hi this seem to still fail here in the github runner could it be another test, or maybe I missed something

trunk / test-arm-backend-vkml (test_pytest_ops_vkml) / linux-job (push)

FAILED backends/arm/test/ops/test_slice.py::test_slice_tensor_vgf_no_quant_step[arange_fp32_2d_step4] - AssertionError: Output 0 does not match reference output.
	Given atol: 0.001, rtol: 0.001.
	Output tensor shape: torch.Size([4, 3]), dtype: torch.float32
	Difference: max: 0.0, abs: 7.0, mean abs error: 1.6666666666666667.
	-- Model vs. Reference --
	 Numel: 12, 12
	Median: 16.0, 19.0
	  Mean: 18.333333333333332, 20.0
	   Max: 39.0, 39.0
	   Min: 1.0, 1.0
= 1 failed, 3781 passed, 45 skipped, 23 xfailed, 7 xpassed, 15152 warnings, 2 rerun in 4086.70s (1:08:06) =