Fix stale TopK availability checks

[vorapolsiloai]

Summary

• remove stale references to the deleted aiter.ops.flydsl.utils module
• restore FlyDSL decode TopK dispatch on supported gfx942/gfx950 systems
• fix op_tests/test_topk_per_row.py collection in the standard-test suite

Context

#5116 removed the optional FlyDSL availability helper and made FlyDSL imports unconditional. #5011 landed later with two references to the removed helper:

• the test imports it eagerly and fails collection with ModuleNotFoundError
• the runtime dispatch catches the same import failure and silently disables the FlyDSL TopK path

This was observed in the MI35X standard-test failure on #4761. The failure occurs before any GPU kernel executes.

Test plan

• PYTHONPYCACHEPREFIX=/tmp/aiter-topk-fix-pycache python3 -m py_compile aiter/ops/topk.py op_tests/test_topk_per_row.py
• git diff --check
• verify no Python references to aiter.ops.flydsl.utils or is_flydsl_available remain
• upstream CI

Made with Cursor

[github-actions]

🏷️ CI Guide

Runs automatically on every PR:

• ✅ Pre-checks (submodule verification, code formatting)
• ✅ Aiter op tests (gfx942 + gfx950)
• ✅ Triton tests on MI35X (only when aiter/ops/triton/** or related paths are changed)

Extended tests (opt-in via labels):

Label	Tests
ci:gfx1250-ffm-triton	Run the five-shard gfx1250 FFM Triton test suite
ci:triton-300x	Run an additional Triton test job on MI300X in PRs; main branch always runs both MI35X and MI300X
multigpu	Aiter multi-GPU tests on the 8-GPU runner
ci:sglang	SGLang integration tests: DeepSeek-R1-MXFP4 accuracy, Qwen 3.5 accuracy
ci:atom	ATOM benchmark: DeepSeek-R1-0528, GPT-OSS-120B
ci:atom_full	ATOM accuracy suite for PR and main models from ATOM models_accuracy.json
ci:vllm	vLLM benchmark: GPT-OSS-120B, DeepSeek-R1-0528, Kimi-K2.5
ci:all	All standard extended tests (excludes ci:atom_full)

Only add ci:atom_full for FlyDSL or Triton upgrades.
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