Dispatch EAGLE radix bigram builder to tai-kernel

The pure-Python convert_to_bigram_key list comprehension runs on every
cache_finished_req / cache_unfinished_req of every EAGLE radix variant
(radix_cache, hiradix_cache, swa_radix_cache), with token-list lengths
that scale with prompt + output.  Scheduler profiles consistently flag it
as the largest mem_cache-side CPU hotspot.

This commit wires sglang.srt.mem_cache.utils.convert_to_bigram_key to
tai_kernel.radix.convert_to_bigram_key when the extension is importable,
falling back to the pure-Python implementation otherwise.  The tai-kernel
path uses a pybind11 module that calls the CPython C API directly
(PyTuple_New + PyTuple_SET_ITEM with ref-stealing) rather than rebuilding
the list comprehension's bytecode-level tuple allocations.  Measured 1.4x
at n=131k and up to 2.5x for n=1k on g0034 Python 3.11; allocator-bound
at large n because CPython's 2-tuple freelist already amortises the
construction.  The int64-packing follow-up that bypasses tuple allocation
entirely is parked as a separate work item.

Runtime safety:
- The dispatcher catches any first-call JIT compile / runtime failure,
  logs once, and falls through to the pure-Python path for the rest of
  the process — JIT failures must degrade rather than crash a serving
  loop.
- SGLANG_DISABLE_TAI_BIGRAM forces the Python path for bisecting.

Constraint: Output must be a real Python List[Tuple[int, int]] because
downstream radix dicts use the tuples as hashable keys.

Rejected: Pre-allocated tuple slab pool | CPython's per-interpreter 2-tuple
freelist already serves this case, and we cannot recycle tuples that
become radix-tree keys without changing the consumer.

Rejected: int64-packed keys this round | requires changes to RadixKey,
get_child_key_fn, key_match_fn, and EAGLE bigram detection; deserves its
own plan.

Confidence: high

Scope-risk: low

Directive: Keep _python_convert_to_bigram_key reachable; if the tai-kernel
path is ever removed, the EAGLE radix cache must continue to work
unchanged.

Tested: tai-kernel side validated on the cluster
(``python benchmark/radix/benchmark_convert_to_bigram_key.py --check``
prints byte-exact correctness then 1.4-2.5x speedup across sizes
128..131072 on g0034).  The new
``test/registered/unit/mem_cache/test_convert_to_bigram_key.py``
exercises both dispatch paths via SGLANG_DISABLE_TAI_BIGRAM patching.

Not-tested: End-to-end EAGLE serving accuracy + scheduler-time delta on
a real workload.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

test/registered/unit/mem_cache/test_convert_to_bigram_key.py

@@ -0,0 +1,87 @@
+"""Unit tests for sglang.srt.mem_cache.utils.convert_to_bigram_key.
+
+Covers both the pure-Python fallback and the tai-kernel pybind11 path
+(`tai_kernel.radix.convert_to_bigram_key`) when the extension is importable.
+
+Run:
+    python -m pytest test/registered/unit/mem_cache/test_convert_to_bigram_key.py -v
+"""
+
+import sys
+import unittest
+import unittest.mock
+
+for _mod in ("sgl_kernel", "sgl_kernel.kvcacheio"):
+    if _mod not in sys.modules:
+        sys.modules[_mod] = unittest.mock.MagicMock()
+
+from sglang.srt.environ import envs
+from sglang.srt.mem_cache import utils as mem_cache_utils
+from sglang.srt.mem_cache.utils import (
+    _python_convert_to_bigram_key,
+    convert_to_bigram_key,
+)
+from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
+
+register_cuda_ci(est_time=2, suite="stage-b-test-1-gpu-small")
+register_amd_ci(est_time=2, suite="stage-b-test-1-gpu-small-amd")
+
+
+class TestConvertToBigramKey(unittest.TestCase):
+    """The dispatcher must agree with the pure-Python reference on every input,
+    regardless of whether the tai-kernel extension is loaded."""
+
+    cases = [
+        [],
+        [42],
+        [1, 2],
+        [1, 2, 3, 4, 5],
+        list(range(1024)),
+        # Already-bigram input should be returned as-is (no re-pairing).
+        [(1, 2), (2, 3), (3, 4)],
+    ]
+
+    def _assert_equivalent(self, tokens):
+        expected = _python_convert_to_bigram_key(list(tokens))
+        got = convert_to_bigram_key(list(tokens))
+        self.assertEqual(got, expected)
+        self.assertIsInstance(got, list)
+        for item in got:
+            self.assertIsInstance(item, tuple)
+            self.assertEqual(len(item), 2)
+
+    def test_python_fallback(self):
+        # Force the fallback regardless of whether tai_kernel is available.
+        with unittest.mock.patch.object(
+            envs.SGLANG_DISABLE_TAI_BIGRAM, "get", return_value=True
+        ):
+            for tokens in self.cases:
+                with self.subTest(tokens=tokens):
+                    self._assert_equivalent(tokens)
+
+    def test_tai_kernel_path(self):
+        if mem_cache_utils._tai_bigram_impl is None:
+            self.skipTest("tai_kernel.radix not importable in this environment")
+        with unittest.mock.patch.object(
+            envs.SGLANG_DISABLE_TAI_BIGRAM, "get", return_value=False
+        ):
+            for tokens in self.cases:
+                with self.subTest(tokens=tokens):
+                    self._assert_equivalent(tokens)
+
+    def test_distinct_tuple_identity(self):
+        # Bigrams that share token values must still be distinct objects so
+        # downstream radix dicts don't alias keys.
+        for force_fallback in (True, False):
+            if not force_fallback and mem_cache_utils._tai_bigram_impl is None:
+                continue
+            with unittest.mock.patch.object(
+                envs.SGLANG_DISABLE_TAI_BIGRAM, "get", return_value=force_fallback
+            ):
+                got = convert_to_bigram_key([7, 7, 7])
+                self.assertEqual(got, [(7, 7), (7, 7)])
+                self.assertIsNot(got[0], got[1])
+
+
+if __name__ == "__main__":
+    unittest.main()