[Spec] Add trtllm_mha support for Gemma 4 MTP draft attention backend (#25545)

Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>

test/registered/attention/unittests/dense/test_trtllm_mha.py

@@ -36,7 +36,7 @@ register_cuda_ci(est_time=20, stage="base-b", runner_config="1-gpu-large")
 @unittest.skipIf(
     not torch.cuda.is_available()
     or not is_flashinfer_available()
-    or not (is_sm90_supported() or is_sm120_supported()),
+    or not (is_sm90_supported() or is_sm100_supported() or is_sm120_supported()),
     "CUDA + FlashInfer TRT-LLM MHA decode support are required",
 )
 class TestTRTLLMMHADenseAttentionBackendCorrectness(CustomTestCase):
@@ -149,8 +149,7 @@ class TestTRTLLMMHADenseAttentionBackendCorrectness(CustomTestCase):
         ),
     )
 
-    # Frozen-KV MTP draft CG runner (chain, topk=1) — records the fused
-    # in-graph metadata rebuild inside FrozenKVMTPCudaGraphRunner's capture.
+    # Frozen-KV MTP draft CG runner (chain, topk=1).
     FROZEN_KV_MTP_RUNNER_CASES = (
         DenseAttentionCase(
             name="runner_frozen_kv_mtp_decode_trtllm_mha_cuda_graph",