Add Eagle and Eagle3 support to Transformers modeling backend (#30340)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

tests/v1/e2e/test_spec_decode.py

@@ -280,9 +280,20 @@ def test_speculators_model_integration(
 
 
 @pytest.mark.parametrize(
-    ["model_setup", "mm_enabled", "enable_chunked_prefill"],
+    ["model_setup", "mm_enabled", "enable_chunked_prefill", "model_impl"],
     [
-        (("eagle3", "Qwen/Qwen3-8B", "AngelSlim/Qwen3-8B_eagle3", 1), False, False),
+        (
+            ("eagle3", "Qwen/Qwen3-8B", "AngelSlim/Qwen3-8B_eagle3", 1),
+            False,
+            False,
+            "auto",
+        ),
+        (
+            ("eagle3", "Qwen/Qwen3-8B", "AngelSlim/Qwen3-8B_eagle3", 1),
+            False,
+            False,
+            "transformers",
+        ),
         pytest.param(
             (
                 "eagle3",
@@ -292,6 +303,7 @@ def test_speculators_model_integration(
             ),
             False,
             False,
+            "auto",
             marks=pytest.mark.skip(
                 reason="architecture of its eagle3 is LlamaForCausalLMEagle3"
             ),
@@ -305,6 +317,7 @@ def test_speculators_model_integration(
             ),
             False,
             False,
+            "auto",
             marks=pytest.mark.skip(
                 reason="Skipping due to its head_dim not being a a multiple of 32"
             ),
@@ -318,6 +331,7 @@ def test_speculators_model_integration(
             ),
             False,
             True,
+            "auto",
             marks=large_gpu_mark(min_gb=40),
         ),  # works on 4x H100
         (
@@ -329,6 +343,7 @@ def test_speculators_model_integration(
             ),
             False,
             False,
+            "auto",
         ),
         pytest.param(
             (
@@ -339,6 +354,7 @@ def test_speculators_model_integration(
             ),
             False,
             False,
+            "auto",
             marks=large_gpu_mark(min_gb=80),
         ),  # works on 4x H100
         pytest.param(
@@ -350,6 +366,7 @@ def test_speculators_model_integration(
             ),
             True,
             True,
+            "auto",
             marks=large_gpu_mark(min_gb=80),
         ),  # works on 4x H100
         (
@@ -361,10 +378,12 @@ def test_speculators_model_integration(
             ),
             False,
             False,
+            "auto",
         ),
     ],
     ids=[
         "qwen3_eagle3",
+        "qwen3_eagle3-transformers",
         "qwen3_vl_eagle3",
         "qwen2_5_vl_eagle3",
         "llama3_eagle",
@@ -381,6 +400,7 @@ def test_eagle_correctness(
     model_setup: tuple[str, str, str, int],
     mm_enabled: bool,
     enable_chunked_prefill: bool,
+    model_impl: str,
     attn_backend: str,
 ):
     if attn_backend == "TREE_ATTN":
@@ -389,6 +409,17 @@ def test_eagle_correctness(
             "TREE_ATTN is flaky in the test disable for now until it can be "
             "resolved (see https://github.com/vllm-project/vllm/issues/22922)"
         )
+    if model_impl == "transformers":
+        import transformers
+        from packaging.version import Version
+
+        installed = Version(transformers.__version__)
+        required = Version("5.0.0.dev")
+        if installed < required:
+            pytest.skip(
+                "Eagle3 with the Transformers modeling backend requires "
+                f"transformers>={required}, but got {installed}"
+            )
 
     # Generate test prompts inside the function instead of using fixture
     test_prompts = get_test_prompts(mm_enabled)
@@ -448,6 +479,7 @@ def test_eagle_correctness(
             max_model_len=max_model_len,
             max_num_batched_tokens=max_num_batched_tokens,
             enable_chunked_prefill=enable_chunked_prefill,
+            model_impl=model_impl,
         )
         spec_outputs = spec_llm.chat(test_prompts, sampling_config)
         matches = 0