[TRTLLM-8070][test] add generation logits case for llama3 (#7759)

Signed-off-by: Ivy Zhang <25222398+crazydemo@users.noreply.github.com>

tests/integration/defs/test_e2e.py

@@ -3270,3 +3270,84 @@ def test_multi_nodes_eval(llm_venv, model_path, tp_size, pp_size, ep_size,
     if os.environ.get("SLURM_PROCID", '0') == '0':
         mmlu_accuracy = get_mmlu_accuracy(output)
         assert mmlu_accuracy > mmlu_threshold, f"MMLU accuracy {mmlu_accuracy} is less than threshold {mmlu_threshold}"
+
+
+@pytest.mark.skip_less_device_memory(80000)
+@pytest.mark.parametrize("return_generation_logits", [True, False])
+@pytest.mark.parametrize("model_path", [
+    ("llama-3.1-model/Llama-3.1-8B-Instruct"),
+    pytest.param("llama-3.3-models/Llama-3.3-70B-Instruct",
+                 marks=pytest.mark.skip_less_device(8)),
+])
+def test_llmapi_generation_logits(llm_venv, model_path,
+                                  return_generation_logits):
+    """
+    RCCA: https://nvbugspro.nvidia.com/bug/5501805
+    """
+
+    import asyncio
+
+    from tensorrt_llm import LLM, SamplingParams
+
+    seq_len, max_tokens = 131072, 100000
+    if return_generation_logits:
+        # use short seq_len and max_tokens for testing when return_generation_logits is True
+        seq_len, max_tokens = 1024, 1000
+    tp_size = 8 if "70B" in model_path else 1
+    # Model parameters
+    params = {
+        "cuda_graph_config": {
+            "batch_sizes": [512]
+        },
+        "enable_chunked_prefill": True,
+        "guided_decoding_backend": "xgrammar",
+        "kv_cache_config": {
+            "cross_kv_cache_fraction": None,
+            "enable_block_reuse": False,
+            "free_gpu_memory_fraction": 0.9,
+            "max_attention_window": None
+        },
+        "max_seq_len": seq_len,
+        "tensor_parallel_size": tp_size,
+    }
+
+    # Sampling parameters
+    sampling_params = SamplingParams(
+        max_tokens=max_tokens,
+        return_context_logits=False,
+        return_generation_logits=return_generation_logits,
+    )
+
+    # Test prompt (token IDs)
+    prompt = [
+        128000, 128006, 9125, 128007, 271, 38766, 1303, 33025, 2696, 25, 6790,
+        220, 2366, 18, 198, 15724, 2696, 25, 220, 2545, 17907, 220, 2366, 20,
+        271, 67, 10319, 7422, 389, 128009, 128006, 882, 128007, 271, 3923, 374,
+        701, 836, 30, 128009, 128006, 78191, 128007, 271
+    ]
+
+    async def async_generation_test():
+        """Async generation test function"""
+        model_path_full = f"{llm_models_root()}/{model_path}"
+        llm = LLM(**params, model=model_path_full, tokenizer=model_path_full)
+
+        try:
+            outputs = []
+            async for output in llm.generate_async(
+                    prompt,
+                    sampling_params,
+                    streaming=True,
+            ):
+                outputs.append(output)
+                print(f"Generated: {output}")
+
+            # Verify that we got some output
+            assert len(outputs) > 0, "No output generated"
+            print(f"Successfully generated {len(outputs)} streaming outputs")
+
+        finally:
+            llm.shutdown()
+
+    # Run the async test
+    loop = asyncio.get_event_loop()
+    loop.run_until_complete(async_generation_test())

tests/integration/test_lists/qa/llm_function_nim.txt

@@ -173,3 +173,7 @@ test_e2e.py::test_ptp_quickstart_advanced[Nemotron4_4B-BF16-nemotron/Minitron-4B
 test_e2e.py::test_ptp_quickstart_advanced[Nemotron-H-8B-Nemotron-H-8B-Base-8K]
 test_e2e.py::test_ptp_quickstart_advanced_8gpus[DeepSeek-V3-671B-FP8-DeepSeek-V3-0324]
 test_e2e.py::test_trtllm_benchmark_serving[gpt_oss/gpt-oss-20b]
+test_e2e.py::test_llmapi_generation_logits[llama-3.1-model/Llama-3.1-8B-Instruct-True]
+test_e2e.py::test_llmapi_generation_logits[llama-3.1-model/Llama-3.1-8B-Instruct-False]
+test_e2e.py::test_llmapi_generation_logits[llama-3.3-models/Llama-3.3-70B-Instruct-True]
+test_e2e.py::test_llmapi_generation_logits[llama-3.3-models/Llama-3.3-70B-Instruct-False]