[Quantization] Supported w8a8 int8 quantized Gemma3 and Qwen-VL models (#8619)

Co-authored-by: ronnie_zheng <zl19940307@163.com>

python/sglang/srt/layers/quantization/w8a8_int8.py

@@ -255,17 +255,23 @@ class W8A8Int8Config(QuantizationConfig):
 
         if _is_npu:
             if isinstance(layer, LinearBase):
+                key = "model"
+                if "vision_model" in prefix:
+                    key = "vision_model"
+                elif "visual" in prefix:
+                    key = "visual"
+                packed_modules_mapping_subset = self.packed_modules_mapping.get(key, {})
                 prefix_in_quant_config = prefix
                 proj_name = prefix.split(".")[-1]
-                if proj_name in self.packed_modules_mapping:
+                if proj_name in packed_modules_mapping_subset:
                     prefix_in_quant_config = prefix.replace(
-                        proj_name, self.packed_modules_mapping[proj_name][0]
+                        proj_name, packed_modules_mapping_subset[proj_name][0]
                     )
                 self.is_dynamic = (
                     self.quant_description[prefix_in_quant_config + ".weight"]
                     == "W8A8_DYNAMIC"
                 )
-                if self.is_layer_skipped(prefix, self.packed_modules_mapping):
+                if self.is_layer_skipped(prefix, packed_modules_mapping_subset):
                     return UnquantizedLinearMethod()
                 return (
                     NPU_W8A8DynamicLinearMethod(self)

python/sglang/srt/model_loader/loader.py

@@ -162,12 +162,24 @@ def _initialize_model(
     model_class, _ = get_model_architecture(model_config)
     packed_modules_mapping = getattr(model_class, "packed_modules_mapping", {})
     if _is_npu:
-        packed_modules_mapping["fused_qkv_a_proj_with_mqa"] = [
+        packed_modules_mapping.update(
+            {
+                "visual": {"qkv_proj": ["qkv"]},
+                "vision_model": {
+                    "qkv_proj": ["q_proj", "k_proj", "v_proj"],
+                    "proj": ["out_proj"],
+                },
+                "model": {
+                    "qkv_proj": ["q_proj", "k_proj", "v_proj"],
+                    "gate_up_proj": ["gate_proj", "up_proj"],
+                    "fused_qkv_a_proj_with_mqa": [
                         "q_a_proj",
                         "kv_a_proj_with_mqa",
-        ]
-        packed_modules_mapping["qkv_proj"] = ["q_proj", "k_proj", "v_proj"]
-        packed_modules_mapping["gate_up_proj"] = ["gate_proj", "up_proj"]
+                    ],
+                },
+            }
+        )
+
     quant_config = _get_quantization_config(
         model_config, load_config, packed_modules_mapping
     )

test/srt/test_ascend_w8a8_quantization.py

+"""
+Usage:
+python3 -m unittest test_ascend_w8a8_quantization.TestAscendW8A8.test_gsm8k
+"""
+
+import os
+import time
+import unittest
+from types import SimpleNamespace
+from urllib.parse import urlparse
+
+import requests
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.few_shot_gsm8k import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    is_in_ci,
+    popen_launch_server,
+)
+
+if "ASCEND_RT_VISIBLE_DEVICES" not in os.environ:
+    os.environ["ASCEND_RT_VISIBLE_DEVICES"] = "0,1"
+DEFAULT_PORT_FOR_SRT_TEST_RUNNER = (
+    7000 + int(os.environ.get("ASCEND_RT_VISIBLE_DEVICES", "0")[0]) * 100
+)
+DEFAULT_URL_FOR_TEST = f"http://127.0.0.1:{DEFAULT_PORT_FOR_SRT_TEST_RUNNER + 1000}"
+
+
+class TestAscendW8A8(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = "vllm-ascend/Qwen2.5-0.5B-Instruct-w8a8"
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                "--trust-remote-code",
+                "--disable-cuda-graph",
+                "--device",
+                "npu",
+                "--attention-backend",
+                "ascend",
+                "--quantization",
+                "w8a8_int8",
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        base_url = DEFAULT_URL_FOR_TEST
+        url = urlparse(base_url)
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=200,
+            max_new_tokens=512,
+            parallel=128,
+            host=f"http://{url.hostname}",
+            port=int(url.port),
+        )
+        metrics = run_eval(args)
+        print(metrics)
+
+        self.assertGreaterEqual(metrics["accuracy"], 0.25)
+        self.assertGreaterEqual(metrics["output_throughput"], 1000)
+
+    def run_decode(self, max_new_tokens):
+        response = requests.post(
+            self.base_url + "/generate",
+            json={
+                "text": "The capital of France is",
+                "sampling_params": {
+                    "temperature": 0,
+                    "max_new_tokens": max_new_tokens,
+                },
+                "ignore_eos": True,
+            },
+        )
+        return response.json()
+
+    def test_throughput(self):
+        max_tokens = 256
+
+        tic = time.perf_counter()
+        res = self.run_decode(max_tokens)
+        tok = time.perf_counter()
+        print(res["text"])
+        throughput = max_tokens / (tok - tic)
+        print(f"Throughput: {throughput} tokens/s")
+
+        if is_in_ci():
+            self.assertGreaterEqual(throughput, 25)
+
+
+if __name__ == "__main__":
+    unittest.main()