[Minor, Performance] Use torch.argmax for greedy sampling (#1589)

python/sglang/srt/layers/sampler.py

@@ -43,7 +43,10 @@ class Sampler(nn.Module):
                 torch.isnan(probs), torch.full_like(probs, 1e-10), probs
             )
 
-        if global_server_args_dict["sampling_backend"] == "flashinfer":
+        if sampling_info.top_ks.max().item() <= 1:
+            # Use torch.argmax if all requests use greedy sampling
+            batch_next_token_ids = torch.argmax(probs, -1)
+        elif global_server_args_dict["sampling_backend"] == "flashinfer":
             max_top_k_round, batch_size = 32, probs.shape[0]
             uniform_samples = torch.rand(
                 (max_top_k_round, batch_size), device=probs.device

test/srt/test_bench_serving.py

@@ -27,11 +27,11 @@ class TestBenchServing(unittest.TestCase):
             model=DEFAULT_MODEL_NAME_FOR_TEST,
             num_prompts=200,
             request_rate=float("inf"),
+            other_server_args=["--max-running-requests", "10"],
             dataset_name="sharegpt",
             random_input_len=None,
             random_output_len=None,
             disable_stream=True,
-            other_server_args=["--max-running-requests", "10"],
         )
 
         if is_in_ci():

test/srt/test_pytorch_sampling_backend.py

+import json
 import unittest
 from types import SimpleNamespace
 
+import requests
+
 from sglang.srt.utils import kill_child_process
 from sglang.test.run_eval import run_eval
 from sglang.test.test_utils import (
@@ -39,6 +42,32 @@ class TestPyTorchSamplingBackend(unittest.TestCase):
         metrics = run_eval(args)
         assert metrics["score"] >= 0.65
 
+    def test_greedy(self):
+        response_single = requests.post(
+            self.base_url + "/generate",
+            json={
+                "text": "The capital of France is",
+                "sampling_params": {
+                    "temperature": 0,
+                    "max_new_tokens": 32,
+                },
+            },
+        ).json()
+        response_batch = requests.post(
+            self.base_url + "/generate",
+            json={
+                "text": ["The capital of France is"] * 10,
+                "sampling_params": {
+                    "temperature": 0,
+                    "max_new_tokens": 32,
+                },
+            },
+        ).json()
+        text = response_single["text"]
+        print(text)
+        for i in range(10):
+            assert response_batch[i]["text"] == text
+
 
 if __name__ == "__main__":
     unittest.main()