adapt to sglang v0.5.2rc1 on dcu

benchmark/multi_document_qa/bench_sglang.py

@@ -0,0 +1,93 @@
+import argparse
+import json
+import time
+
+import sglang as sgl
+from sglang.test.test_utils import (
+    add_common_sglang_args_and_parse,
+    select_sglang_backend,
+)
+from sglang.utils import dump_state_text, read_jsonl
+
+
+@sgl.function
+def multi_document_qa(s, docs, question):
+    s += sgl.user_begin()
+    s += "Please answer a question according to given documents.\n"
+    s += "Question:" + question + "Documents begin.\n"
+
+    forks = s.fork(len(docs))
+    forks += lambda i: docs[i]
+    forks.join("concate_and_append")
+
+    s += "\nDocuments end."
+    s += (
+        "\n\nBased on the above documents, please answer this question:\n"
+        + question
+        + "\nAnswer in three words or fewer."
+    )
+    s += sgl.user_end()
+    s += sgl.assistant(sgl.gen("answer", max_tokens=16))
+
+
+def main(args):
+    lines = read_jsonl(args.data_path)
+    l = lines[0]
+    arguments = []
+    labels = []
+    for i in range(len(l["questions"][: args.num_questions])):
+        arguments.append(
+            {
+                "docs": l["documents"][:10],
+                "question": l["questions"][i],
+            }
+        )
+        labels.append(l["answers"][i])
+
+    # Select backend
+    backend = select_sglang_backend(args)
+    sgl.set_default_backend(backend)
+
+    # Run requests
+    tic = time.perf_counter()
+    states = multi_document_qa.run_batch(
+        arguments, temperature=0, num_threads=args.parallel, progress_bar=True
+    )
+    latency = time.perf_counter() - tic
+
+    # Compute accuracy
+    print([s["answer"] for s in states])
+    correct = 0
+    for s, label in zip(states, labels):
+        answer = s["answer"].lower()
+        if all(x in answer for x in label.lower().split(" ")):
+            correct += 1
+    accuracy = correct / len(labels)
+    print(f"Accuracy: {accuracy:.3f}")
+    print(f"Latency: {latency:.3f}")
+
+    # Write results
+    dump_state_text(f"tmp_output_{args.backend}.txt", states)
+
+    with open(args.result_file, "a") as fout:
+        value = {
+            "task": "multi_document_qa",
+            "backend": args.backend,
+            "num_gpus": 1,
+            "latency": round(latency, 3),
+            "num_requests": args.num_questions,
+            "accuracy": accuracy,
+            "other": {
+                "num_questions": args.num_questions,
+                "parallel": args.parallel,
+            },
+        }
+        fout.write(json.dumps(value) + "\n")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--data-path", type=str, default="questions.jsonl")
+    parser.add_argument("--num-questions", type=int, default=100)
+    args = add_common_sglang_args_and_parse(parser)
+    main(args)