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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 15, 21:00 UTC

Fix benchmark_moe.py tuning for CUDA devices (#14164)

Michael Goin committed Mar 4, 2025 at 00:11 UTC f78c0be80a8341167a5ebf20ce4eb62421a351a6
1 file changed +3 -1
benchmarks/kernels/benchmark_moe.py
+3 -1
@@ -2,6 +2,7 @@
2
3 import argparse
4 import time
5 +from contextlib import nullcontext
6 from datetime import datetime
7 from itertools import product
8 from typing import Any, TypedDict
@@ -412,7 +413,8 @@ class BenchmarkWorker:
413 hidden_size, search_space,
414 is_fp16, topk)
415
415 - with torch.cuda.device(self.device_id):
416 + with torch.cuda.device(self.device_id) if current_platform.is_rocm(
417 + ) else nullcontext():
418 for config in tqdm(search_space):
419 try:
420 kernel_time = benchmark_config(