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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 12, 21:00 UTC

[CI/Build] Make test_attention_selector.py run tests on correct platform (#29064)

Signed-off-by: Randall Smith <ransmith@amd.com> Signed-off-by: rasmith <Randall.Smith@amd.com> Co-authored-by: Randall Smith <ransmith@amd.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

rasmith committed Nov 20, 2025 at 14:45 UTC 5e5a7eb16f121f05e19c8bdf88247744ab9d1b83
1 file changed +4 -1
tests/kernels/attention/test_attention_selector.py
+4 -1
@@ -7,6 +7,7 @@ import pytest
7 import torch
8
9 from vllm.attention.selector import _cached_get_attn_backend, get_attn_backend
10 +from vllm.platforms import current_platform
11 from vllm.platforms.cpu import CpuPlatform
12 from vllm.platforms.cuda import CudaPlatform
13 from vllm.platforms.rocm import RocmPlatform
@@ -47,9 +48,11 @@ DEVICE_MLA_BLOCK_SIZES = {
48
49
50 def generate_params():
51 + is_rocm = current_platform.is_rocm()
52 params = []
53 + device_list = ["cuda", "cpu"] if not is_rocm else ["hip", "cpu"]
54 for use_mla in [True, False]:
52 - for device in ["cuda", "hip", "cpu"]:
55 + for device in device_list:
56 backends = (
57 DEVICE_MLA_BACKENDS[device]
58 if use_mla