ef6abf3dc7
Adds ALL files needed for Dockerfile build:
- qwen3_6_scripts/ (baseline patches + our optimizations)
- vllm/ (full vllm package)
- paged_attention_v2_pytorch.py (V2 with single-bmm optimization)
- Dockerfile + computility-run.yaml
Our optimizations vs baseline:
1. paged_attn.py: pre-gathered context KV (eliminates 194 gather calls),
Triton try/fallback, V2 heuristic, threshold 32K→64K
2. paged_attention_v2_pytorch.py: fills NotImplementedError,
single-bmm Phase 1 (195 launches → 3)
3. patch_enable_triton.py: HAS_TRITON=True with safety fallback
4. patch_triton_tuning.py: BLOCK=64, NUM_WARPS=4 for BI-V100
5. computility-run.yaml: gpu-memory-utilization 0.9→0.95,
max-num-batched-tokens 8192→16384
This repo can now be submitted to dev.modelhub.org.cn as-is.
82 lines
1.9 KiB
Python
82 lines
1.9 KiB
Python
from .interface import Platform, PlatformEnum, UnspecifiedPlatform
|
|
|
|
current_platform: Platform
|
|
|
|
# NOTE: we don't use `torch.version.cuda` / `torch.version.hip` because
|
|
# they only indicate the build configuration, not the runtime environment.
|
|
# For example, people can install a cuda build of pytorch but run on tpu.
|
|
|
|
is_tpu = False
|
|
try:
|
|
# While it's technically possible to install libtpu on a non-TPU machine,
|
|
# this is a very uncommon scenario. Therefore, we assume that libtpu is
|
|
# installed if and only if the machine has TPUs.
|
|
import libtpu # noqa: F401
|
|
is_tpu = True
|
|
except Exception:
|
|
pass
|
|
|
|
is_cuda = False
|
|
|
|
try:
|
|
import pynvml
|
|
pynvml.nvmlInit()
|
|
try:
|
|
if pynvml.nvmlDeviceGetCount() > 0:
|
|
is_cuda = True
|
|
finally:
|
|
pynvml.nvmlShutdown()
|
|
except Exception:
|
|
is_cuda = True
|
|
|
|
is_rocm = False
|
|
|
|
try:
|
|
import amdsmi
|
|
amdsmi.amdsmi_init()
|
|
try:
|
|
if len(amdsmi.amdsmi_get_processor_handles()) > 0:
|
|
is_rocm = True
|
|
finally:
|
|
amdsmi.amdsmi_shut_down()
|
|
except Exception:
|
|
pass
|
|
|
|
is_xpu = False
|
|
|
|
try:
|
|
import torch
|
|
if hasattr(torch, 'xpu') and torch.xpu.is_available():
|
|
is_xpu = True
|
|
except Exception:
|
|
pass
|
|
|
|
is_cpu = False
|
|
try:
|
|
from importlib.metadata import version
|
|
is_cpu = "cpu" in version("vllm")
|
|
except Exception:
|
|
pass
|
|
|
|
if is_tpu:
|
|
# people might install pytorch built with cuda but run on tpu
|
|
# so we need to check tpu first
|
|
from .tpu import TpuPlatform
|
|
current_platform = TpuPlatform()
|
|
elif is_cuda:
|
|
from .cuda import CudaPlatform
|
|
current_platform = CudaPlatform()
|
|
elif is_rocm:
|
|
from .rocm import RocmPlatform
|
|
current_platform = RocmPlatform()
|
|
elif is_xpu:
|
|
from .xpu import XPUPlatform
|
|
current_platform = XPUPlatform()
|
|
elif is_cpu:
|
|
from .cpu import CpuPlatform
|
|
current_platform = CpuPlatform()
|
|
else:
|
|
current_platform = UnspecifiedPlatform()
|
|
|
|
__all__ = ['Platform', 'PlatformEnum', 'current_platform']
|