### What this PR does / why we need it?
This PR aims to support aclgraph for model runner v2, please see RFC
#5208. The PR contains these modifications:
- adapt to newest commit of vllm main branch.
- supply a unified interface of extra forward context for both model
runner v1 and model runner v2.
- implement graph mode for main model.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
54 lines
1.7 KiB
Python
54 lines
1.7 KiB
Python
from contextlib import contextmanager
|
|
|
|
import torch
|
|
import vllm
|
|
from vllm.logger import logger
|
|
|
|
from vllm_ascend.worker.v2.block_table import AscendBlockTables
|
|
from vllm_ascend.worker.v2.model_states import init_asecnd_model_state
|
|
|
|
|
|
@contextmanager
|
|
def torch_cuda_wrapper():
|
|
try:
|
|
torch.cuda.Event = torch.npu.Event
|
|
torch.cuda.Stream = torch.npu.Stream
|
|
torch.cuda.stream = torch.npu.stream
|
|
torch.cuda.default_stream = torch.npu.default_stream
|
|
torch.cuda.current_stream = torch.npu.current_stream
|
|
torch.cuda.graph_pool_handle = torch.npu.graph_pool_handle
|
|
torch.cuda.CUDAGraph = torch.npu.NPUGraph
|
|
torch.cuda.graph = torch.npu.graph
|
|
torch.cuda.synchronize = torch.npu.synchronize
|
|
torch.cuda.set_stream = torch.npu.set_stream
|
|
torch.cuda.current_device = torch.npu.current_device
|
|
torch.cuda.mem_get_info = torch.npu.mem_get_info
|
|
logger.info_once("Wrapping torch.cuda with torch.npu.")
|
|
yield
|
|
finally:
|
|
pass
|
|
|
|
|
|
@contextmanager
|
|
def block_table_wrapper():
|
|
try:
|
|
# vllm-ascend need to initialize slot mapping as torch.int32 dtype,
|
|
# but vllm default is torch.int64 dtype.
|
|
vllm.v1.worker.gpu.model_runner.BlockTables = AscendBlockTables
|
|
logger.info_once("Wrapping BlockTables with AscendBlockTables.")
|
|
yield
|
|
finally:
|
|
pass
|
|
|
|
|
|
@contextmanager
|
|
def model_states_wrapper():
|
|
try:
|
|
# prepare_attn in AscendModelState is different from vllm,
|
|
# we need to override init_model_state.
|
|
vllm.v1.worker.gpu.model_runner.init_model_state = init_asecnd_model_state
|
|
logger.info_once("Wrapping init_model_state with init_asecnd_model_state.")
|
|
yield
|
|
finally:
|
|
pass
|