[SOT] Extend SOT warmup support to new hardware (#3032)

* add new hardware

* add_sot_warmup4new_hardware

* fix conflict

* rm Optional
This commit is contained in:
Ryan
2025-07-29 22:45:20 +08:00
committed by GitHub
parent b2f9a42d87
commit 73cfe1fd37
7 changed files with 62 additions and 4 deletions

View File

@@ -26,6 +26,10 @@ from paddleformers.utils.log import logger
from fastdeploy.config import FDConfig
from fastdeploy.engine.request import Request
from fastdeploy.model_executor.forward_meta import ForwardMeta
from fastdeploy.model_executor.graph_optimization.utils import (
profile_run_guard,
sot_warmup_guard,
)
from fastdeploy.model_executor.guided_decoding import get_guided_backend
from fastdeploy.model_executor.guided_decoding.base_guided_decoding import (
LogitsProcessorBase,
@@ -79,8 +83,10 @@ class GCUModelRunner(ModelRunnerBase):
self.sampler = SpeculativeSampler(fd_config)
# Cuda Graph
self.graph_opt_level = self.graph_opt_config.graph_opt_level
self.use_cudagraph = self.graph_opt_config.use_cudagraph
self.cudagraph_capture_sizes = list(reversed(self.graph_opt_config.cudagraph_capture_sizes))
self.sot_warmup_sizes = self.graph_opt_config.sot_warmup_sizes
# Initialize share inputs
self._init_share_inputs(self.parallel_config.max_num_seqs)
@@ -851,6 +857,17 @@ class GCUModelRunner(ModelRunnerBase):
time_after_capture = time.perf_counter()
logger.info(f"Cuda Graph capturing took {time_after_capture - time_before_capture} seconds")
@sot_warmup_guard(True)
def sot_warmup(self) -> None:
start_time = time.perf_counter()
for batch_size in self.sot_warmup_sizes:
self._dummy_run(
num_tokens=self.parallel_config.max_num_batched_tokens,
batch_size=batch_size,
)
logger.info(f"SOT warmup the model with the batch size:{batch_size}")
logger.info(f"SOT warmup took {time.perf_counter() - start_time} seconds")
def _get_skip_idx(self, model_forward_batch: Optional[List[Request]] = None):
"""
Get the index of the request that needs to be skipped during execution.
@@ -1041,6 +1058,7 @@ class GCUModelRunner(ModelRunnerBase):
else:
raise ValueError(f"{type(self.model)} has no attribute 'empty_input_forward")
@profile_run_guard(True)
def profile_run(self) -> None:
"""Execute a forward pass with dummy inputs to profile the memory usage of the model"""