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polish code for prefill restrictions (#2991)

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Zero Rains
2025-07-23 20:10:14 +08:00
committed by GitHub
parent 172e69fe17
commit ca0f71bd39
2 changed files with 5 additions and 13 deletions
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13
fastdeploy/worker/gpu_model_runner.py
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@@ -150,17 +150,10 @@ class GPUModelRunner(ModelRunnerBase):
"""
Check whether prefill stage finished
"""
if self.enable_mm:
# VL only support 1 batch to prefill
prefill_statue = (self.share_inputs["seq_lens_this_time"] != 0) & (
self.share_inputs["seq_lens_this_time"] != 1
)
return not paddle.any(prefill_statue).numpy()
if int(paddle.max(self.share_inputs["seq_lens_encoder"])) != 0:
return 1
else:
if int(paddle.max(self.share_inputs["seq_lens_encoder"])) != 0:
return 1
else:
return 0
return 0
def _init_speculative_proposer(self):
"""

5
fastdeploy/worker/worker_process.py
View File

@@ -286,7 +286,7 @@ class PaddleDisWorkerProc:
if self.local_rank % mp_num_per_node == 0:
if self.task_queue.num_tasks() > 0:
# VL only support 1 batch to prefill
if not self.fd_config.model_config.enable_mm or self.worker.prefill_finished():
if not self.fd_config.model_config.enable_mm or not self.worker.prefill_finished():
if self.nnode > 1:
self.task_queue.read_finish_flag.set(1)
else:
@@ -346,8 +346,7 @@ class PaddleDisWorkerProc:
# Execute model to generate token. The generated token will be written to the buffer.
# These generated tokens can be obtained through get_output op.
self.worker.execute_model(req_dicts)
if not self.fd_config.model_config.enable_mm:
self.exist_prefill_task_signal.value[0] = self.worker.prefill_finished()
self.exist_prefill_task_signal.value[0] = self.worker.prefill_finished()
def initialize_kv_cache(self) -> None:
"""Profiles the peak memory usage of the model to determine how many