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revert pr (#3481)

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Co-authored-by: iosmers <yinwei_hust@163.com>
This commit is contained in:
qw86972190
2025-08-21 14:19:50 +08:00
committed by GitHub
parent 51f68ae593
commit c83381d650
2 changed files with 16 additions and 24 deletions
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27
fastdeploy/worker/xpu_model_runner.py
View File

@@ -373,7 +373,7 @@ class XPUModelRunner(ModelRunnerBase):
# Forward meta store the global meta information of the forward
self.forward_meta: ForwardMeta = None
def insert_tasks_v1(self, req_dicts: List[Request], num_running_requests: int = None):
def insert_tasks_v1(self, req_dicts: List[Request]):
"""
Process scheduler output tasks, used when ENABLE_V1_KVCACHE_SCHEDULER=1
"""
@@ -403,7 +403,7 @@ class XPUModelRunner(ModelRunnerBase):
)
self.share_inputs["stop_flags"][idx : idx + 1] = False
self.share_inputs["seq_lens_decoder"][idx : idx + 1] = prefill_start_index
self.seq_lens_this_time_buffer[idx : idx + 1] = length
self.share_inputs["seq_lens_this_time"][idx : idx + 1] = length
self.share_inputs["seq_lens_encoder"][idx : idx + 1] = length
self.share_inputs["step_seq_lens_decoder"][idx : idx + 1] = 0
self.share_inputs["prompt_lens"][idx : idx + 1] = len(input_ids)
@@ -425,7 +425,7 @@ class XPUModelRunner(ModelRunnerBase):
logger.debug(f"Handle preempted request {request} at idx {idx}")
self.share_inputs["block_tables"][idx : idx + 1, :] = -1
self.share_inputs["stop_flags"][idx : idx + 1] = True
self.seq_lens_this_time_buffer[idx : idx + 1] = 0
self.share_inputs["seq_lens_this_time"][idx : idx + 1] = 0
self.share_inputs["seq_lens_decoder"][idx : idx + 1] = 0
self.share_inputs["seq_lens_encoder"][idx : idx + 1] = 0
self.share_inputs["is_block_step"][idx : idx + 1] = False
@@ -465,9 +465,8 @@ class XPUModelRunner(ModelRunnerBase):
)
if has_prefill_task:
self.share_inputs["not_need_stop"][0] = True
self.share_inputs["seq_lens_this_time"] = self.seq_lens_this_time_buffer[:num_running_requests]
def process_prefill_inputs(self, req_dicts: List[Request], num_running_requests: int = None):
def process_prefill_inputs(self, req_dicts: List[Request]):
"""Process inputs for prefill tasks and update share_inputs buffer"""
req_len = len(req_dicts)
for i in range(req_len):
@@ -487,7 +486,7 @@ class XPUModelRunner(ModelRunnerBase):
self.share_inputs["penalty_score"][idx : idx + 1] = request.get("repetition_penalty", 1.0)
self.share_inputs["frequency_score"][idx : idx + 1] = request.get("frequency_penalty", 0.0)
self.share_inputs["presence_score"][idx : idx + 1] = request.get("presence_penalty", 0.0)
self.seq_lens_this_time_buffer[idx : idx + 1] = length
self.share_inputs["seq_lens_this_time"][idx : idx + 1] = length
self.share_inputs["step_seq_lens_encoder"][idx : idx + 1] = length
self.share_inputs["seq_lens_encoder"][idx : idx + 1] = length
self.share_inputs["seq_lens_decoder"][idx : idx + 1] = 0
@@ -531,7 +530,6 @@ class XPUModelRunner(ModelRunnerBase):
)
self.share_inputs["not_need_stop"][0] = True
self.share_inputs["seq_lens_this_time"] = self.seq_lens_this_time_buffer[:num_running_requests]
def _init_share_inputs(self, max_num_seqs: int):
"""Initialize all share buffers for model inputs.
@@ -579,7 +577,7 @@ class XPUModelRunner(ModelRunnerBase):
self.share_inputs["max_length"] = paddle.full(
[max_num_seqs, 1], self.model_config.max_model_len, dtype="int64"
)
self.seq_lens_this_time_buffer = paddle.full(max_num_seqs, 0, dtype="int32")
self.share_inputs["seq_lens_this_time"] = paddle.full(max_num_seqs, 0, dtype="int32")
self.share_inputs["seq_lens_encoder"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
self.share_inputs["seq_lens_decoder"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
self.share_inputs["step_seq_lens_encoder"] = paddle.full([max_num_seqs, 1], 0, dtype="int32")
@@ -823,10 +821,10 @@ class XPUModelRunner(ModelRunnerBase):
for i in range(batch_size):
idx = i
self.share_inputs["input_ids"][idx : idx + 1, :input_length] = np.array([5] * input_length)
self.share_inputs["eos_token_id"][:] = np.array(
[2] * self.model_config.eos_tokens_lens, dtype="int64"
).reshape(-1, 1)
self.seq_lens_this_time_buffer[idx : idx + 1] = input_length
self.share_inputs["eos_token_id"][:] = np.array([2], dtype="int64").reshape(-1, 1)
self.share_inputs["seq_lens_this_time"][idx : idx + 1] = input_length
self.share_inputs["step_seq_lens_encoder"][idx : idx + 1] = input_length
self.share_inputs["seq_lens_encoder"][idx : idx + 1] = input_length
self.share_inputs["seq_lens_decoder"][idx : idx + 1] = 0
@@ -842,7 +840,6 @@ class XPUModelRunner(ModelRunnerBase):
self.share_inputs["block_tables"][idx : idx + 1, :block_num] = np.arange(
idx * block_num, (idx + 1) * block_num, 1
)
self.share_inputs["seq_lens_this_time"] = self.seq_lens_this_time_buffer
def _dummy_run(
self,
@@ -936,10 +933,6 @@ class XPUModelRunner(ModelRunnerBase):
self.cache_config.block_size,
self.cache_config.enc_dec_block_num,
)
if num_running_requests is not None:
self.seq_lens_this_time_buffer[:num_running_requests].copy_(
self.share_inputs["seq_lens_this_time"][:num_running_requests], False
)
return None

13
fastdeploy/worker/xpu_worker.py
View File

@@ -151,10 +151,9 @@ class XpuWorker(WorkerBase):
num_running_requests: Optional[int] = None,
) -> Optional[ModelRunnerOutput]:
""" """
if is_dummy_run:
output = self.model_runner.execute_model(model_forward_batch)
else:
output = self.model_runner.execute_model(model_forward_batch, num_running_requests)
output = self.model_runner.execute_model(model_forward_batch)
return output
def exist_prefill(self):
@@ -163,15 +162,15 @@ class XpuWorker(WorkerBase):
"""
return self.model_runner.exist_prefill()
def preprocess_new_task(self, req_dicts: List[Request], num_running_requests: int) -> None:
def preprocess_new_task(self, req_dicts: List[Request], num_running_requests: int = -1) -> None:
"""Process new requests and then start the decode loop
TODO(gongshaotian):The scheduler should schedule the handling of prefill,
and workers and modelrunners should not perceive it.
"""
if envs.ENABLE_V1_KVCACHE_SCHEDULER:
self.model_runner.insert_tasks_v1(req_dicts=req_dicts, num_running_requests=num_running_requests)
self.model_runner.insert_tasks_v1(req_dicts=req_dicts)
else:
self.model_runner.process_prefill_inputs(req_dicts=req_dicts, num_running_requests=num_running_requests)
self.model_runner.process_prefill_inputs(req_dicts=req_dicts)
def check_health(self) -> bool:
""" """