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Code Issues Actions 2 Packages Projects Releases Wiki Activity

Revert "[BugFix] num_seqs (#3291)" (#3316)

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This reverts commit e0aeac58e1.
This commit is contained in:
Jiang-Jia-Jun
2025-08-11 16:16:51 +08:00
committed by GitHub
parent 9571c458f0
commit c56c99837a
3 changed files with 3 additions and 6 deletions
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2
fastdeploy/model_executor/models/ernie4_5_moe.py
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@@ -450,7 +450,7 @@ class Ernie4_5_MoeForCausalLM(ModelForCasualLM):
self.fd_config.model_config.moe_layer_start_index, self.fd_config.model_config.moe_layer_start_index,
self.fd_config.model_config.num_hidden_layers, self.fd_config.model_config.num_hidden_layers,
): ):
self.ernie.layers[i].mlp.experts(fake_hidden_states, self.ernie.layers[i].mlp.gate) self.ernie.layers[i].mlp.expert(fake_hidden_states)
def forward( def forward(
self, self,

4
fastdeploy/worker/gpu_model_runner.py
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@@ -799,7 +799,7 @@ class GPUModelRunner(ModelRunnerBase):
output_padding_offset, output_padding_offset,
) = pre_process( ) = pre_process(
self.share_inputs["input_ids"], self.share_inputs["input_ids"],
getattr(self.share_inputs, "seq_lens_this_time", self.seq_lens_this_time_buffer), self.share_inputs["seq_lens_this_time"],
self.speculative_decoding, self.speculative_decoding,
(self.share_inputs["draft_tokens"] if self.speculative_decoding else None), (self.share_inputs["draft_tokens"] if self.speculative_decoding else None),
self.share_inputs["seq_lens_encoder"], self.share_inputs["seq_lens_encoder"],
@@ -884,7 +884,7 @@ class GPUModelRunner(ModelRunnerBase):
max_len_tensor_cpu=self.share_inputs["max_len_tensor_cpu"], max_len_tensor_cpu=self.share_inputs["max_len_tensor_cpu"],
seq_lens_encoder=self.share_inputs["seq_lens_encoder"], seq_lens_encoder=self.share_inputs["seq_lens_encoder"],
seq_lens_decoder=self.share_inputs["seq_lens_decoder"], seq_lens_decoder=self.share_inputs["seq_lens_decoder"],
seq_lens_this_time=getattr(self.share_inputs, "seq_lens_this_time", self.seq_lens_this_time_buffer), seq_lens_this_time=self.share_inputs["seq_lens_this_time"],
batch_id_per_token=self.share_inputs["batch_id_per_token"], batch_id_per_token=self.share_inputs["batch_id_per_token"],
cu_seqlens_q=self.share_inputs["cu_seqlens_q"], cu_seqlens_q=self.share_inputs["cu_seqlens_q"],
cu_seqlens_k=self.share_inputs["cu_seqlens_k"], cu_seqlens_k=self.share_inputs["cu_seqlens_k"],

3
fastdeploy/worker/worker_process.py
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@@ -244,7 +244,6 @@ class PaddleDisWorkerProc:
""" """
while True: while True:
self.worker_healthy_live_signal.value[self.local_rank % self.max_chips_per_node] = int(time.time()) self.worker_healthy_live_signal.value[self.local_rank % self.max_chips_per_node] = int(time.time())
num_running_requests = 0
if self.fd_config.parallel_config.tensor_parallel_rank == 0 and self.task_queue.num_tasks() > 0: if self.fd_config.parallel_config.tensor_parallel_rank == 0 and self.task_queue.num_tasks() > 0:
tasks, read_finish = self.task_queue.get_tasks() tasks, read_finish = self.task_queue.get_tasks()
@@ -272,8 +271,6 @@ class PaddleDisWorkerProc:
self.nnode = int((self.parallel_config.tensor_parallel_size + 7) // 8) self.nnode = int((self.parallel_config.tensor_parallel_size + 7) // 8)
mp_num_per_node = self.parallel_config.tensor_parallel_size // self.nnode mp_num_per_node = self.parallel_config.tensor_parallel_size // self.nnode
req_ids = [] req_ids = []
num_running_requests = 0
while True: while True:
if self.local_rank == 0: if self.local_rank == 0:
if self.model_weights_status.value[0] != 0: if self.model_weights_status.value[0] != 0: