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