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[FDConfig]Remove splitwise_role and engine_worker_queue_port in FDConfig (#4147)
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* remove splitwise_role and engine_worker_queue_port * fix xpu * fix xpu * fix xpu * fix unittest * resolve conflct
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@@ -905,12 +905,12 @@ class MetaxModelRunner(ModelRunnerBase):
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only_decode_batch = True
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prefill_exists = None
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# mix ep in single node
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if self.fd_config.parallel_config.use_ep and self.fd_config.parallel_config.splitwise_role == "mixed":
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if self.fd_config.parallel_config.use_ep and self.fd_config.scheduler_config.splitwise_role == "mixed":
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only_decode_batch_list = []
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prefill_exists = self.exist_prefill()
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paddle.distributed.all_gather_object(only_decode_batch_list, not prefill_exists)
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only_decode_batch = all(only_decode_batch_list)
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self.fd_config.parallel_config.moe_phase.phase = "decode" if only_decode_batch else "prefill"
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self.fd_config.model_config.moe_phase.phase = "decode" if only_decode_batch else "prefill"
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self.forward_meta.step_use_cudagraph = (
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self.use_cudagraph
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@@ -947,7 +947,9 @@ class MetaxModelRunner(ModelRunnerBase):
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)
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local_rank = self.local_rank % self.parallel_config.tensor_parallel_size
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if not profile and (self.cache_config.enable_prefix_caching or self.parallel_config.splitwise_role != "mixed"):
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if not profile and (
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self.cache_config.enable_prefix_caching or self.scheduler_config.splitwise_role != "mixed"
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):
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cache_kvs_list = []
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for i in range(self.model_config.num_hidden_layers):
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key_cache = paddle.empty(shape=[], dtype=cache_type)
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@@ -1407,7 +1409,7 @@ class MetaxModelRunner(ModelRunnerBase):
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stop_seqs_len=self.share_inputs["stop_seqs_len"],
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)
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if self.speculative_config.method in ["mtp"] and self.parallel_config.splitwise_role == "prefill":
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if self.speculative_config.method in ["mtp"] and self.scheduler_config.splitwise_role == "prefill":
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skip_save_output = True
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else:
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skip_save_output = False
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