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vllm_ascend/torchair/torchair_model_runner.py

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@@ -120,18 +120,6 @@ def _generate_dummy_run_hidden_states(self, with_prefill,
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hidden_states = super()._generate_dummy_run_hidden_states(
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with_prefill, is_torchair_compile, input_ids, positions,
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attn_metadata, num_tokens, intermediate_tensors, inputs_embeds)
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if not self.in_profile_run and self.lmhead_tp_enable():
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# lmhead_tp introduces additional communication across
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# dp when computing logits. Hence we need to add it
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# in profile_run.
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if not with_prefill:
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max_num_reqs_across_dp = num_tokens
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else:
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max_num_reqs_across_dp = self.scheduler_config.max_num_seqs
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dummy_indices = torch.zeros(max_num_reqs_across_dp,
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device=hidden_states.device,
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dtype=torch.int32)
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self.model.compute_logits(hidden_states[dummy_indices], None)
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return hidden_states
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def _convert_torch_format(self, kv_cache):

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