upgrade vLLM to main (#4608)
1. fix https://github.com/vllm-project/vllm/pull/28542 The model structure modifications we involved in are: - Qwen2.5-VL(still exist some patch) - Qwen2-VL - Qwen2 - DeepSeek series - Qwen-moe series 2. fix https://github.com/vllm-project/vllm/pull/29121 the output token now type changed from np to `list[list[int]]` 3. fix https://github.com/vllm-project/vllm/pull/29262 `xformers` backend for multimodal now has been deprecated 4. fix https://github.com/vllm-project/vllm/pull/29342 5. fix https://github.com/vllm-project/vllm/pull/28579 6. fix https://github.com/vllm-project/vllm/pull/28718 7. fix https://github.com/vllm-project/vllm/issues/28665 8. fix https://github.com/vllm-project/vllm/pull/26847 vllm introduced the `optimization-level`, some default config has been changed, and the param `--enforce-eager` has been deprecated 9. fix http://github.com/vllm-project/vllm/pull/29223 it retuns tuple for sampler. 10. fix https://github.com/vllm-project/vllm/pull/29471 we'll remove the related patch to avoid this kind of error. Co-authored-by: hfadzxy <starmoon_zhang@163.com> Co-authored-by: wangli <wangli858794774@gmail.com> - vLLM version: v0.11.2 --------- Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com> Signed-off-by: wangli <wangli858794774@gmail.com> Signed-off-by: hfadzxy <starmoon_zhang@163.com> Co-authored-by: wangli <wangli858794774@gmail.com> Co-authored-by: hfadzxy <starmoon_zhang@163.com>
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@@ -138,7 +138,8 @@ class EagleProposer(Proposer):
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dummy_compute_logits(self.hidden_states)
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def generate_token_ids(self,
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valid_sampled_token_ids: list[np.ndarray],
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valid_sampled_token_ids: torch.Tensor
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| list[list[int]],
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sampling_metadata: SamplingMetadata = None,
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scheduler_output: SchedulerOutput = None,
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spec_decode_metadata: SpecDecodeMetadata = None,
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@@ -151,7 +152,7 @@ class EagleProposer(Proposer):
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attn_metadata = self._get_eagle_atten_dict(scheduler_output)
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next_token_ids: list[int] = []
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for i, token_ids in enumerate(valid_sampled_token_ids):
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if token_ids.shape[0] > 0:
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if token_ids:
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# Common case.
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next_token_id = token_ids[-1]
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else:
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@@ -163,7 +164,7 @@ class EagleProposer(Proposer):
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scheduler_output.num_scheduled_tokens[req_id])
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next_token_id = req_state.get_token_id(seq_len)
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next_token_ids.append(next_token_id.item())
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next_token_ids.append(next_token_id)
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next_token_ids = torch.tensor(next_token_ids,
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dtype=torch.int32,
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device=self.device)
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@@ -183,7 +184,7 @@ class EagleProposer(Proposer):
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else:
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num_draft_tokens = spec_decode_metadata.num_draft_tokens
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num_rejected_tokens = [
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n + 1 - valid_sampled_token_ids[i].shape[0] if n > 0 else 0
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n + 1 - len(valid_sampled_token_ids[i]) if n > 0 else 0
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for i, n in enumerate(num_draft_tokens)
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]
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num_rejected_tokens = torch.tensor(
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