add qwen3

vllm-v0.6.2/vllm/beam_search.py

@@ -0,0 +1,71 @@
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
+
+from vllm.sequence import Logprob
+
+if TYPE_CHECKING:
+    from vllm.multimodal import MultiModalDataDict
+
+
+@dataclass
+class BeamSearchSequence:
+    """A sequence for beam search.
+    It keeps track of the tokens and the log probability of the sequence.
+    The text field is optional and will only be filled when the sequence is
+    about to be returned to the user.
+    """
+    # The tokens includes the prompt.
+    tokens: List[int]
+    logprobs: List[Dict[int, Logprob]]
+    cum_logprob: float = 0.0
+    text: Optional[str] = None
+    finish_reason: Optional[str] = None
+    stop_reason: Union[int, str, None] = None
+    multi_modal_data: Optional["MultiModalDataDict"] = None
+    mm_processor_kwargs: Optional[Dict[str, Any]] = None
+
+
+@dataclass
+class BeamSearchOutput:
+    """The output of beam search.
+    It contains the list of the best beam search sequences.
+    The length of the list is equal to the beam width.
+    """
+    sequences: List[BeamSearchSequence]
+
+
+class BeamSearchInstance:
+
+    def __init__(self, prompt_tokens: List[int]):
+        self.beams: List[BeamSearchSequence] = [
+            BeamSearchSequence(tokens=prompt_tokens, logprobs=[])
+        ]
+        self.completed: List[BeamSearchSequence] = []
+
+
+def get_beam_search_score(
+    tokens: List[int],
+    cumulative_logprob: float,
+    eos_token_id: int,
+    length_penalty: float = 1.0,
+) -> float:
+    """Calculate the beam search score with length penalty.
+
+    Adapted from
+
+    https://github.com/huggingface/transformers/blob/ccb92be23def445f2afdea94c31286f84b89eb5b/src/transformers/generation/beam_search.py#L938
+    """
+    seq_len = len(tokens)
+    if tokens[-1] == eos_token_id:
+        seq_len -= 1
+
+    return cumulative_logprob / (seq_len**length_penalty)
+
+
+def create_sort_beams_key_function(eos_token_id: int, length_penalty: float):
+
+    def sort_beams_key(x: BeamSearchSequence) -> float:
+        return get_beam_search_score(x.tokens, x.cum_logprob, eos_token_id,
+                                     length_penalty)
+
+    return sort_beams_key