45 lines
1.1 KiB
Python
45 lines
1.1 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from dataclasses import dataclass
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from typing import Optional
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import torch
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@dataclass
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class SamplingMetadata:
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temperature: Optional[torch.Tensor]
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all_greedy: bool
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all_random: bool
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top_p: Optional[torch.Tensor]
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top_k: Optional[torch.Tensor]
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min_p: Optional[torch.Tensor]
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generators: dict[int, torch.Generator]
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# None means no logprobs, 0 means sampled token logprobs only
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max_num_logprobs: Optional[int]
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no_penalties: bool
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prompt_token_ids: Optional[torch.Tensor]
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frequency_penalties: torch.Tensor
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presence_penalties: torch.Tensor
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repetition_penalties: torch.Tensor
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output_token_ids: list[list[int]]
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# req_index -> (min_tokens, stop_token_ids)
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min_tokens: dict[int, tuple[int, set[int]]]
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logit_bias: list[Optional[dict[int, float]]]
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# `allowed_token_ids_mask` is a 2D bool tensor of shape (max batch size,
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# vocab size).
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allowed_token_ids_mask: Optional[torch.Tensor]
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# req_index -> bad_words_token_ids
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bad_words_token_ids: dict[int, list[list[int]]]
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