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84 lines
3.2 KiB
Python
84 lines
3.2 KiB
Python
# Copyright (c) 2026 LightSeek Foundation
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in
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# all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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from __future__ import annotations
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from abc import abstractmethod
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from typing import TYPE_CHECKING
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import torch
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from tokenspeed.runtime.execution.model_runner import ModelRunner
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if TYPE_CHECKING:
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from tokenspeed.runtime.execution.context import ForwardContext
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from tokenspeed.runtime.execution.input_buffer import InputBuffers
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from tokenspeed.runtime.execution.runtime_states import RuntimeStates
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from tokenspeed.runtime.layers.attention.backends.base import AttentionBackend
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from tokenspeed.runtime.layers.attention.kv_cache.base import BaseTokenToKVPool
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from tokenspeed.runtime.layers.logits_processor import LogitsProcessorOutput
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class BaseDrafter:
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def __init__(
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self,
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spec_num_tokens: int,
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spec_num_steps: int | None = None,
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draft_model_runner: ModelRunner | None = None,
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runtime_states: RuntimeStates | None = None,
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input_buffers: InputBuffers | None = None,
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page_size: int | None = None,
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req_to_page: torch.Tensor | None = None,
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attn_backend: AttentionBackend | None = None,
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token_to_kv_pool: BaseTokenToKVPool | None = None,
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vocab_size: int | None = None,
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):
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self.spec_num_tokens = spec_num_tokens
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self.spec_num_steps = spec_num_steps
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self.draft_model_runner = draft_model_runner
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self.runtime_states = runtime_states
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self.input_buffers = input_buffers
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self.page_size = page_size
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self.req_to_page = req_to_page
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self.attn_backend = attn_backend
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self.token_to_kv_pool = token_to_kv_pool
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self.vocab_size = vocab_size
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@abstractmethod
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def get_candidates(
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self,
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base_ctx: ForwardContext,
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) -> torch.Tensor | None:
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raise NotImplementedError
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@abstractmethod
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def run(
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self,
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base_ctx: ForwardContext,
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logits_output: LogitsProcessorOutput,
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output_tokens: torch.Tensor,
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accept_lengths: torch.Tensor,
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) -> torch.Tensor:
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raise NotImplementedError
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@abstractmethod
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def draft(self, *args, **kwargs) -> torch.Tensor | None:
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raise NotImplementedError
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