Files
wehub-resource-sync 59a0a3844c
PR Test AMD / cancel-on-close (push) Has been skipped
PR Test NVIDIA ARM / scan (push) Has been skipped
PR Test NVIDIA / cancel-on-close (push) Has been skipped
PR Test AMD / scan (push) Has been skipped
PR Test NVIDIA ARM / cancel-on-close (push) Has been skipped
PR Test NVIDIA / scan (push) Has been skipped
Release Docker Images / build (cu129-torch-2.11.0) (push) Has been skipped
Release Docker Images / build (cu130-torch-2.11.0) (push) Has been skipped
Release PyPI / publish (push) Has been skipped
Scheduler Python Test / test (push) Successful in 27m19s
Docs / build (push) Successful in 28m8s
Scheduler C++ Test / test (push) Successful in 28m19s
Scheduler C++ Test / test-flat (push) Successful in 28m18s
Docs / deploy (push) Has been cancelled
PR Test AMD / finish (push) Has been cancelled
PR Test NVIDIA / finish (push) Has been cancelled
PR Test NVIDIA ARM / finish (push) Has been cancelled
PR Test NVIDIA ARM / ${{ matrix.name }} (${{ matrix.runner }}) (push) Has been cancelled
PR Test AMD / ${{ matrix.name }} (${{ matrix.runner }}) (push) Has been cancelled
PR Test NVIDIA / ${{ matrix.name }} (${{ matrix.runner }}) (push) Has been cancelled
chore: import upstream snapshot with attribution
2026-07-13 12:32:31 +08:00

84 lines
3.2 KiB
Python

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