#
# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
# Copyright 2023 The vLLM team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# This file is a part of the vllm-ascend project.
# Adapted from vllm-project/vllm/vllm/worker/gpu_model_runner.py
#

from vllm_ascend.spec_decode.draft_proposer import AscendDraftModelProposer
from vllm_ascend.spec_decode.eagle_proposer import AscendEagleProposer
from vllm_ascend.spec_decode.medusa_proposer import AscendMedusaProposer
from vllm_ascend.spec_decode.ngram_proposer import AscendNgramProposer
from vllm_ascend.spec_decode.suffix_proposer import AscendSuffixDecodingProposer


def get_spec_decode_method(method, vllm_config, device, runner):
    if method == "ngram":
        return AscendNgramProposer(vllm_config, runner)
    elif method == "suffix":
        return AscendSuffixDecodingProposer(vllm_config, runner)
    elif method == "medusa":
        return AscendMedusaProposer(vllm_config, device)
    elif method in ("eagle", "eagle3", "mtp"):
        return AscendEagleProposer(vllm_config, device, runner)
    elif method == "draft_model":
        return AscendDraftModelProposer(vllm_config, device, runner)
    else:
        raise ValueError(f"Unknown speculative decoding method: {method}")