/python/tokenspeed/runtime/configs/qwen3_moe_config.py

# 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.

"""Qwen3 MoE model configuration definitions."""

from tokenspeed.runtime.configs.qwen3_config import Qwen3Config


class Qwen3MoeConfig(Qwen3Config):
    """Configuration for Qwen3 MoE causal LMs such as Qwen3-30B-A3B."""

    model_type = "qwen3_moe"

    def __init__(
        self,
        decoder_sparse_step=1,
        moe_intermediate_size=768,
        shared_expert_intermediate_size=0,
        num_experts_per_tok=8,
        num_experts=128,
        norm_topk_prob=True,
        output_router_logits=False,
        router_aux_loss_coef=0.001,
        mlp_only_layers=None,
        **kwargs,
    ):
        super().__init__(**kwargs)
        self.decoder_sparse_step = decoder_sparse_step
        self.moe_intermediate_size = moe_intermediate_size
        self.shared_expert_intermediate_size = shared_expert_intermediate_size
        self.num_experts_per_tok = num_experts_per_tok
        self.num_experts = num_experts
        self.norm_topk_prob = norm_topk_prob
        self.output_router_logits = output_router_logits
        self.router_aux_loss_coef = router_aux_loss_coef
        self.mlp_only_layers = [] if mlp_only_layers is None else mlp_only_layers


__all__ = ["Qwen3MoeConfig"]