Enable loading of fused expert weights in the Transformers modelling backend#36997
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The pull request refactors the Mixture of Experts (MoE) weight loading mechanism to support both fused and non-fused expert weight formats. In vllm/model_executor/layers/fused_moe/layer.py, the load_weights method is updated to differentiate between 3D tensors representing fused expert weights and single expert weights, applying a unified loading logic that iterates through individual experts. Concurrently, vllm/model_executor/models/transformers/moe.py introduces an explicit expert_mapping for fused experts, ensuring proper identification and handling of these weight structures during model loading.
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This pull request introduces improvements to the handling and loading of fused Mixture-of-Experts (MoE) weights in the Transformers modelling backend:
save_original_format=False. This mapping repurposesexpert_idasshard_idxfor deconcatenatingw1andw3weights.FusedMoE.load_weightsto handle both fused (3D tensor) and non-fused (single expert) weights, simplifying the process and reducing code duplication.