permute/unpermute kernel for moe optimization (#14568)
Signed-off-by: Caleb_Du <Caleb_Du@zju.edu.cn>
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@@ -53,7 +53,29 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, m) {
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"int size_m, int size_n, int size_k,"
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"bool is_full_k, bool use_atomic_add,"
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"bool use_fp32_reduce, bool is_zp_float) -> Tensor");
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m.def(
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"marlin_gemm_moe(Tensor! a, Tensor! b_q_weights, Tensor! sorted_ids, "
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"Tensor! topk_weights, Tensor! topk_ids, Tensor! b_scales, Tensor! "
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"b_zeros, Tensor! g_idx, Tensor! perm, Tensor! workspace, "
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"int b_q_type, SymInt size_m, "
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"SymInt size_n, SymInt size_k, bool is_k_full, int num_experts, int "
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"topk, "
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"int moe_block_size, bool replicate_input, bool apply_weights)"
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" -> Tensor");
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m.def(
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"moe_permute(Tensor input, Tensor topk_weight, Tensor! topk_ids,"
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"Tensor token_expert_indicies, Tensor? expert_map, int n_expert,"
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"int n_local_expert,"
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"int topk, int? align_block_size,Tensor! permuted_input, Tensor! "
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"expert_first_token_offset, Tensor! src_row_id2dst_row_id_map, Tensor! "
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"m_indices)->()");
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m.def(
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"moe_unpermute(Tensor permuted_hidden_states, Tensor topk_weights,"
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"Tensor topk_ids,Tensor src_row_id2dst_row_id_map, Tensor "
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"expert_first_token_offset, int n_expert, int n_local_expert,int "
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"topk, Tensor! hidden_states)->()");
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// conditionally compiled so impl registration is in source file
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#endif
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