diff --git a/ex_engine/python/xllm_ops.py b/ex_engine/python/xllm_ops.py index 79347e68..118dead0 100644 --- a/ex_engine/python/xllm_ops.py +++ b/ex_engine/python/xllm_ops.py @@ -131,7 +131,7 @@ def paged_attention(out, query, key_cache, value_cache, block_size, max_context_len, alibi_slopes=None): """Paged attention decode. .so export: ix_paged_attention in ix_moe_bridge.so.""" bridge = _get("ix_moe_bridge") - return bridge.ix_paged_attention( + return bridge.paged_attention( out, query, key_cache, value_cache, scale, block_tables, context_lens, block_size, max_context_len, max_context_len, alibi_slopes @@ -166,7 +166,7 @@ def moe_compute_token_index(sorted_token_ids, expert_ids, num_tokens_post_padded def ixformer_linear(input, weight, act_type=0, bias=None, out=None): """GEMM via ixformer. .so export: ix_linear in ix_moe_bridge.so.""" bridge = _get("ix_moe_bridge") - return bridge.ix_linear(input, weight, bias) + return bridge.linear(input, weight, bias) # --- Fused QK-Norm + RoPE --- def fused_qknorm_rope(query, key, cos_sin_cache, positions, diff --git a/qwen3_6_scripts/ex_engine/python/xllm_ops.py b/qwen3_6_scripts/ex_engine/python/xllm_ops.py index 79347e68..118dead0 100644 --- a/qwen3_6_scripts/ex_engine/python/xllm_ops.py +++ b/qwen3_6_scripts/ex_engine/python/xllm_ops.py @@ -131,7 +131,7 @@ def paged_attention(out, query, key_cache, value_cache, block_size, max_context_len, alibi_slopes=None): """Paged attention decode. .so export: ix_paged_attention in ix_moe_bridge.so.""" bridge = _get("ix_moe_bridge") - return bridge.ix_paged_attention( + return bridge.paged_attention( out, query, key_cache, value_cache, scale, block_tables, context_lens, block_size, max_context_len, max_context_len, alibi_slopes @@ -166,7 +166,7 @@ def moe_compute_token_index(sorted_token_ids, expert_ids, num_tokens_post_padded def ixformer_linear(input, weight, act_type=0, bias=None, out=None): """GEMM via ixformer. .so export: ix_linear in ix_moe_bridge.so.""" bridge = _get("ix_moe_bridge") - return bridge.ix_linear(input, weight, bias) + return bridge.linear(input, weight, bias) # --- Fused QK-Norm + RoPE --- def fused_qknorm_rope(query, key, cos_sin_cache, positions,