[Model] Support DeepSeek-V4

vllm_mlu/lora/layers/column_parallel_linear.py

@@ -0,0 +1,39 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-MLU project
+
+import torch
+
+from vllm.lora.layers.column_parallel_linear import ColumnParallelLinearWithLoRA
+from vllm_mlu.mlu_hijack_utils import MluHijackObject
+
+
+vllm__lora__layers__column_parallel_linear__ColumnParallelLinearWithLoRA__forward_org = ColumnParallelLinearWithLoRA.forward
+
+
+'''
+=============================
+Modify by vllm_mlu
+=============================
+@brief: add smooth_quant_scale and use_tp_weight parameters.
+'''
+def vllm__lora__layers__column_parallel_linear__ColumnParallelLinearWithLoRA__forward(
+    self,
+    input_,
+    smooth_quant_scale: torch.Tensor | None = None,
+    use_tp_weight: bool = False,
+) -> torch.Tensor | tuple[torch.Tensor, torch.Tensor | None]:
+    assert not use_tp_weight, "LoRa does not support use_tp_weight yet."
+    assert smooth_quant_scale is None, "LoRA does not support smooth quant yet."
+    return vllm__lora__layers__column_parallel_linear__ColumnParallelLinearWithLoRA__forward_org(self, input_)
+'''
+==================
+End of MLU Hijack
+==================
+'''
+
+
+MluHijackObject.apply_hijack(
+    ColumnParallelLinearWithLoRA,
+    ColumnParallelLinearWithLoRA.forward,
+    vllm__lora__layers__column_parallel_linear__ColumnParallelLinearWithLoRA__forward,
+)