[Model][2/N] Remove deepseek_mtp modeling. (#3561)

This PR is step 2 of deepseek model refactoring and removes
deepseek_mtp.

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: whx-sjtu <2952154980@qq.com>

vllm_ascend/attention/mla_v1.py

@@ -11,6 +11,7 @@ from vllm.attention.backends.abstract import (AttentionBackend,
 from vllm.config import VllmConfig, get_current_vllm_config
 from vllm.distributed import get_tensor_model_parallel_world_size
 from vllm.forward_context import ForwardContext, get_forward_context
+from vllm.logger import logger
 from vllm.model_executor.layers.linear import (LinearBase,
                                                UnquantizedLinearMethod)
 from vllm.utils import cdiv, round_down
@@ -29,6 +30,7 @@ from vllm_ascend.multistream.base import MSAttentionMetadataSplitConfig
 from vllm_ascend.multistream.context import get_multistream_comm_context
 from vllm_ascend.multistream.ms_split import model_input_split_v1_mla_attn
 from vllm_ascend.ops.weight_prefetch import maybe_npu_prefetch
+from vllm_ascend.quantization.w8a8 import AscendW8A8LinearMethod
 from vllm_ascend.utils import (ACL_FORMAT_FRACTAL_ND, ACL_FORMAT_FRACTAL_NZ,
                                is_enable_nz)
 from vllm_ascend.worker.npu_input_batch import InputBatch
@@ -557,6 +559,7 @@ class AscendMLAImpl(MLAAttentionImpl):
         self.prefill_mask = None
 
         self.speculative_config = vllm_config.speculative_config
+        self.enable_mlapo = envs.VLLM_ASCEND_ENABLE_MLAPO
 
     def _v_up_proj(self, x):
         if self.W_UV.shape[0] * self.W_UV.shape[1] < 65536:
@@ -654,7 +657,17 @@ class AscendMLAImpl(MLAAttentionImpl):
         # self.W_UV.data = torch_npu.npu_format_cast(self.W_UV.data, 29)
         # self.W_UK_T.data = torch_npu.npu_format_cast(self.W_UK_T.data, 29)
 
-        if envs.VLLM_ASCEND_ENABLE_MLAPO:
+        # Currently mlapo only supports W8A8 quantization in MLA scenario
+        # TODO(whx): modify this limitation when mlapo supports floating point
+        if self.fused_qkv_a_proj is None or not isinstance(
+                getattr(self.fused_qkv_a_proj.quant_method, 'quant_method',
+                        None), AscendW8A8LinearMethod):
+            self.enable_mlapo = False
+            logger.warning(
+                "Currently mlapo only supports W8A8 quantization in MLA scenario."
+                "Some layers in your model are not quantized with W8A8,"
+                "thus mlapo is disabled for these layers.")
+        if self.enable_mlapo:
             self._process_weights_for_fused_mlapo(act_dtype)
 
     def _process_weights_for_fused_mlapo(self, act_dtype: torch.dtype):
@@ -1229,7 +1242,7 @@ class AscendMLAImpl(MLAAttentionImpl):
 
         # MLA Preprocess
         forward_context = get_forward_context()
-        if (envs.VLLM_ASCEND_ENABLE_MLAPO and
+        if (self.enable_mlapo and
             (attn_metadata is None or not forward_context.with_prefill)):
             decode_preprocess_res, prefill_preprocess_res = self._mla_decode_preprocess(
                 hidden_states, kv_cache, attn_metadata)