[Bugfix] Disable torch.compile() (#370)

### What this PR does / why we need it?
To resolve this
[patch](https://github.com/vllm-project/vllm-ascend/pull/236/files#diff-43b96b39b5a52fe209d86449ad703a7ff5e1349ebaf1aa12ece8d82163ee5b61R24-R49)
, we need to set `torch.compile()` backend to `eager` to disable
compile, using default pytorch way.


---------

Signed-off-by: shen-shanshan <467638484@qq.com>

vllm_ascend/attention/attention.py

@@ -988,7 +988,7 @@ class AscendMLAAttentionBackendImpl(MLAAttentionImpl):
                                       self.num_heads,
                                       self.v_head_dim,
                                       dtype=query.dtype,
-                                      device="npu")
+                                      device=query.device)
             if (attn_metadata.block_tables is None
                     or attn_metadata.block_tables.numel() == 0):
                 assert attn_metadata.attn_mask is not None
@@ -1015,11 +1015,12 @@ class AscendMLAAttentionBackendImpl(MLAAttentionImpl):
                 )
         elif attn_metadata.decode_metadata:
             assert kv_cache is not None
-            attn_output = torch.empty(num_tokens,
-                                      self.num_heads,
-                                      self.kv_lora_rank,
-                                      dtype=query.dtype,
-                                      device="npu")
+            # if torch.empty is used here, the preemptive scheduling case of
+            # test_mtp_correctness.py will fail to run.
+            attn_output = torch.randn(
+                [num_tokens, self.num_heads, self.kv_lora_rank],
+                dtype=query.dtype,
+                device=query.device)
             self.seq_lens_tensor_cpu = torch.from_numpy(
                 np.array(attn_metadata.decode_metadata.seq_lens).astype(
                     np.int32))