[Bugfix] Fix zero attention output in qwen3-next (#3572)

### What this PR does / why we need it?
Since Attention and LinearAttention share the same ```slot_mapping```,
and the ```slot_mapping``` for LinearAttention is all zeros, the
```slot_mapping``` for Attention gets overwritten, resulting in the
computed output being all zeros.

This PR removes the uniformly managed ```self.slot_mapping``` and
directly passes the ```slot_mapping``` from ```input_batch.blocktable```
to ```attn_metadata```, along with modifying the relevant references.
Due to hardware, the data type of ```block_table.slot_mapping``` needs
to be set to int32.

### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed with existing test.

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

Signed-off-by: QilaiZhang <245706640@qq.com>

vllm_ascend/spec_decode/eagle_proposer.py

@@ -359,7 +359,8 @@ class EagleProposer(Proposer):
                 actual_seq_lengths_q=self.runner.actual_seq_lengths_q,
                 block_table_tensor=self.runner.input_batch.block_table[0].
                 get_device_tensor(),
-                slot_mapping=self.runner.slot_mapping,
+                slot_mapping=self.runner.input_batch.block_table[0].
+                slot_mapping,
                 positions=self.runner.positions,
                 attn_mask=self.runner.attn_mask,
                 spec_attn_mask=self.runner.spec_attn_mask,