[refactor] refactor excute_model and _dymmy_run method (#6043)

### What this PR does / why we need it?
The structure of the `excute_model` and `_dymmy_run` methods in
NPUModelRunner differs greatly from that in GPUModelRunner.
Achieve alignment with GPUModelRunner:
Split the `_prepare_inputs` method into `_prepare_inputs`,
`_determine_batch_execution_and_padding`, `_build_attention_metadata`,
and `_preprocess`.
Modify `_generate_process_reqs_hidden_states` to `_model_forward`.
Align the implementation of the `postprocess` phase

**Related-RFC**: https://github.com/vllm-project/vllm-ascend/issues/5449

**Co-authored-by**: @zhenwenqi2024 
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?

- vLLM version: v0.13.0
- vLLM main:
d68209402d

---------

Signed-off-by: Wang Kunpeng <1289706727@qq.com>
Signed-off-by: gcanlin <canlinguosdu@gmail.com>
Signed-off-by: zhenwenqi2024 <zhenwenqi_2022@qq.com>
Co-authored-by: gcanlin <canlinguosdu@gmail.com>
Co-authored-by: zhenwenqi2024 <zhenwenqi_2022@qq.com>

vllm_ascend/attention/sfa_v1.py

@@ -170,7 +170,7 @@ class AscendSFAMetadataBuilder(MLACommonMetadataBuilder[AscendSFAMetadata]):
                 npu_fused_infer_attention_score TND layout's limit of 16, \
                 got {self.decode_threshold}"
             )
-
+        self.reorder_batch_threshold = self.decode_threshold
         self.attn_mask_builder = AttentionMaskBuilder(self.device)
         self.rope_dim = self.model_config.hf_text_config.qk_rope_head_dim
         self.enable_dsa_cp = enable_dsa_cp()