For nz unset in bf16&fp16 (#4495)

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### What this PR does / why we need it?
disable NZ for float weight case. This is only a quick fix for dev
branch.

For main branch, we'll consider more case to make it more common.


### Does this PR introduce _any_ user-facing change?
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Note that it means *any* user-facing change including all aspects such
as API, interface or other behavior changes.
Documentation-only updates are not considered user-facing changes.
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### How was this patch tested?
qwen2.5 32B
<img width="441" height="221" alt="image"
src="https://github.com/user-attachments/assets/7ae18ffd-1ce2-43d9-9960-be45250ad0da"
/>

---------

Signed-off-by: 刘哲续 <liuzhexu1@huawei.com>
Co-authored-by: 刘哲续 <liuzhexu1@huawei.com>

vllm_ascend/torchair/torchair_sfa.py

@@ -842,7 +842,7 @@ class AscendSFATorchairImpl(MLAAttentionImpl):
         wd_qkv = wd_qkv.t().contiguous()
         wd_qkv = transdata(wd_qkv,
                            block_size=(16, 32)).unsqueeze(0).contiguous()
-        if is_enable_nz():
+        if is_enable_nz(wd_qkv.dtype):
             self.wd_qkv = torch_npu.npu_format_cast(wd_qkv, 29)
 
         kv_a_proj_deq_scl = self.kv_a_proj_with_mqa.deq_scale.clone()
@@ -876,7 +876,7 @@ class AscendSFATorchairImpl(MLAAttentionImpl):
             self.num_heads * (self.qk_nope_head_dim + self.qk_rope_head_dim),
             -1)
         wu_q = transdata(wu_q, block_size=(16, 32)).unsqueeze(0).contiguous()
-        if is_enable_nz():
+        if is_enable_nz(wu_q.dtype):
             self.wu_q = torch_npu.npu_format_cast(wu_q, 29)
 
         qb_deq_scl = self.q_proj.deq_scale.data.clone()

vllm_ascend/torchair/utils.py

@@ -146,7 +146,7 @@ def converting_weight_acl_format(model, format):
             if torch_npu.get_npu_format(module.w13_weight.data) == format:
                 return
             if format == ACL_FORMAT_FRACTAL_NZ \
-                    and not is_enable_nz():
+                    and not is_enable_nz(module.w13_weight.data.dtype):
                 return
             module.w13_weight.data = torch_npu.npu_format_cast(
                 module.w13_weight.data, format)