Fix W8A8 fused moe bug (#1529)

### What this PR does / why we need it?
1. drop some useless code for w8a8 fusedmoe
2. Add in8 kv cache check
3. Add more ut.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
CI passed with new added test.

---------

Signed-off-by: zhuyilin <809721801@qq.com>
Signed-off-by: tianyitang <tangtianyi4@huawei.com>
Co-authored-by: tianyitang <tangtianyi4@huawei.com>

vllm_ascend/attention/attention_v1.py

@@ -274,6 +274,8 @@ class AscendAttentionBackendImpl(AttentionImpl):
             shape = [batch_size * seq_len, num_heads, head_size]
         """
         num_tokens = query.shape[0]
+        use_kv_cache_int8 = kv_cache.numel(
+        ) > 0 and kv_cache[0].dtype == torch.int8
         if output is None:
             output = torch.empty(num_tokens,
                                  self.num_heads,
@@ -289,7 +291,7 @@ class AscendAttentionBackendImpl(AttentionImpl):
                 output=output,
                 layer_name=layer.layer_name)
 
-        elif hasattr(layer, 'quant_method'):
+        elif hasattr(layer, 'quant_method') and use_kv_cache_int8:
             output = layer.quant_method.apply(layer, query, key, value,
                                               kv_cache, attn_metadata,
                                               self.attn_type, self.scale,
@@ -429,7 +431,7 @@ class AscendAttentionBackendImpl(AttentionImpl):
                         out=output)
 
         # to make in-place change to the output tensor
-        if hasattr(layer, 'quant_method'):
+        if hasattr(layer, 'quant_method') and use_kv_cache_int8:
             output = output.view(num_tokens, self.num_heads, self.head_size)
         ori_output[:, :, :] = output[:num_tokens, :, :]
         return output.view(num_tokens, self.hidden_size)