support pangumoe w8a8c8 and docs (#1477)

### What this PR does / why we need it?
support pangu moe w8a8c8

### 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>

vllm_ascend/attention/attention_v1.py

@@ -69,6 +69,15 @@ class AscendAttentionBackend(AttentionBackend):
                     16)
         return (2, num_blocks, block_size, num_kv_heads, head_size)
 
+    @staticmethod
+    def get_bsh_kv_cache_shape(
+        num_blocks: int,
+        block_size: int,
+        num_kv_heads: int,
+        head_size: int,
+    ) -> Tuple[int, ...]:
+        return (2, num_blocks, block_size, num_kv_heads * head_size)
+
     @staticmethod
     def swap_blocks(
         src_kv_cache: List[torch.Tensor],
@@ -279,6 +288,13 @@ class AscendAttentionBackendImpl(AttentionImpl):
                 value=value,
                 output=output,
                 layer_name=layer.layer_name)
+
+        elif hasattr(layer, 'quant_method'):
+            output = layer.quant_method.apply(layer, query, key, value,
+                                              kv_cache, attn_metadata,
+                                              self.attn_type, self.scale,
+                                              output)
+
         else:
             if attn_metadata is None:
                 return output.view(num_tokens, self.hidden_size)
@@ -308,11 +324,8 @@ class AscendAttentionBackendImpl(AttentionImpl):
                     value_cache=self.value_cache,
                     slot_indices=slots)
 
-            if hasattr(layer, 'quant_method'):
-                # TODO: Add attr (num_prefills, prefill_metadata, decode_metadata) to AscendMetadata
-                pass
             # V0-Style scheduler situation.
-            elif attn_metadata.attn_state == AscendAttentionState.PrefillNoCache:
+            if attn_metadata.attn_state == AscendAttentionState.PrefillNoCache:
                 assert attn_metadata is not None
                 assert attn_metadata.attn_mask is not None
                 mask = attn_metadata.attn_mask
@@ -414,6 +427,8 @@ class AscendAttentionBackendImpl(AttentionImpl):
                         out=output)
 
         # to make in-place change to the output tensor
+        if hasattr(layer, 'quant_method'):
+            output = output.view(num_tokens, self.num_heads, self.head_size)
         ori_output[:, :, :] = output[:num_tokens, :, :]
         return output.view(num_tokens, self.hidden_size)