[Bugfix/CI] Fix broken kernels/test_mha.py (#12450)

tests/kernels/test_mha_attn.py

@@ -26,7 +26,7 @@ def clear_cache():
 @pytest.mark.parametrize("device", ["cpu", "hip", "cuda"])
 def test_mha_attn_platform(device: str):
     """
-    Test that the attention selector between different platform and device.
+    Test the attention selector between different platform and device.
     """
     torch.set_default_dtype(torch.float16)
 
@@ -41,7 +41,7 @@ def test_mha_attn_platform(device: str):
     else:
         with patch("vllm.attention.selector.current_platform", CudaPlatform()):
             attn = MultiHeadAttention(16, 64, scale=1)
-            assert attn.attn_backend == _Backend.FLASH_ATTN
+            assert attn.attn_backend == _Backend.XFORMERS
 
         with patch("vllm.attention.selector.current_platform", CudaPlatform()):
             attn = MultiHeadAttention(16, 72, scale=1)

vllm/attention/layer.py

@@ -210,6 +210,9 @@ class MultiHeadAttention(nn.Module):
         self.scale = scale
         self.num_kv_heads = num_heads if num_kv_heads is None else num_kv_heads
 
+        assert self.num_heads % self.num_kv_heads == 0
+        self.num_queries_per_kv = self.num_heads // self.num_kv_heads
+
         dtype = torch.get_default_dtype()
         attn_backend = get_attn_backend(head_size,
                                         dtype,
@@ -240,6 +243,11 @@ class MultiHeadAttention(nn.Module):
         key = key.view(bsz, kv_len, self.num_kv_heads, self.head_size)
         value = value.view(bsz, kv_len, self.num_kv_heads, self.head_size)
 
+        if (num_repeat := self.num_queries_per_kv) > 1:
+            # Handle MQA and GQA
+            key = torch.repeat_interleave(key, num_repeat, dim=2)
+            value = torch.repeat_interleave(value, num_repeat, dim=2)
+
         if self.attn_backend == _Backend.XFORMERS:
             from xformers import ops as xops