[ROCm][Quantization] add fp8xfp8 attn support for rocm_aiter_unified_attn (#36927)

Signed-off-by: Divakar Verma <divakar.verma@amd.com>

vllm/v1/attention/backends/rocm_aiter_unified_attn.py

@@ -125,6 +125,7 @@ class RocmAiterUnifiedAttentionImpl(RocmAttentionImpl):
         from aiter.ops.triton.unified_attention import unified_attention
 
         self.unified_attention = unified_attention
+        self.supports_quant_query_input = True
 
     def forward(
         self,
@@ -190,12 +191,20 @@ class RocmAiterUnifiedAttentionImpl(RocmAttentionImpl):
 
         key_cache, value_cache = kv_cache.unbind(0)
 
+        softmax_scale = self.scale
+        fp8_post_attn_v_rescale = False
         if self.kv_cache_dtype.startswith("fp8"):
             key_cache = key_cache.view(self.fp8_dtype)
             value_cache = value_cache.view(self.fp8_dtype)
-            assert layer._q_scale_float == 1.0, (
-                "A non 1.0 q_scale is not currently supported."
-            )
+            # When Q is FP8, triton kernel skips K/V dequant (for fp8xfp8 matmul).
+            # Compensate by absorbing q_scale and k_scale into softmax_scale, and
+            # v_scale into output_scale (or post-multiplying if no fusion).
+            if query.dtype == self.fp8_dtype:
+                softmax_scale = self.scale * layer._q_scale_float * layer._k_scale_float
+                if output_scale is not None:
+                    output_scale = output_scale / layer._v_scale_float
+                else:
+                    fp8_post_attn_v_rescale = True
 
         cu_seqlens_q = attn_metadata.query_start_loc
         seqused_k = attn_metadata.seq_lens
@@ -217,19 +226,22 @@ class RocmAiterUnifiedAttentionImpl(RocmAttentionImpl):
             max_seqlen_q=max_seqlen_q,
             seqused_k=seqused_k,
             max_seqlen_k=max_seqlen_k,
-            softmax_scale=self.scale,
+            softmax_scale=softmax_scale,
             causal=True,
             alibi_slopes=self.alibi_slopes,
             window_size=self.sliding_window,
             block_table=block_table,
             softcap=self.logits_soft_cap,
-            q_descale=None,  # Not supported
+            q_descale=None,  # q_scale absorbed into softmax_scale
             k_descale=layer._k_scale.expand(descale_shape),
             v_descale=layer._v_scale.expand(descale_shape),
             sinks=self.sinks,
             output_scale=output_scale,
         )
 
+        if fp8_post_attn_v_rescale:
+            output[:num_actual_tokens].mul_(layer._v_scale_float)
+
         return output
 
     def do_kv_cache_update(