[Kernel] AQ AZP 4/4: Integrate asymmetric quantization to linear method (#7271)

vllm/model_executor/layers/quantization/utils/w8a8_utils.py

@@ -191,13 +191,28 @@ def apply_int8_linear(
     weight: torch.Tensor,
     weight_scale: torch.Tensor,
     input_scale: Optional[torch.Tensor] = None,
+    input_zero_point: Optional[torch.Tensor] = None,
+    azp_adj: Optional[torch.Tensor] = None,
     bias: Optional[torch.Tensor] = None,
 ):
     # ops.scaled_int8_quant supports both dynamic and static quant.
     # * dynamic, layer.input_scale is None and x_scale computed from x.
     # * static, layer.input_scale is scalar and x_scale is input_scale.
-    x_q, x_scale, _ = ops.scaled_int8_quant(input, input_scale)
+    symmetric = azp_adj is None
+    x_q, x_scale, x_zp = ops.scaled_int8_quant(input,
+                                               input_scale,
+                                               input_zero_point,
+                                               symmetric=symmetric)
 
+    if x_zp is not None:
+        return ops.cutlass_scaled_mm_azp(x_q,
+                                         weight,
+                                         scale_a=x_scale,
+                                         scale_b=weight_scale,
+                                         out_dtype=input.dtype,
+                                         azp_adj=azp_adj,
+                                         azp=x_zp,
+                                         bias=bias)
     return ops.cutlass_scaled_mm(x_q,
                                  weight,
                                  scale_a=x_scale,