Enable dequant fp8 weights quantized per-channel with compressed-tensor method

Signed-off-by: mandy-li <[email protected]>

Author: mandy-li

vllm_gaudi/ops/hpu_compressed_tensors.py

@@ -88,6 +88,16 @@ def get_hpu_scheme(self, layer: torch.nn.Module):
             raise ValueError(f"{scheme_classname} compressed format is not supported on HPU")
         return hpu_scheme
 
+    def dequant_fp8_weight(self, layer: torch.nn.Module) -> torch.Tensor:
+        if layer.scheme.strategy == QuantizationStrategy.CHANNEL.value:  # weights were quantized per-channel
+            dequant_weight = layer.weight.to(layer.weight_scale.dtype) * layer.weight_scale.squeeze()
+            return dequant_weight.to(torch.bfloat16).t()
+        else:
+            raise NotImplementedError("Implemented per-channel dequantization only")
+
+    def get_dequant_weights_func(self, ) -> Optional[Callable[[torch.nn.Module], torch.Tensor]]:
+        return self.dequant_fp8_weight
+
 
 @CustomOp.register_oot(name='CompressedTensorsW8A16Fp8')
 class HPUCompressedTensorsW8A8Fp8(CompressedTensorsScheme):