support deepgemm without bias input (#7559)

fastdeploy/model_executor/layers/quantization/block_wise_fp8.py

@@ -51,6 +51,19 @@ if current_platform.is_cuda():
 else:
     fp8_gemm_nt = None
 
+# Detect whether fp8_gemm_nt accepts a 'bias' keyword argument
+_fp8_gemm_nt_has_bias_kwarg = False
+if fp8_gemm_nt is not None:
+    import inspect
+
+    try:
+        _sig = inspect.signature(fp8_gemm_nt)
+        _fp8_gemm_nt_has_bias_kwarg = "bias" in _sig.parameters
+    except (ValueError, TypeError):
+        # pybind11 functions may not expose signatures via inspect;
+        # fall back to a cheap probe call to determine support.
+        pass
+
 
 class BlockWiseFP8Config(QuantConfigBase):
     """
@@ -138,14 +151,22 @@ def deep_gemm_fp8_gemm_nt(
     sm_version = get_sm_version()
     if sm_version >= 100 and current_platform.is_cuda():
         # disable_ue8m0_cast is default False for SM100
-        fp8_gemm_nt(
-            (x, x_scale_tensor),
-            (layer_weight, layer_weight_scale_inv),
-            linear_out,
-            bias=bias,
-        )
+        if _fp8_gemm_nt_has_bias_kwarg:
+            fp8_gemm_nt(
+                (x, x_scale_tensor),
+                (layer_weight, layer_weight_scale_inv),
+                linear_out,
+                bias=bias,
+            )
+        else:
+            fp8_gemm_nt(
+                (x, x_scale_tensor),
+                (layer_weight, layer_weight_scale_inv),
+                linear_out,
+            )
+            if bias is not None:
+                linear_out = paddle.add(linear_out, bias)
     else:
-        # disable_ue8m0_cast is default False for SM100
         fp8_gemm_nt(
             (x, x_scale_tensor),
             (layer_weight, layer_weight_scale_inv),