fix: remove cublas_grouped_gemm (#5307)

sgl-kernel/python/sgl_kernel/__init__.py

@@ -25,7 +25,6 @@ from sgl_kernel.elementwise import (
 from sgl_kernel.gemm import (
     awq_dequantize,
     bmm_fp8,
-    cublas_grouped_gemm,
     cutlass_scaled_fp4_mm,
     fp8_blockwise_scaled_mm,
     fp8_scaled_mm,

sgl-kernel/python/sgl_kernel/gemm.py

@@ -121,26 +121,6 @@ def sgl_per_tensor_quant_fp8(
     )
 
 
-def cublas_grouped_gemm(
-    inputs: List[torch.Tensor],
-    weights: List[torch.Tensor],
-    outputs: List[torch.Tensor],
-    out_dtype: torch.dtype,
-) -> None:
-    assert (
-        len(inputs) > 0 and len(weights) > 0 and len(outputs) > 0
-    ), "Inputs/weights/outputs should not be empty!"
-    cublas_handle = torch.cuda.current_blas_handle()
-    torch.ops.sgl_kernel.cublas_grouped_gemm.default(
-        inputs,
-        weights,
-        outputs,
-        out_dtype,
-        cublas_handle,
-        get_cuda_stream(),
-    )
-
-
 def sgl_per_token_quant_fp8(
     input: torch.Tensor,
     output_q: torch.Tensor,