feat: support sm75 with FlashInfer v0.1.6 (#1233)

python/sglang/srt/layers/activation.py

@@ -30,18 +30,11 @@ from vllm.model_executor.utils import set_weight_attrs
 
 
 class SiluAndMul(CustomOp):
-    def __init__(self, **kwargs):
-        super().__init__()
-        self.is_lower_sm80 = torch.cuda.get_device_capability()[0] < 8
-
     def forward_native(self, x: torch.Tensor) -> torch.Tensor:
         d = x.shape[-1] // 2
         return F.silu(x[..., :d]) * x[..., d:]
 
     def forward_cuda(self, x: torch.Tensor) -> torch.Tensor:
-        if self.is_lower_sm80:
-            return self.forward_native(x)
-
         d = x.shape[-1] // 2
         output_shape = x.shape[:-1] + (d,)
         out = torch.empty(output_shape, dtype=x.dtype, device=x.device)

python/sglang/srt/layers/layernorm.py

@@ -32,15 +32,12 @@ class RMSNorm(CustomOp):
         super().__init__()
         self.weight = nn.Parameter(torch.ones(hidden_size))
         self.variance_epsilon = eps
-        self.is_lower_sm80 = torch.cuda.get_device_capability()[0] < 8
 
     def forward_cuda(
         self,
         x: torch.Tensor,
         residual: Optional[torch.Tensor] = None,
     ) -> Union[torch.Tensor, Tuple[torch.Tensor, torch.Tensor]]:
-        if self.is_lower_sm80:
-            return self.forward_native(x, residual)
 
         if residual is not None:
             fused_add_rmsnorm(x, residual, self.weight.data, self.variance_epsilon)