minor simplify

nanovllm/layers/activation.py

@@ -5,9 +5,6 @@ import torch.nn.functional as F
 
 class SiluAndMul(nn.Module):
 
-    def __init__(self):
-        super().__init__()
-
     @torch.compile
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         x, y = x.chunk(2, -1)

nanovllm/layers/linear.py

@@ -141,8 +141,7 @@ class RowParallelLinear(LinearBase):
 
     def weight_loader(self, param: nn.Parameter, loaded_weight: torch.Tensor):
         param_data = param.data
-        if param_data.dim() == 1:
-            # bias is not sharded in RowParallelLinear
+        if param_data.ndim == 1:
             param_data.copy_(loaded_weight)
             return
         shard_size = param_data.size(self.tp_dim)

nanovllm/layers/sampler.py

@@ -4,9 +4,6 @@ from torch import nn
 
 class Sampler(nn.Module):
 
-    def __init__(self):
-        super().__init__()
-
     @torch.compile
     def forward(self, logits: torch.Tensor, temperatures: torch.Tensor):
         logits = logits.float().div_(temperatures.unsqueeze(dim=1))