Add ruff noqas as suitable

Author: akx

bitsandbytes/functional.py

@@ -230,7 +230,7 @@ def create_linear_map(signed=True, total_bits=8, add_zero=True):
     if gap == 0:
         return values
     else:
-        l = values.numel()//2
+        l = values.numel()//2  # noqa: E741
         return torch.Tensor(values[:l].tolist() + [0]*gap + values[l:].tolist())
 
 def create_normal_map(offset=0.9677083, use_extra_value=True):

bitsandbytes/research/autograd/_functions.py

@@ -184,7 +184,9 @@ def backward(ctx, grad_output):
 
 class SwitchBackBnb(torch.autograd.Function):
     @staticmethod
-    def forward(ctx, A, B, out=None, bias=None, state=MatmulLtState()):
+    # TODO: the B008 on the line below is a likely bug; the current implementation will
+    #       have each SwitchBackBnb instance share a single MatmulLtState instance!!!
+    def forward(ctx, A, B, out=None, bias=None, state=MatmulLtState()):  # noqa: B008
         # default to pytorch behavior if inputs are empty
         ctx.is_empty = False
         if prod(A.shape) == 0: