fix black

Author: refraction-ray

tensorcircuit/interfaces/torch.py

@@ -65,7 +65,7 @@ def vjp_fun(x: Tensor, v: Tensor) -> Tuple[Tensor, Tensor]:
         fun = backend.jit(fun)
         vjp_fun = backend.jit(vjp_fun)
 
-    class Fun(torch.autograd.Function):
+    class Fun(torch.autograd.Function):  # type: ignore
         @staticmethod
         def forward(ctx: Any, *x: Any) -> Any:  # type: ignore
             # ctx.xdtype = [xi.dtype for xi in x]
@@ -111,7 +111,7 @@ def backward(ctx: Any, *grad_y: Any) -> Any:
             return r
 
     # currently, memory transparent dlpack in these ML framework has broken support on complex dtypes
-    return Fun.apply
+    return Fun.apply  # type: ignore
 
 
 pytorch_interface = torch_interface

tensorcircuit/quantum.py

@@ -1705,7 +1705,6 @@ def reduced_density_matrix(
         if normalize:
             rho /= backend.trace(rho)
 
-
     else:
         w = state / backend.norm(state)
         freedomexp = backend.sizen(state)

tensorcircuit/torchnn.py

@@ -13,7 +13,7 @@
 Tensor = Any
 
 
-class QuantumNet(torch.nn.Module):
+class QuantumNet(torch.nn.Module):  # type: ignore
     def __init__(
         self,
         f: Callable[..., Any],