Adding typing.

Author: datumbox

torchvision/models/efficientnet.py

@@ -19,7 +19,7 @@
 }
 
 
-def drop_connect(x: Tensor, rate: float):
+def drop_connect(x: Tensor, rate: float) -> Tensor:
     keep = torch.rand(size=(x.size(0), ), dtype=x.dtype, device=x.device) > rate
     keep = keep[(None, ) * (x.ndim - 1)].T
     return (x / (1.0 - rate)) * keep
@@ -29,7 +29,7 @@ class MBConvConfig:
     def __init__(self,
                  kernel: int, stride: int, dilation: int,
                  input_channels: int, out_channels: int, expand_ratio: float,
-                 width_mult: float):
+                 width_mult: float) -> None:
         self.kernel = kernel
         self.stride = stride
         self.dilation = dilation
@@ -38,13 +38,13 @@ def __init__(self,
         self.expanded_channels = self.adjust_channels(input_channels, expand_ratio * width_mult)
 
     @staticmethod
-    def adjust_channels(channels: int, width_mult: float, min_value: Optional[int] = None):
+    def adjust_channels(channels: int, width_mult: float, min_value: Optional[int] = None) -> int:
         return _make_divisible(channels * width_mult, 8, min_value)
 
 
 class MBConv(nn.Module):
     def __init__(self, cnf: MBConvConfig, norm_layer: Callable[..., nn.Module],
-                 se_layer: Callable[..., nn.Module] = SqueezeExcitation):
+                 se_layer: Callable[..., nn.Module] = SqueezeExcitation) -> None:
         super().__init__()
         if not (1 <= cnf.stride <= 2):
             raise ValueError('illegal stride value')