Remove dependency from functool in ShuffleNetsV2 (#916)

* Remove dependency from functool in ShuffleNetsV2

This PR removes the dependence of the ShuffleNetV2 code from `functool`.

* flake fix

torchvision/models/shufflenetv2.py

-import functools
-
 import torch
 import torch.nn as nn
 from .utils import load_state_dict_from_url
@@ -45,26 +43,23 @@ class InvertedResidual(nn.Module):
         branch_features = oup // 2
         assert (self.stride != 1) or (inp == branch_features << 1)
 
-        pw_conv11 = functools.partial(nn.Conv2d, kernel_size=1, stride=1, padding=0, bias=False)
-        dw_conv33 = functools.partial(self.depthwise_conv,
-                                      kernel_size=3, stride=self.stride, padding=1)
-
         if self.stride > 1:
             self.branch1 = nn.Sequential(
-                dw_conv33(inp, inp),
+                self.depthwise_conv(inp, inp, kernel_size=3, stride=self.stride, padding=1),
                 nn.BatchNorm2d(inp),
-                pw_conv11(inp, branch_features),
+                nn.Conv2d(inp, branch_features, kernel_size=1, stride=1, padding=0, bias=False),
                 nn.BatchNorm2d(branch_features),
                 nn.ReLU(inplace=True),
             )
 
         self.branch2 = nn.Sequential(
-            pw_conv11(inp if (self.stride > 1) else branch_features, branch_features),
+            nn.Conv2d(inp if (self.stride > 1) else branch_features,
+                      branch_features, kernel_size=1, stride=1, padding=0, bias=False),
             nn.BatchNorm2d(branch_features),
             nn.ReLU(inplace=True),
-            dw_conv33(branch_features, branch_features),
+            self.depthwise_conv(branch_features, branch_features, kernel_size=3, stride=self.stride, padding=1),
             nn.BatchNorm2d(branch_features),
-            pw_conv11(branch_features, branch_features),
+            nn.Conv2d(branch_features, branch_features, kernel_size=1, stride=1, padding=0, bias=False),
             nn.BatchNorm2d(branch_features),
             nn.ReLU(inplace=True),
         )