From 585aa2aeba825f67f0210e5a45dfe591edb57e96 Mon Sep 17 00:00:00 2001
From: "deepsource-autofix[bot]"
 <62050782+deepsource-autofix[bot]@users.noreply.github.com>
Date: Wed, 13 Oct 2021 00:25:59 +0200
Subject: [PATCH] Use `is` to compare type of objects

Co-authored-by: deepsource-autofix[bot] <62050782+deepsource-autofix[bot]@users.noreply.github.com>
---
 torchvision/models/quantization/googlenet.py    | 2 +-
 torchvision/models/quantization/inception.py    | 2 +-
 torchvision/models/quantization/mobilenetv2.py  | 6 +++---
 torchvision/models/quantization/mobilenetv3.py  | 6 +++---
 torchvision/models/quantization/resnet.py       | 2 +-
 torchvision/models/quantization/shufflenetv2.py | 2 +-
 torchvision/models/quantization/utils.py        | 2 +-
 7 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/torchvision/models/quantization/googlenet.py b/torchvision/models/quantization/googlenet.py
index 4b6d25e013c..6266e296c03 100644
--- a/torchvision/models/quantization/googlenet.py
+++ b/torchvision/models/quantization/googlenet.py
@@ -167,5 +167,5 @@ def fuse_model(self) -> None:
         """
 
         for m in self.modules():
-            if type(m) == QuantizableBasicConv2d:
+            if type(m) is QuantizableBasicConv2d:
                 m.fuse_model()
diff --git a/torchvision/models/quantization/inception.py b/torchvision/models/quantization/inception.py
index acad3f6df53..ea9326276f2 100644
--- a/torchvision/models/quantization/inception.py
+++ b/torchvision/models/quantization/inception.py
@@ -247,5 +247,5 @@ def fuse_model(self) -> None:
         """
 
         for m in self.modules():
-            if type(m) == QuantizableBasicConv2d:
+            if type(m) is QuantizableBasicConv2d:
                 m.fuse_model()
diff --git a/torchvision/models/quantization/mobilenetv2.py b/torchvision/models/quantization/mobilenetv2.py
index a2c88cdd388..8626de19aab 100644
--- a/torchvision/models/quantization/mobilenetv2.py
+++ b/torchvision/models/quantization/mobilenetv2.py
@@ -30,7 +30,7 @@ def forward(self, x: Tensor) -> Tensor:
 
     def fuse_model(self) -> None:
         for idx in range(len(self.conv)):
-            if type(self.conv[idx]) == nn.Conv2d:
+            if type(self.conv[idx]) is nn.Conv2d:
                 fuse_modules(self.conv, [str(idx), str(idx + 1)], inplace=True)
 
 
@@ -54,9 +54,9 @@ def forward(self, x: Tensor) -> Tensor:
 
     def fuse_model(self) -> None:
         for m in self.modules():
-            if type(m) == ConvNormActivation:
+            if type(m) is ConvNormActivation:
                 fuse_modules(m, ["0", "1", "2"], inplace=True)
-            if type(m) == QuantizableInvertedResidual:
+            if type(m) is QuantizableInvertedResidual:
                 m.fuse_model()
 
 
diff --git a/torchvision/models/quantization/mobilenetv3.py b/torchvision/models/quantization/mobilenetv3.py
index ad195d178c7..e19912e25b0 100644
--- a/torchvision/models/quantization/mobilenetv3.py
+++ b/torchvision/models/quantization/mobilenetv3.py
@@ -99,12 +99,12 @@ def forward(self, x: Tensor) -> Tensor:
 
     def fuse_model(self) -> None:
         for m in self.modules():
-            if type(m) == ConvNormActivation:
+            if type(m) is ConvNormActivation:
                 modules_to_fuse = ["0", "1"]
-                if len(m) == 3 and type(m[2]) == nn.ReLU:
+                if len(m) == 3 and type(m[2]) is nn.ReLU:
                     modules_to_fuse.append("2")
                 fuse_modules(m, modules_to_fuse, inplace=True)
-            elif type(m) == QuantizableSqueezeExcitation:
+            elif type(m) is QuantizableSqueezeExcitation:
                 m.fuse_model()
 
 
diff --git a/torchvision/models/quantization/resnet.py b/torchvision/models/quantization/resnet.py
index f7124798254..596ae56d85b 100644
--- a/torchvision/models/quantization/resnet.py
+++ b/torchvision/models/quantization/resnet.py
@@ -104,7 +104,7 @@ def fuse_model(self) -> None:
 
         fuse_modules(self, ["conv1", "bn1", "relu"], inplace=True)
         for m in self.modules():
-            if type(m) == QuantizableBottleneck or type(m) == QuantizableBasicBlock:
+            if type(m) is QuantizableBottleneck or type(m) is QuantizableBasicBlock:
                 m.fuse_model()
 
 
diff --git a/torchvision/models/quantization/shufflenetv2.py b/torchvision/models/quantization/shufflenetv2.py
index a4c4aede665..76920433399 100644
--- a/torchvision/models/quantization/shufflenetv2.py
+++ b/torchvision/models/quantization/shufflenetv2.py
@@ -68,7 +68,7 @@ def fuse_model(self) -> None:
             if name in ["conv1", "conv5"]:
                 torch.quantization.fuse_modules(m, [["0", "1", "2"]], inplace=True)
         for m in self.modules():
-            if type(m) == QuantizableInvertedResidual:
+            if type(m) is QuantizableInvertedResidual:
                 if len(m.branch1._modules.items()) > 0:
                     torch.quantization.fuse_modules(m.branch1, [["0", "1"], ["2", "3", "4"]], inplace=True)
                 torch.quantization.fuse_modules(
diff --git a/torchvision/models/quantization/utils.py b/torchvision/models/quantization/utils.py
index 74a8287030b..22edee47621 100644
--- a/torchvision/models/quantization/utils.py
+++ b/torchvision/models/quantization/utils.py
@@ -9,7 +9,7 @@ def _replace_relu(module: nn.Module) -> None:
         # Checking for explicit type instead of instance
         # as we only want to replace modules of the exact type
         # not inherited classes
-        if type(mod) == nn.ReLU or type(mod) == nn.ReLU6:
+        if type(mod) is nn.ReLU or type(mod) is nn.ReLU6:
             reassign[name] = nn.ReLU(inplace=False)
 
     for key, value in reassign.items():