Bump torchfix from 0.1.1 to 0.5.0 (#3220)

Summary:
Bumps [torchfix](https://github.com/pytorch-labs/torchfix) from 0.1.1 to 0.5.0.
<details>
<summary>Release notes</summary>
<p><em>Sourced from <a href="https://github.com/pytorch-labs/torchfix/releases">torchfix's releases</a>.</em></p>
<blockquote>
<h2>TorchFix 0.5.0</h2>
<ul>
<li>Added rule TOR203 to replace 'import torchvision.models as models' with 'from torchvision import models'</li>
<li>Added rules TOR104 and TOR105 for calling and importing non-public PyTorch functions that have known public aliases</li>
<li>Added rules TOR004 and TOR103 for importing removed and deprecated functions (in addition to the existing rules for calling those functions)</li>
<li>Fixed loading for deprecated symbols config in zipped deployments</li>
<li>Done several smaller bug fixes and refactorings</li>
</ul>
<h2>TorchFix 0.4.0</h2>
<ul>
<li>Improvements for the standalone <code>torchfix</code> command:
<ul>
<li>Added  <code>--version</code> flag</li>
<li><code>--select</code> flag now accepts specific rules, not just <code>ALL</code></li>
<li>Fixed excessive debug output on MacOS</li>
</ul>
</li>
<li>Added PyTorch-internal rule TOR901</li>
<li>TorchFix explicitly requires at least Python 3.9 now</li>
<li>Small clean-ups and bugfixes</li>
</ul>
<h2>TorchFix 0.3.0</h2>
<ul>
<li>Added rule TOR003 about explicitly passing <code>use_reentrant</code> to <code>torch.utils.checkpoint</code></li>
<li>Added <code>torch.nn.utils.weight_norm</code> to the list of deprecated functions flagged by TOR101</li>
<li>Updated README with TOR0 rules description</li>
</ul>
<h2>TorchFix 0.2.1: first release for pytorch-labs/torchfix repo</h2>
<p>This is the first release for pytorch-labs/torchfix repo, with the only differences from TorchFix 0.2.0 on PyPI are files related to repo maintenance and project metadata.</p>
</blockquote>
</details>
<details>
<summary>Commits</summary>
<ul>
<li>See full diff in <a href="https://github.com/pytorch-labs/torchfix/commits/v0.5.0">compare view</a></li>
</ul>
</details>
<br />

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</details>

Pull Request resolved: #3220

Reviewed By: kit1980

Differential Revision: D56449277

Pulled By: huydhn

fbshipit-source-id: ad3c86d49f86427c91af28063d5347b37b893e87

Author: dependabot[bot]

backends/arm/test/models/test_mobilenet_v2_arm.py

@@ -9,11 +9,11 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.arm.test import common
 
 from executorch.backends.arm.test.tester.arm_tester import ArmTester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 from torchvision.models.mobilenetv2 import MobileNet_V2_Weights
 
 

backends/xnnpack/test/models/inception_v3.py

@@ -7,9 +7,9 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 
 
 class TestInceptionV3(unittest.TestCase):

backends/xnnpack/test/models/mobilenet_v2.py

@@ -7,9 +7,9 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 from torchvision.models.mobilenetv2 import MobileNet_V2_Weights
 
 

backends/xnnpack/test/models/mobilenet_v3.py

@@ -7,9 +7,9 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
 from executorch.backends.xnnpack.test.tester.tester import Quantize
+from torchvision import models
 
 
 class TestMobileNetV3(unittest.TestCase):

backends/xnnpack/test/models/torchvision_vit.py

@@ -7,8 +7,8 @@
 import unittest
 
 import torch
-import torchvision.models as models
 from executorch.backends.xnnpack.test.tester import Tester
+from torchvision import models
 
 
 class TestViT(unittest.TestCase):

examples/qualcomm/oss_scripts/ssd300_vgg16.py

@@ -109,7 +109,11 @@ def SSD300VGG16(pretrained_weight_model):
     from model import SSD300
 
     model = SSD300(n_classes=21)
-    checkpoint = torch.load(pretrained_weight_model, map_location="cpu")
+    # TODO: If possible, it's better to set weights_only to True
+    # https://pytorch.org/docs/stable/generated/torch.load.html
+    checkpoint = torch.load(
+        pretrained_weight_model, map_location="cpu", weights_only=False
+    )
     model.load_state_dict(checkpoint["model"].state_dict())
 
     return model.eval()

examples/qualcomm/scripts/mobilebert_fine_tune.py

@@ -204,13 +204,16 @@ def get_fine_tuned_mobilebert(artifacts_dir, pretrained_weight, batch_size):
             )
 
     model.load_state_dict(
+        # TODO: If possible, it's better to set weights_only to True
+        # https://pytorch.org/docs/stable/generated/torch.load.html
         torch.load(
             (
                 f"{artifacts_dir}/finetuned_mobilebert_epoch_{epochs}.model"
                 if pretrained_weight is None
                 else pretrained_weight
             ),
             map_location=torch.device("cpu"),
+            weights_only=False,
         ),
     )
 

exir/serde/export_serialize.py

@@ -242,7 +242,9 @@ def deserialize_torch_artifact(serialized: bytes):
         return {}
     buffer = io.BytesIO(serialized)
     buffer.seek(0)
-    return torch.load(buffer)
+    # TODO: If possible, it's better to set weights_only to True
+    # https://pytorch.org/docs/stable/generated/torch.load.html
+    return torch.load(buffer, weights_only=False)
 
 
 def _sympy_int_to_int(val: sympy.Expr):

requirements-lintrunner.txt

@@ -10,7 +10,7 @@ flake8-comprehensions==3.12.0
 flake8-pyi==23.5.0
 mccabe==0.7.0
 pycodestyle==2.10.0
-torchfix==0.1.1
+torchfix==0.5.0
 
 # UFMT
 black==24.2.0