properly support deepcopying and serialization of model weights (#7107)

test/test_extended_models.py

 import copy
 import os
+import pickle
 
 import pytest
 import test_models as TM
@@ -73,10 +74,32 @@ def test_get_model_weights(name, weight):
     ],
 )
 def test_weights_copyable(copy_fn, name):
-    model_weights = models.get_model_weights(name)
-    for weights in list(model_weights):
-        copied_weights = copy_fn(weights)
-        assert copied_weights is weights
+    for weights in list(models.get_model_weights(name)):
+        # It is somewhat surprising that (deep-)copying is an identity operation here, but this is the default behavior
+        # of enums: https://docs.python.org/3/howto/enum.html#enum-members-aka-instances
+        # Checking for equality, i.e. `==`, is sufficient (and even preferable) for our use case, should we need to drop
+        # support for the identity operation in the future.
+        assert copy_fn(weights) is weights
+
+
+@pytest.mark.parametrize(
+    "name",
+    [
+        "resnet50",
+        "retinanet_resnet50_fpn_v2",
+        "raft_large",
+        "quantized_resnet50",
+        "lraspp_mobilenet_v3_large",
+        "mvit_v1_b",
+    ],
+)
+def test_weights_deserializable(name):
+    for weights in list(models.get_model_weights(name)):
+        # It is somewhat surprising that deserialization is an identity operation here, but this is the default behavior
+        # of enums: https://docs.python.org/3/howto/enum.html#enum-members-aka-instances
+        # Checking for equality, i.e. `==`, is sufficient (and even preferable) for our use case, should we need to drop
+        # support for the identity operation in the future.
+        assert pickle.loads(pickle.dumps(weights)) is weights
 
 
 @pytest.mark.parametrize(

torchvision/models/_api.py

@@ -2,6 +2,7 @@ import importlib
 import inspect
 import sys
 from dataclasses import dataclass, fields
+from functools import partial
 from inspect import signature
 from types import ModuleType
 from typing import Any, Callable, cast, Dict, List, Mapping, Optional, TypeVar, Union
@@ -37,6 +38,32 @@ class Weights:
     transforms: Callable
     meta: Dict[str, Any]
 
+    def __eq__(self, other: Any) -> bool:
+        # We need this custom implementation for correct deep-copy and deserialization behavior.
+        # TL;DR: After the definition of an enum, creating a new instance, i.e. by deep-copying or deserializing it,
+        # involves an equality check against the defined members. Unfortunately, the `transforms` attribute is often
+        # defined with `functools.partial` and `fn = partial(...); assert deepcopy(fn) != fn`. Without custom handling
+        # for it, the check against the defined members would fail and effectively prevent the weights from being
+        # deep-copied or deserialized.
+        # See https://github.com/pytorch/vision/pull/7107 for details.
+        if not isinstance(other, Weights):
+            return NotImplemented
+
+        if self.url != other.url:
+            return False
+
+        if self.meta != other.meta:
+            return False
+
+        if isinstance(self.transforms, partial) and isinstance(other.transforms, partial):
+            return (
+                self.transforms.func == other.transforms.func
+                and self.transforms.args == other.transforms.args
+                and self.transforms.keywords == other.transforms.keywords
+            )
+        else:
+            return self.transforms == other.transforms
+
 
 class WeightsEnum(StrEnum):
     """
@@ -75,9 +102,6 @@ class WeightsEnum(StrEnum):
                 return object.__getattribute__(self.value, name)
         return super().__getattr__(name)
 
-    def __deepcopy__(self, memodict=None):
-        return self
-
 
 def get_weight(name: str) -> WeightsEnum:
     """