From 89be62eea28fd0de710effc0aa84ea6aafb8e5d9 Mon Sep 17 00:00:00 2001
From: aviruthen <91846056+aviruthen@users.noreply.github.com>
Date: Mon, 6 Apr 2026 14:59:09 -0400
Subject: [PATCH 1/4] feature: Torch dependency in sagameker-core to be made
 optional (5457)

---
 sagemaker-core/pyproject.toml                 |   7 +-
 .../src/sagemaker/core/deserializers/base.py  |   5 +-
 .../src/sagemaker/core/serializers/base.py    |   8 +-
 .../unit/test_optional_torch_dependency.py    | 154 ++++++++++++++++++
 4 files changed, 171 insertions(+), 3 deletions(-)
 create mode 100644 sagemaker-core/tests/unit/test_optional_torch_dependency.py

diff --git a/sagemaker-core/pyproject.toml b/sagemaker-core/pyproject.toml
index 2756ce0f1c..4134d50e34 100644
--- a/sagemaker-core/pyproject.toml
+++ b/sagemaker-core/pyproject.toml
@@ -32,7 +32,6 @@ dependencies = [
     "smdebug_rulesconfig>=1.0.1",
     "schema>=0.7.5",
     "omegaconf>=2.1.0",
-    "torch>=1.9.0",
     "scipy>=1.5.0",
     # Remote function dependencies
     "cloudpickle>=2.0.0",
@@ -51,6 +50,12 @@ classifiers = [
 ]
 
 [project.optional-dependencies]
+torch = [
+    "torch>=1.9.0",
+]
+all = [
+    "torch>=1.9.0",
+]
 codegen = [
     "black>=24.3.0, <25.0.0",
     "pandas>=2.0.0, <3.0.0",
diff --git a/sagemaker-core/src/sagemaker/core/deserializers/base.py b/sagemaker-core/src/sagemaker/core/deserializers/base.py
index 4faae7db74..1f7ec9ab06 100644
--- a/sagemaker-core/src/sagemaker/core/deserializers/base.py
+++ b/sagemaker-core/src/sagemaker/core/deserializers/base.py
@@ -366,7 +366,10 @@ def __init__(self, accept="tensor/pt"):
 
             self.convert_npy_to_tensor = from_numpy
         except ImportError:
-            raise Exception("Unable to import pytorch.")
+            raise ImportError(
+                "Unable to import torch. Please install torch to use TorchTensorDeserializer: "
+                "pip install 'sagemaker-core[torch]'"
+            )
 
     def deserialize(self, stream, content_type="tensor/pt"):
         """Deserialize streamed data to TorchTensor
diff --git a/sagemaker-core/src/sagemaker/core/serializers/base.py b/sagemaker-core/src/sagemaker/core/serializers/base.py
index a4ecf7c1dc..4b3ba4fdba 100644
--- a/sagemaker-core/src/sagemaker/core/serializers/base.py
+++ b/sagemaker-core/src/sagemaker/core/serializers/base.py
@@ -443,7 +443,13 @@ class TorchTensorSerializer(SimpleBaseSerializer):
 
     def __init__(self, content_type="tensor/pt"):
         super(TorchTensorSerializer, self).__init__(content_type=content_type)
-        from torch import Tensor
+        try:
+            from torch import Tensor
+        except ImportError:
+            raise ImportError(
+                "Unable to import torch. Please install torch to use TorchTensorSerializer: "
+                "pip install 'sagemaker-core[torch]'"
+            )
 
         self.torch_tensor = Tensor
         self.numpy_serializer = NumpySerializer()
diff --git a/sagemaker-core/tests/unit/test_optional_torch_dependency.py b/sagemaker-core/tests/unit/test_optional_torch_dependency.py
new file mode 100644
index 0000000000..f0eb2879fd
--- /dev/null
+++ b/sagemaker-core/tests/unit/test_optional_torch_dependency.py
@@ -0,0 +1,154 @@
+# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"). You
+# may not use this file except in compliance with the License. A copy of
+# the License is located at
+#
+#     http://aws.amazon.com/apache2.0/
+#
+# or in the "license" file accompanying this file. This file is
+# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific
+# language governing permissions and limitations under the License.
+"""Tests to verify torch dependency is optional in sagemaker-core."""
+from __future__ import absolute_import
+
+import io
+import sys
+from unittest import mock
+
+import numpy as np
+import pytest
+
+
+def test_serializer_module_imports_without_torch():
+    """Verify that importing serializers module succeeds without torch installed."""
+    # The serializers module should be importable even without torch
+    # because TorchTensorSerializer uses lazy import in __init__
+    from sagemaker.core.serializers.base import (
+        CSVSerializer,
+        NumpySerializer,
+        JSONSerializer,
+        IdentitySerializer,
+        SparseMatrixSerializer,
+        JSONLinesSerializer,
+        LibSVMSerializer,
+        DataSerializer,
+        StringSerializer,
+    )
+    # Verify non-torch serializers can be instantiated
+    assert CSVSerializer() is not None
+    assert NumpySerializer() is not None
+    assert JSONSerializer() is not None
+    assert IdentitySerializer() is not None
+
+
+def test_deserializer_module_imports_without_torch():
+    """Verify that importing deserializers module succeeds without torch installed."""
+    from sagemaker.core.deserializers.base import (
+        StringDeserializer,
+        BytesDeserializer,
+        CSVDeserializer,
+        StreamDeserializer,
+        NumpyDeserializer,
+        JSONDeserializer,
+        PandasDeserializer,
+        JSONLinesDeserializer,
+    )
+    # Verify non-torch deserializers can be instantiated
+    assert StringDeserializer() is not None
+    assert BytesDeserializer() is not None
+    assert CSVDeserializer() is not None
+    assert NumpyDeserializer() is not None
+    assert JSONDeserializer() is not None
+
+
+def test_torch_tensor_serializer_raises_import_error_without_torch():
+    """Verify TorchTensorSerializer raises ImportError when torch is not installed."""
+    import importlib
+    import sagemaker.core.serializers.base as ser_module
+
+    # Save original torch module if present
+    original_torch = sys.modules.get('torch')
+    
+    try:
+        # Simulate torch not being installed
+        sys.modules['torch'] = None
+        # Need to also handle the case where torch submodules are cached
+        torch_keys = [key for key in sys.modules if key.startswith('torch.')]
+        saved = {key: sys.modules.pop(key) for key in torch_keys}
+        
+        with pytest.raises(ImportError, match="Unable to import torch"):
+            ser_module.TorchTensorSerializer()
+    finally:
+        # Restore original state
+        if original_torch is not None:
+            sys.modules['torch'] = original_torch
+        elif 'torch' in sys.modules:
+            del sys.modules['torch']
+        for key, val in saved.items():
+            sys.modules[key] = val
+
+
+def test_torch_tensor_deserializer_raises_import_error_without_torch():
+    """Verify TorchTensorDeserializer raises ImportError when torch is not installed."""
+    import sagemaker.core.deserializers.base as deser_module
+
+    # Save original torch module if present
+    original_torch = sys.modules.get('torch')
+    
+    try:
+        # Simulate torch not being installed
+        sys.modules['torch'] = None
+        torch_keys = [key for key in sys.modules if key.startswith('torch.')]
+        saved = {key: sys.modules.pop(key) for key in torch_keys}
+        
+        with pytest.raises(ImportError, match="Unable to import torch"):
+            deser_module.TorchTensorDeserializer()
+    finally:
+        # Restore original state
+        if original_torch is not None:
+            sys.modules['torch'] = original_torch
+        elif 'torch' in sys.modules:
+            del sys.modules['torch']
+        for key, val in saved.items():
+            sys.modules[key] = val
+
+
+def test_torch_tensor_serializer_works_with_torch():
+    """Verify TorchTensorSerializer works when torch is available."""
+    try:
+        import torch
+    except ImportError:
+        pytest.skip("torch is not installed")
+
+    from sagemaker.core.serializers.base import TorchTensorSerializer
+
+    serializer = TorchTensorSerializer()
+    tensor = torch.tensor([1.0, 2.0, 3.0])
+    result = serializer.serialize(tensor)
+    assert result is not None
+    # Verify the result can be loaded back as numpy
+    array = np.load(io.BytesIO(result))
+    assert np.array_equal(array, np.array([1.0, 2.0, 3.0]))
+
+
+def test_torch_tensor_deserializer_works_with_torch():
+    """Verify TorchTensorDeserializer works when torch is available."""
+    try:
+        import torch
+    except ImportError:
+        pytest.skip("torch is not installed")
+
+    from sagemaker.core.deserializers.base import TorchTensorDeserializer
+
+    deserializer = TorchTensorDeserializer()
+    # Create a numpy array, save it, and deserialize to tensor
+    array = np.array([1.0, 2.0, 3.0])
+    buffer = io.BytesIO()
+    np.save(buffer, array)
+    buffer.seek(0)
+
+    result = deserializer.deserialize(buffer, "tensor/pt")
+    assert isinstance(result, torch.Tensor)
+    assert torch.equal(result, torch.tensor([1.0, 2.0, 3.0]))

From 57b5c02cb6d097312fc055fa4bf83559abbae941 Mon Sep 17 00:00:00 2001
From: aviruthen <91846056+aviruthen@users.noreply.github.com>
Date: Mon, 6 Apr 2026 15:04:48 -0400
Subject: [PATCH 2/4] fix: address review comments (iteration #1)

---
 sagemaker-core/pyproject.toml                 |   2 +-
 .../src/sagemaker/core/deserializers/base.py  |   4 +-
 .../src/sagemaker/core/serializers/base.py    |   4 +-
 .../unit/test_optional_torch_dependency.py    | 138 +++++++++---------
 4 files changed, 73 insertions(+), 75 deletions(-)

diff --git a/sagemaker-core/pyproject.toml b/sagemaker-core/pyproject.toml
index 4134d50e34..c0656ab16a 100644
--- a/sagemaker-core/pyproject.toml
+++ b/sagemaker-core/pyproject.toml
@@ -54,7 +54,7 @@ torch = [
     "torch>=1.9.0",
 ]
 all = [
-    "torch>=1.9.0",
+    "sagemaker-core[torch]",
 ]
 codegen = [
     "black>=24.3.0, <25.0.0",
diff --git a/sagemaker-core/src/sagemaker/core/deserializers/base.py b/sagemaker-core/src/sagemaker/core/deserializers/base.py
index 1f7ec9ab06..03138ed577 100644
--- a/sagemaker-core/src/sagemaker/core/deserializers/base.py
+++ b/sagemaker-core/src/sagemaker/core/deserializers/base.py
@@ -365,11 +365,11 @@ def __init__(self, accept="tensor/pt"):
             from torch import from_numpy
 
             self.convert_npy_to_tensor = from_numpy
-        except ImportError:
+        except ImportError as e:
             raise ImportError(
                 "Unable to import torch. Please install torch to use TorchTensorDeserializer: "
                 "pip install 'sagemaker-core[torch]'"
-            )
+            ) from e
 
     def deserialize(self, stream, content_type="tensor/pt"):
         """Deserialize streamed data to TorchTensor
diff --git a/sagemaker-core/src/sagemaker/core/serializers/base.py b/sagemaker-core/src/sagemaker/core/serializers/base.py
index 4b3ba4fdba..e8862b66f3 100644
--- a/sagemaker-core/src/sagemaker/core/serializers/base.py
+++ b/sagemaker-core/src/sagemaker/core/serializers/base.py
@@ -445,11 +445,11 @@ def __init__(self, content_type="tensor/pt"):
         super(TorchTensorSerializer, self).__init__(content_type=content_type)
         try:
             from torch import Tensor
-        except ImportError:
+        except ImportError as e:
             raise ImportError(
                 "Unable to import torch. Please install torch to use TorchTensorSerializer: "
                 "pip install 'sagemaker-core[torch]'"
-            )
+            ) from e
 
         self.torch_tensor = Tensor
         self.numpy_serializer = NumpySerializer()
diff --git a/sagemaker-core/tests/unit/test_optional_torch_dependency.py b/sagemaker-core/tests/unit/test_optional_torch_dependency.py
index f0eb2879fd..5008244e27 100644
--- a/sagemaker-core/tests/unit/test_optional_torch_dependency.py
+++ b/sagemaker-core/tests/unit/test_optional_torch_dependency.py
@@ -11,108 +11,106 @@
 # ANY KIND, either express or implied. See the License for the specific
 # language governing permissions and limitations under the License.
 """Tests to verify torch dependency is optional in sagemaker-core."""
-from __future__ import absolute_import
+from __future__ import annotations
 
+import importlib
 import io
 import sys
-from unittest import mock
 
 import numpy as np
 import pytest
 
 
+def _block_torch():
+    """Block torch imports by setting sys.modules['torch'] to None.
+
+    Returns a dict of saved torch submodule entries so they can be restored.
+    """
+    saved = {}
+    torch_keys = [key for key in sys.modules if key.startswith("torch.")]
+    saved = {key: sys.modules.pop(key) for key in torch_keys}
+    saved["torch"] = sys.modules.get("torch")
+    sys.modules["torch"] = None
+    return saved
+
+
+def _restore_torch(saved):
+    """Restore torch modules from saved dict."""
+    original_torch = saved.pop("torch", None)
+    if original_torch is not None:
+        sys.modules["torch"] = original_torch
+    elif "torch" in sys.modules:
+        del sys.modules["torch"]
+    for key, val in saved.items():
+        sys.modules[key] = val
+
+
 def test_serializer_module_imports_without_torch():
-    """Verify that importing serializers module succeeds without torch installed."""
-    # The serializers module should be importable even without torch
-    # because TorchTensorSerializer uses lazy import in __init__
-    from sagemaker.core.serializers.base import (
-        CSVSerializer,
-        NumpySerializer,
-        JSONSerializer,
-        IdentitySerializer,
-        SparseMatrixSerializer,
-        JSONLinesSerializer,
-        LibSVMSerializer,
-        DataSerializer,
-        StringSerializer,
-    )
-    # Verify non-torch serializers can be instantiated
-    assert CSVSerializer() is not None
-    assert NumpySerializer() is not None
-    assert JSONSerializer() is not None
-    assert IdentitySerializer() is not None
+    """Verify that importing non-torch serializers succeeds without torch installed."""
+    saved = {}
+    try:
+        saved = _block_torch()
+
+        # Reload the module so it re-evaluates imports with torch blocked
+        import sagemaker.core.serializers.base as ser_module
+
+        importlib.reload(ser_module)
+
+        # Verify non-torch serializers can be instantiated
+        assert ser_module.CSVSerializer() is not None
+        assert ser_module.NumpySerializer() is not None
+        assert ser_module.JSONSerializer() is not None
+        assert ser_module.IdentitySerializer() is not None
+    finally:
+        _restore_torch(saved)
 
 
 def test_deserializer_module_imports_without_torch():
-    """Verify that importing deserializers module succeeds without torch installed."""
-    from sagemaker.core.deserializers.base import (
-        StringDeserializer,
-        BytesDeserializer,
-        CSVDeserializer,
-        StreamDeserializer,
-        NumpyDeserializer,
-        JSONDeserializer,
-        PandasDeserializer,
-        JSONLinesDeserializer,
-    )
-    # Verify non-torch deserializers can be instantiated
-    assert StringDeserializer() is not None
-    assert BytesDeserializer() is not None
-    assert CSVDeserializer() is not None
-    assert NumpyDeserializer() is not None
-    assert JSONDeserializer() is not None
+    """Verify that importing non-torch deserializers succeeds without torch installed."""
+    saved = {}
+    try:
+        saved = _block_torch()
+
+        import sagemaker.core.deserializers.base as deser_module
+
+        importlib.reload(deser_module)
+
+        # Verify non-torch deserializers can be instantiated
+        assert deser_module.StringDeserializer() is not None
+        assert deser_module.BytesDeserializer() is not None
+        assert deser_module.CSVDeserializer() is not None
+        assert deser_module.NumpyDeserializer() is not None
+        assert deser_module.JSONDeserializer() is not None
+    finally:
+        _restore_torch(saved)
 
 
 def test_torch_tensor_serializer_raises_import_error_without_torch():
     """Verify TorchTensorSerializer raises ImportError when torch is not installed."""
-    import importlib
     import sagemaker.core.serializers.base as ser_module
 
-    # Save original torch module if present
-    original_torch = sys.modules.get('torch')
-    
+    saved = {}
     try:
-        # Simulate torch not being installed
-        sys.modules['torch'] = None
-        # Need to also handle the case where torch submodules are cached
-        torch_keys = [key for key in sys.modules if key.startswith('torch.')]
-        saved = {key: sys.modules.pop(key) for key in torch_keys}
-        
+        saved = _block_torch()
+
         with pytest.raises(ImportError, match="Unable to import torch"):
             ser_module.TorchTensorSerializer()
     finally:
-        # Restore original state
-        if original_torch is not None:
-            sys.modules['torch'] = original_torch
-        elif 'torch' in sys.modules:
-            del sys.modules['torch']
-        for key, val in saved.items():
-            sys.modules[key] = val
+        _restore_torch(saved)
 
 
 def test_torch_tensor_deserializer_raises_import_error_without_torch():
     """Verify TorchTensorDeserializer raises ImportError when torch is not installed."""
     import sagemaker.core.deserializers.base as deser_module
 
-    # Save original torch module if present
-    original_torch = sys.modules.get('torch')
-    
+    saved = {}
     try:
-        # Simulate torch not being installed
-        sys.modules['torch'] = None
-        torch_keys = [key for key in sys.modules if key.startswith('torch.')]
-        saved = {key: sys.modules.pop(key) for key in torch_keys}
-        
+        saved = _block_torch()
+
         with pytest.raises(ImportError, match="Unable to import torch"):
             deser_module.TorchTensorDeserializer()
     finally:
-        # Restore original state
-        if original_torch is not None:
-            sys.modules['torch'] = original_torch
-        elif 'torch' in sys.modules:
-            del sys.modules['torch']
-        for key, val in saved.items():
-            sys.modules[key] = val
+        _restore_torch(saved)
 
 
 def test_torch_tensor_serializer_works_with_torch():

From 0ed06b2afb0480bdb86131f1c04aeb800cf3f9ca Mon Sep 17 00:00:00 2001
From: aviruthen <91846056+aviruthen@users.noreply.github.com>
Date: Tue, 14 Apr 2026 15:34:58 -0700
Subject: [PATCH 3/4] fix: address review comments (iteration #1)

---
 sagemaker-core/pyproject.toml                 |  1 +
 .../src/sagemaker/core/serializers/base.py    |  3 ++-
 .../unit/test_serializer_implementations.py   | 24 ++++++++++++++++++-
 sagemaker-core/tox.ini                        |  1 -
 4 files changed, 26 insertions(+), 3 deletions(-)

diff --git a/sagemaker-core/pyproject.toml b/sagemaker-core/pyproject.toml
index c0656ab16a..4b3f3f1739 100644
--- a/sagemaker-core/pyproject.toml
+++ b/sagemaker-core/pyproject.toml
@@ -66,6 +66,7 @@ test = [
     "pytest>=8.0.0, <9.0.0",
     "pytest-cov>=4.0.0",
     "pytest-xdist>=3.0.0",
+    "sagemaker-core[torch]",
 ]
 
 [project.urls]
diff --git a/sagemaker-core/src/sagemaker/core/serializers/base.py b/sagemaker-core/src/sagemaker/core/serializers/base.py
index e8862b66f3..84b9832c63 100644
--- a/sagemaker-core/src/sagemaker/core/serializers/base.py
+++ b/sagemaker-core/src/sagemaker/core/serializers/base.py
@@ -445,13 +445,14 @@ def __init__(self, content_type="tensor/pt"):
         super(TorchTensorSerializer, self).__init__(content_type=content_type)
         try:
             from torch import Tensor
+
+            self.torch_tensor = Tensor
         except ImportError as e:
             raise ImportError(
                 "Unable to import torch. Please install torch to use TorchTensorSerializer: "
                 "pip install 'sagemaker-core[torch]'"
             ) from e
 
-        self.torch_tensor = Tensor
         self.numpy_serializer = NumpySerializer()
 
     def serialize(self, data):
diff --git a/sagemaker-core/tests/unit/test_serializer_implementations.py b/sagemaker-core/tests/unit/test_serializer_implementations.py
index 60d7d62b0b..b12471cbf2 100644
--- a/sagemaker-core/tests/unit/test_serializer_implementations.py
+++ b/sagemaker-core/tests/unit/test_serializer_implementations.py
@@ -11,7 +11,7 @@
 # ANY KIND, either express or implied. See the License for the specific
 # language governing permissions and limitations under the License.
 """Unit tests for sagemaker.core.serializers.implementations module."""
-from __future__ import absolute_import
+from __future__ import annotations
 
 import pytest
 from unittest.mock import Mock, patch
@@ -162,3 +162,25 @@ def test_numpy_serializer_import(self):
     def test_record_serializer_deprecated(self):
         """Test that numpy_to_record_serializer is available as deprecated."""
         assert hasattr(implementations, "numpy_to_record_serializer")
+
+
+class TestTorchSerializerWithOptionalDependency:
+    """Test torch serializer/deserializer with optional torch dependency."""
+
+    def test_torch_tensor_serializer_instantiation(self):
+        """Test that TorchTensorSerializer can be instantiated when torch is available."""
+        torch = pytest.importorskip("torch")
+        from sagemaker.core.serializers.base import TorchTensorSerializer
+
+        serializer = TorchTensorSerializer()
+        assert serializer is not None
+        assert serializer.content_type == "tensor/pt"
+
+    def test_torch_tensor_deserializer_instantiation(self):
+        """Test that TorchTensorDeserializer can be instantiated when torch is available."""
+        torch = pytest.importorskip("torch")
+        from sagemaker.core.deserializers.base import TorchTensorDeserializer
+
+        deserializer = TorchTensorDeserializer()
+        assert deserializer is not None
+        assert deserializer.accept == "tensor/pt"
diff --git a/sagemaker-core/tox.ini b/sagemaker-core/tox.ini
index 136b99c69c..0e31a74d80 100644
--- a/sagemaker-core/tox.ini
+++ b/sagemaker-core/tox.ini
@@ -6,7 +6,6 @@
 [tox]
 isolated_build = true
 envlist = black-format,flake8,pylint,docstyle,sphinx,doc8,twine,py39,py310,py311,py312
-
 skip_missing_interpreters = False
 
 [flake8]

From 528080325ae8b2ff31fad68164c0f74bd96c1bdd Mon Sep 17 00:00:00 2001
From: aviruthen <91846056+aviruthen@users.noreply.github.com>
Date: Wed, 15 Apr 2026 10:12:43 -0700
Subject: [PATCH 4/4] fix: use subprocess instead of importlib.reload to avoid
 breaking six.with_metaclass super()

---
 .../unit/test_optional_torch_dependency.py    | 108 ++++++++++++------
 .../unit/test_serializer_implementations.py   |   2 +-
 2 files changed, 73 insertions(+), 37 deletions(-)

diff --git a/sagemaker-core/tests/unit/test_optional_torch_dependency.py b/sagemaker-core/tests/unit/test_optional_torch_dependency.py
index 5008244e27..2b7efbc227 100644
--- a/sagemaker-core/tests/unit/test_optional_torch_dependency.py
+++ b/sagemaker-core/tests/unit/test_optional_torch_dependency.py
@@ -10,12 +10,21 @@
 # distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
 # ANY KIND, either express or implied. See the License for the specific
 # language governing permissions and limitations under the License.
-"""Tests to verify torch dependency is optional in sagemaker-core."""
-from __future__ import annotations
+"""Tests to verify torch dependency is optional in sagemaker-core.
+
+The "module imports without torch" tests use subprocess instead of
+importlib.reload to avoid poisoning the class hierarchy in the current
+process.  six.with_metaclass + old-style super() breaks when a module
+is reloaded because the class identity changes, causing
+``TypeError: super(type, obj): obj must be an instance or subtype of type``
+in subsequent tests that instantiate serializers/deserializers.
+"""
+from __future__ import absolute_import
 
-import importlib
 import io
+import subprocess
 import sys
+import textwrap
 
 import numpy as np
 import pytest
@@ -26,7 +35,6 @@ def _block_torch():
 
     Returns a dict of saved torch submodule entries so they can be restored.
     """
-    saved = {}
     torch_keys = [key for key in sys.modules if key.startswith("torch.")]
     saved = {key: sys.modules.pop(key) for key in torch_keys}
     saved["torch"] = sys.modules.get("torch")
@@ -46,43 +54,71 @@ def _restore_torch(saved):
 
 
 def test_serializer_module_imports_without_torch():
-    """Verify that importing non-torch serializers succeeds without torch installed."""
-    saved = {}
-    try:
-        saved = _block_torch()
+    """Verify that non-torch serializers can be imported and instantiated without torch.
 
-        # Reload the module so it re-evaluates imports with torch blocked
-        import sagemaker.core.serializers.base as ser_module
-
-        importlib.reload(ser_module)
-
-        # Verify non-torch serializers can be instantiated
-        assert ser_module.CSVSerializer() is not None
-        assert ser_module.NumpySerializer() is not None
-        assert ser_module.JSONSerializer() is not None
-        assert ser_module.IdentitySerializer() is not None
-    finally:
-        _restore_torch(saved)
+    Runs in a subprocess to avoid polluting the current process's class
+    hierarchy via importlib.reload (which breaks six.with_metaclass).
+    """
+    code = textwrap.dedent("""\
+        import sys
+        # Block torch before any sagemaker imports
+        sys.modules["torch"] = None
+
+        from sagemaker.core.serializers.base import (
+            CSVSerializer,
+            NumpySerializer,
+            JSONSerializer,
+            IdentitySerializer,
+        )
+
+        assert CSVSerializer() is not None
+        assert NumpySerializer() is not None
+        assert JSONSerializer() is not None
+        assert IdentitySerializer() is not None
+        print("OK")
+    """)
+    result = subprocess.run(
+        [sys.executable, "-c", code],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0, (
+        f"Subprocess failed:\nstdout: {result.stdout}\nstderr: {result.stderr}"
+    )
 
 
 def test_deserializer_module_imports_without_torch():
-    """Verify that importing non-torch deserializers succeeds without torch installed."""
-    saved = {}
-    try:
-        saved = _block_torch()
-
-        import sagemaker.core.deserializers.base as deser_module
+    """Verify that non-torch deserializers can be imported and instantiated without torch.
 
-        importlib.reload(deser_module)
-
-        # Verify non-torch deserializers can be instantiated
-        assert deser_module.StringDeserializer() is not None
-        assert deser_module.BytesDeserializer() is not None
-        assert deser_module.CSVDeserializer() is not None
-        assert deser_module.NumpyDeserializer() is not None
-        assert deser_module.JSONDeserializer() is not None
-    finally:
-        _restore_torch(saved)
+    Runs in a subprocess for the same reason as the serializer test above.
+    """
+    code = textwrap.dedent("""\
+        import sys
+        sys.modules["torch"] = None
+
+        from sagemaker.core.deserializers.base import (
+            StringDeserializer,
+            BytesDeserializer,
+            CSVDeserializer,
+            NumpyDeserializer,
+            JSONDeserializer,
+        )
+
+        assert StringDeserializer() is not None
+        assert BytesDeserializer() is not None
+        assert CSVDeserializer() is not None
+        assert NumpyDeserializer() is not None
+        assert JSONDeserializer() is not None
+        print("OK")
+    """)
+    result = subprocess.run(
+        [sys.executable, "-c", code],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0, (
+        f"Subprocess failed:\nstdout: {result.stdout}\nstderr: {result.stderr}"
+    )
 
 
 def test_torch_tensor_serializer_raises_import_error_without_torch():
diff --git a/sagemaker-core/tests/unit/test_serializer_implementations.py b/sagemaker-core/tests/unit/test_serializer_implementations.py
index b12471cbf2..82d5e074b1 100644
--- a/sagemaker-core/tests/unit/test_serializer_implementations.py
+++ b/sagemaker-core/tests/unit/test_serializer_implementations.py
@@ -11,7 +11,7 @@
 # ANY KIND, either express or implied. See the License for the specific
 # language governing permissions and limitations under the License.
 """Unit tests for sagemaker.core.serializers.implementations module."""
-from __future__ import annotations
+from __future__ import absolute_import
 
 import pytest
 from unittest.mock import Mock, patch