[syft/serde] - move all code related to torch tensor serde into a try…

…-exception block in `third_party.py`

- move torch back to under data_science marker in setup.cfg

packages/syft/setup.cfg

@@ -66,8 +66,6 @@ syft =
     rich==13.7.1
     jinja2==3.1.4
     tenacity==8.3.0
-    # backend.dockerfile installs torch separately, so update the version over there as well!
-    torch==2.3.0
 
 install_requires =
     %(syft)s
@@ -88,6 +86,8 @@ data_science =
     opendp==0.9.2
     evaluate==0.4.1
     recordlinkage==0.16
+    # backend.dockerfile installs torch separately, so update the version over there as well!
+    torch==2.3.0
 
 dev =
     %(test_plugins)s

packages/syft/src/syft/serde/array.py

@@ -1,7 +1,6 @@
 # third party
 import numpy as np
 from numpy import frombuffer
-import torch
 
 # relative
 from .arrow import numpy_deserialize
@@ -151,22 +150,5 @@
 #     deserialize=lambda buffer: frombuffer(buffer, dtype=numpy_scalar_type),
 # )
 
-
-# Add support for torch tensors
-def torch_serialize(tensor: torch.Tensor) -> bytes:
-    return numpy_serialize(tensor.numpy())
-
-
-def torch_deserialize(buffer: bytes) -> torch.tensor:
-    np_array = numpy_deserialize(buffer)
-    return torch.from_numpy(np_array)
-
-
-recursive_serde_register(
-    torch.Tensor,
-    serialize=torch_serialize,
-    deserialize=lambda data: torch_deserialize(data),
-)
-
 # how else do you import a relative file to execute it?
 NOTHING = None

packages/syft/src/syft/serde/third_party.py

@@ -24,14 +24,14 @@
 from result import Err
 from result import Ok
 from result import Result
-import torch
-from torch._C import _TensorMeta
 
 # relative
 from ..types.dicttuple import DictTuple
 from ..types.dicttuple import _Meta as _DictTupleMetaClass
 from ..types.syft_metaclass import EmptyType
 from ..types.syft_metaclass import PartialModelMetaclass
+from .array import numpy_deserialize
+from .array import numpy_serialize
 from .deserialize import _deserialize as deserialize
 from .recursive_primitives import _serialize_kv_pairs
 from .recursive_primitives import deserialize_kv
@@ -107,24 +107,6 @@ def deserialize_series(blob: bytes) -> Series:
     deserialize=deserialize_series,
 )
 
-
-def serialize_torch_tensor_meta(t: _TensorMeta) -> bytes:
-    buffer = BytesIO()
-    torch.save(t, buffer)
-    return buffer.getvalue()
-
-
-def deserialize_torch_tensor_meta(buf: bytes) -> _TensorMeta:
-    buffer = BytesIO(buf)
-    return torch.load(buffer)
-
-
-recursive_serde_register(
-    _TensorMeta,
-    serialize=serialize_torch_tensor_meta,
-    deserialize=deserialize_torch_tensor_meta,
-)
-
 recursive_serde_register(
     datetime,
     serialize=lambda x: serialize(x.isoformat(), to_bytes=True),
@@ -198,6 +180,42 @@ def serialize_bytes_io(io: BytesIO) -> bytes:
     pass
 
 
+try:
+    # third party
+    import torch
+    from torch._C import _TensorMeta
+
+    def serialize_torch_tensor_meta(t: _TensorMeta) -> bytes:
+        buffer = BytesIO()
+        torch.save(t, buffer)
+        return buffer.getvalue()
+
+    def deserialize_torch_tensor_meta(buf: bytes) -> _TensorMeta:
+        buffer = BytesIO(buf)
+        return torch.load(buffer)
+
+    recursive_serde_register(
+        _TensorMeta,
+        serialize=serialize_torch_tensor_meta,
+        deserialize=deserialize_torch_tensor_meta,
+    )
+
+    def torch_serialize(tensor: torch.Tensor) -> bytes:
+        return numpy_serialize(tensor.numpy())
+
+    def torch_deserialize(buffer: bytes) -> torch.tensor:
+        np_array = numpy_deserialize(buffer)
+        return torch.from_numpy(np_array)
+
+    recursive_serde_register(
+        torch.Tensor,
+        serialize=torch_serialize,
+        deserialize=lambda data: torch_deserialize(data),
+    )
+
+except Exception:  # nosec
+    pass
+
 # unsure why we have to register the object not the type but this works
 recursive_serde_register(np.core._ufunc_config._unspecified())