[V1] Allow turning off pickle fallback in vllm.v1.serial_utils (#17427)

Signed-off-by: Russell Bryant <rbryant@redhat.com>
Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>

Author: russellb

tests/v1/test_serial_utils.py

@@ -5,6 +5,7 @@
 
 import msgspec
 import numpy as np
+import pytest
 import torch
 
 from vllm.multimodal.inputs import (MultiModalBatchedField,
@@ -196,3 +197,100 @@ def assert_equal(obj1: MyType, obj2: MyType):
     assert torch.equal(obj1.large_non_contig_tensor,
                        obj2.large_non_contig_tensor)
     assert torch.equal(obj1.empty_tensor, obj2.empty_tensor)
+
+
+@pytest.mark.parametrize("allow_pickle", [True, False])
+def test_dict_serialization(allow_pickle: bool):
+    """Test encoding and decoding of a generic Python object using pickle."""
+    encoder = MsgpackEncoder(allow_pickle=allow_pickle)
+    decoder = MsgpackDecoder(allow_pickle=allow_pickle)
+
+    # Create a sample Python object
+    obj = {"key": "value", "number": 42}
+
+    # Encode the object
+    encoded = encoder.encode(obj)
+
+    # Decode the object
+    decoded = decoder.decode(encoded)
+
+    # Verify the decoded object matches the original
+    assert obj == decoded, "Decoded object does not match the original object."
+
+
+@pytest.mark.parametrize("allow_pickle", [True, False])
+def test_tensor_serialization(allow_pickle: bool):
+    """Test encoding and decoding of a torch.Tensor."""
+    encoder = MsgpackEncoder(allow_pickle=allow_pickle)
+    decoder = MsgpackDecoder(torch.Tensor, allow_pickle=allow_pickle)
+
+    # Create a sample tensor
+    tensor = torch.rand(10, 10)
+
+    # Encode the tensor
+    encoded = encoder.encode(tensor)
+
+    # Decode the tensor
+    decoded = decoder.decode(encoded)
+
+    # Verify the decoded tensor matches the original
+    assert torch.allclose(
+        tensor, decoded), "Decoded tensor does not match the original tensor."
+
+
+@pytest.mark.parametrize("allow_pickle", [True, False])
+def test_numpy_array_serialization(allow_pickle: bool):
+    """Test encoding and decoding of a numpy array."""
+    encoder = MsgpackEncoder(allow_pickle=allow_pickle)
+    decoder = MsgpackDecoder(np.ndarray, allow_pickle=allow_pickle)
+
+    # Create a sample numpy array
+    array = np.random.rand(10, 10)
+
+    # Encode the numpy array
+    encoded = encoder.encode(array)
+
+    # Decode the numpy array
+    decoded = decoder.decode(encoded)
+
+    # Verify the decoded array matches the original
+    assert np.allclose(
+        array,
+        decoded), "Decoded numpy array does not match the original array."
+
+
+class CustomClass:
+
+    def __init__(self, value):
+        self.value = value
+
+    def __eq__(self, other):
+        return isinstance(other, CustomClass) and self.value == other.value
+
+
+def test_custom_class_serialization_allowed_with_pickle():
+    """Test that serializing a custom class succeeds when allow_pickle=True."""
+    encoder = MsgpackEncoder(allow_pickle=True)
+    decoder = MsgpackDecoder(CustomClass, allow_pickle=True)
+
+    obj = CustomClass("test_value")
+
+    # Encode the custom class
+    encoded = encoder.encode(obj)
+
+    # Decode the custom class
+    decoded = decoder.decode(encoded)
+
+    # Verify the decoded object matches the original
+    assert obj == decoded, "Decoded object does not match the original object."
+
+
+def test_custom_class_serialization_disallowed_without_pickle():
+    """Test that serializing a custom class fails when allow_pickle=False."""
+    encoder = MsgpackEncoder(allow_pickle=False)
+
+    obj = CustomClass("test_value")
+
+    with pytest.raises(TypeError):
+        # Attempt to encode the custom class
+        encoder.encode(obj)

vllm/v1/serial_utils.py

@@ -47,7 +47,9 @@ class MsgpackEncoder:
     via dedicated messages. Note that this is a per-tensor limit.
     """
 
-    def __init__(self, size_threshold: Optional[int] = None):
+    def __init__(self,
+                 size_threshold: Optional[int] = None,
+                 allow_pickle: bool = True):
         if size_threshold is None:
             size_threshold = envs.VLLM_MSGPACK_ZERO_COPY_THRESHOLD
         self.encoder = msgpack.Encoder(enc_hook=self.enc_hook)
@@ -56,6 +58,7 @@ def __init__(self, size_threshold: Optional[int] = None):
         # pass custom data to the hook otherwise.
         self.aux_buffers: Optional[list[bytestr]] = None
         self.size_threshold = size_threshold
+        self.allow_pickle = allow_pickle
 
     def encode(self, obj: Any) -> Sequence[bytestr]:
         try:
@@ -105,6 +108,9 @@ def enc_hook(self, obj: Any) -> Any:
                     for itemlist in mm._items_by_modality.values()
                     for item in itemlist]
 
+        if not self.allow_pickle:
+            raise TypeError(f"Object of type {type(obj)} is not serializable")
+
         if isinstance(obj, FunctionType):
             # `pickle` is generally faster than cloudpickle, but can have
             # problems serializing methods.
@@ -179,12 +185,13 @@ class MsgpackDecoder:
     not thread-safe when encoding tensors / numpy arrays.
     """
 
-    def __init__(self, t: Optional[Any] = None):
+    def __init__(self, t: Optional[Any] = None, allow_pickle: bool = True):
         args = () if t is None else (t, )
         self.decoder = msgpack.Decoder(*args,
                                        ext_hook=self.ext_hook,
                                        dec_hook=self.dec_hook)
         self.aux_buffers: Sequence[bytestr] = ()
+        self.allow_pickle = allow_pickle
 
     def decode(self, bufs: Union[bytestr, Sequence[bytestr]]) -> Any:
         if isinstance(bufs, (bytes, bytearray, memoryview, zmq.Frame)):
@@ -265,10 +272,12 @@ def _decode_nested_tensors(self, obj: Any) -> NestedTensors:
     def ext_hook(self, code: int, data: memoryview) -> Any:
         if code == CUSTOM_TYPE_RAW_VIEW:
             return data
-        if code == CUSTOM_TYPE_PICKLE:
-            return pickle.loads(data)
-        if code == CUSTOM_TYPE_CLOUDPICKLE:
-            return cloudpickle.loads(data)
+
+        if self.allow_pickle:
+            if code == CUSTOM_TYPE_PICKLE:
+                return pickle.loads(data)
+            if code == CUSTOM_TYPE_CLOUDPICKLE:
+                return cloudpickle.loads(data)
 
         raise NotImplementedError(
             f"Extension type code {code} is not supported")