[air] Suppress "NumPy array is not writable" error in torch conversion

python/ray/air/_internal/torch_utils.py

@@ -1,3 +1,4 @@
+import warnings
 from typing import Dict, List, Optional, Union
 
 import numpy as np
@@ -132,7 +133,15 @@ def convert_ndarray_to_torch_tensor(
     Returns: A Torch Tensor.
     """
     ndarray = _unwrap_ndarray_object_type_if_needed(ndarray)
-    return torch.as_tensor(ndarray, dtype=dtype, device=device)
+
+    # The numpy array is not always writeable as it can come from the Ray object store.
+    # Numpy will throw a verbose warning here, which we suppress, as we don't write
+    # to the tensors. We also don't want to copy the array to avoid memory overhead.
+    # Original warning: https://github.com/pytorch/pytorch/blob/v1.13.0/
+    # torch/csrc/utils/tensor_numpy.cpp#L198-L206
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore")
+        return torch.as_tensor(ndarray, dtype=dtype, device=device)
 
 
 def convert_ndarray_batch_to_torch_tensor_batch(

python/ray/air/tests/test_data_batch_conversion.py

@@ -4,6 +4,7 @@
 import numpy as np
 import pyarrow as pa
 
+from ray.air._internal.torch_utils import convert_ndarray_to_torch_tensor
 from ray.air.constants import TENSOR_COLUMN_NAME
 from ray.air.util.data_batch_conversion import (
     convert_batch_type_to_pandas,
@@ -185,6 +186,17 @@ def test_numpy_object_pandas():
     )
 
 
+@pytest.mark.parametrize("writable", [False, True])
+def test_numpy_to_tensor_warning(writable):
+    input_data = np.array([[1, 2, 3]], dtype=int)
+    input_data.setflags(write=writable)
+
+    with pytest.warns(None) as record:
+        tensor = convert_ndarray_to_torch_tensor(input_data)
+    assert not record.list, [w.message for w in record.list]
+    assert tensor is not None
+
+
 def test_dict_fail():
     input_data = {"x": "y"}
     with pytest.raises(ValueError):