code: 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
  
imports: import pytest
  import warnings
  import pandas
  import numpy
  import pyarrow
  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, _convert_pandas_to_batch_type, _convert_batch_type_to_numpy, _cast_ndarray_columns_to_tensor_extension, _cast_tensor_columns_to_ndarrays
  from ray.air.util.data_batch_conversion import BatchFormat
  from ray.air.util.tensor_extensions.pandas import TensorArray
  from ray.air.util.tensor_extensions.arrow import ArrowTensorArray
label_desc: Use image node_id 10 for calling a global function with example usage: test_numpy_to_tensor_warning(writable) without return types