[Data] Support serializing zero-length numpy arrays

[chriso]

Description

Ray data can't serialize zero (byte) length numpy arrays:

import numpy as np
import ray.data

array = np.empty((2, 0), dtype=np.int8)

ds = ray.data.from_items([{"array": array}])

for batch in ds.iter_batches(batch_size=1):
     print(batch)

What I expect to see:

{'array': array([], shape=(1, 2, 0), dtype=int8)}

What I see:

/Users/chris.ohara/Downloads/.venv/lib/python3.12/site-packages/ray/air/util/tensor_extensions/arrow.py:736: RuntimeWarning: invalid value encountered in scalar divide
  offsets = np.arange(
2025-10-17 17:18:09,499 WARNING arrow.py:189 -- Failed to convert column 'array' into pyarrow array due to: Error converting data to Arrow: column: 'array', shape: (1, 2, 0), dtype: int8, data: []; falling back to serialize as pickled python objects
Traceback (most recent call last):
  File "/Users/chris.ohara/Downloads/.venv/lib/python3.12/site-packages/ray/air/util/tensor_extensions/arrow.py", line 672, in from_numpy
    return cls._from_numpy(arr)
           ^^^^^^^^^^^^^^^^^^^^
  File "/Users/chris.ohara/Downloads/.venv/lib/python3.12/site-packages/ray/air/util/tensor_extensions/arrow.py", line 736, in _from_numpy
    offsets = np.arange(
              ^^^^^^^^^^
ValueError: arange: cannot compute length

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/Users/chris.ohara/Downloads/.venv/lib/python3.12/site-packages/ray/air/util/tensor_extensions/arrow.py", line 141, in convert_to_pyarrow_array
    return ArrowTensorArray.from_numpy(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/chris.ohara/Downloads/.venv/lib/python3.12/site-packages/ray/air/util/tensor_extensions/arrow.py", line 678, in from_numpy
    raise ArrowConversionError(data_str) from e
ray.air.util.tensor_extensions.arrow.ArrowConversionError: Error converting data to Arrow: column: 'array', shape: (1, 2, 0), dtype: int8, data: []
2025-10-17 17:18:09,789 INFO logging.py:293 -- Registered dataset logger for dataset dataset_0_0
2025-10-17 17:18:09,815 WARNING resource_manager.py:134 -- ⚠️  Ray's object store is configured to use only 33.5% of available memory (2.0GiB out of 6.0GiB total). For optimal Ray Data performance, we recommend setting the object store to at least 50% of available memory. You can do this by setting the 'object_store_memory' parameter when calling ray.init() or by setting the RAY_DEFAULT_OBJECT_STORE_MEMORY_PROPORTION environment variable.
{'array': array([array([], shape=(2, 0), dtype=int8)], dtype=object)}

This PR fixes the issue so that zero-length arrays are serialized correctly, and the shape and dtype is preserved.

Additional information

This is ray==2.50.0.

[gemini-code-assist]

Code Review

This pull request correctly addresses the serialization issue with zero-length numpy arrays by adding a special case for when num_items_per_element is zero. The fix is clean and directly solves the ValueError from np.arange. The addition of a new test case ensures this scenario is covered going forward. I've suggested a small improvement to the new test to make it more robust by parameterizing it with various zero-length array shapes.