Fix dataframe_to_mds for non-nullable ArrayType columns

[discobot]

Description of changes:

dataframe_to_mds rejects array columns declared with containsNull=False, as reported in the issue.

This PR implements the element-type lookup suggested there: map_spark_dtype now normalizes arrays to ArrayType(elementType) before the SPARK_TO_MDS lookup, mirroring the existing DecimalType normalization directly above. Both call sites are covered (user-defined-columns validation and automatic schema inference), and the change is safe because the MDS ndarray:* encodings don't depend on array nullability.

Added regression tests: schema inference on a containsNull=False array column, plus end-to-end conversion with both auto-inferred and user-defined columns. They fail without the source change; with it, tests/base/converters/test_dataframe_to_mds.py passes locally (24 passed).

Issue #, if available:

• Fixes dataframe_to_mds fails with non-nullable ArrayType #870

Merge Checklist:

Put an x without space in the boxes that apply. If you are unsure about any checklist, please don't hesitate to ask. We are here to help! This is simply a reminder of what we are going to look for before merging your pull request.

General

• I have read the contributor guidelines
• This is a documentation change or typo fix. If so, skip the rest of this checklist.
• I certify that the changes I am introducing will be backward compatible, and I have discussed concerns about this, if any, with the MosaicML team.
• I have updated any necessary documentation, including README and API docs (if appropriate).

Tests

• I ran pre-commit on my change. (check out the pre-commit section of prerequisites)
• I have added tests that prove my fix is effective or that my feature works (if appropriate).
• I ran the tests locally to make sure it pass. (check out testing)
• I have added unit and/or integration tests as appropriate to ensure backward compatibility of the changes.

_{Authored with the help of Claude Code.}