fix featurization freesolv

[ARY2260]

Description

The freesolv CSV featurization with molgraphconv featurizer is failing because of a deprecation in numpy module.
Few months back, I made a PR to address some error where this deprication warning had popped up in a part of the code. #2937 (comment)

This error is present elsewhere in the code as well. For example, this error occurred during featurization using molgraphconv featurizer, where the list of GraphData objects is converted to a np.array. It would have worked just fine if all the elements in the list were GraphData objects, but some molecules threw exception during featurization (eg: C, N, S) and were appended as empty numpy array (of. default dtype = Float) to the list.

Since now the list contained arrays of dtype=GraphData and dtype=Float, numpy failed to convert the non-homogeneous list to array. (Due to a feature deprecation)

Error: np.asarray(features)
Possible Fix: np.asarray(features, dtype=object)

Type of change

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• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
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• Documentations (modification for documents)

Checklist

• My code follows the style guidelines of this project
  • Run yapf -i <modified file> and check no errors (yapf version must be 0.32.0)
  • Run mypy -p deepchem and check no errors
  • Run flake8 <modified file> --count and check no errors
  • Run python -m doctest <modified file> and check no errors
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• I have added tests that prove my fix is effective or that my feature works
• New unit tests pass locally with my changes
• I have checked my code and corrected any misspellings

[rbharath]

There are number of tests breaking, especially with computing statistics from the disk dataset. Can you verify and ensure that no new tests break because of this PR?

[ARY2260]

@rbharath The PR is ready for review. The failing tests are not related to this PR.

[rbharath]

LGTM