Fixes test on ci

[arunppsg]

Description

CI test for some of the featurizers where failing with an error similar to

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (2, 2) + inhomogeneous part

The error occured from numpy version 24.

During the featurization process, some featurizers returned arrays of various shapes for a different data points. It was especially the case with tokenizers, where the result of returned array depend on the number of input tokens. In numpy versions prior to 24, numpy ignores these issues but from 24, it expected these datapoints to have a dtype of object. There were two possible solutions:

• set dtype as object in base featurizer class (a dtype of object says that the object stored in the numpy array is a python datatype)
• update tokenizers to return encoding with padding, so that the we don't have inhomogenous shape

I chose the latter one because:

• most of the models work on encodings of uniform length
• we lose the precision offered by storing the data points in the original datatype (float, int, etc)

Hence, I added padding with max length for roberta tokenizer and reaction tokenizer and updated tests for the same.

I also noticed a failure in xgboost which was also fixed.

Type of change

Please check the option that is related to your PR.

• 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)
  • In this case, we recommend to discuss your modification on GitHub issues before creating the PR
• 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]

@arunppsg I think there are some mypy errors here. Could you take a quick look and fix?

[shreyasvinaya]

@arunppsg can you rerun the CI?, the mypy issues are now fixed

[rbharath]

LGTM