Update get_trace to work for preference learning experiments

[shrutipatel31]

Summary: This diff adds a new property to the Experiment class called is_preference_learning_problem. This property checks if the experiment is a preference learning (BOPE) experiment by checking if the optimization config is a PreferenceOptimizationConfig or if there is a PE_EXPERIMENT (preference exploration) auxiliary experiment attached. This property is useful for identifying preference learning experiments in Ax.

Differential Revision: D87347126

[meta-codesync[bot]]

@shrutipatel31 has exported this pull request. If you are a Meta employee, you can view the originating Diff in D87347126.

[codecov-commenter]

Codecov Report

:x: Patch coverage is 95.16129% with 6 lines in your changes missing coverage. Please review. :white_check_mark: Project coverage is 96.52%. Comparing base (e26c9d7) to head (d10b696).

Files with missing lines	Patch %	Lines
ax/service/utils/best_point.py	85.36%	6 Missing :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #4553      +/-   ##
==========================================
+ Coverage   96.50%   96.52%   +0.01%     
==========================================
  Files         557      557              
  Lines       57359    57479     +120     
==========================================
+ Hits        55356    55480     +124     
+ Misses       2003     1999       -4     

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