Pass X_train, y_train in Engine.submit_scoring_job for time series

[freddyaboulton]

Pull Request Description

Fixes #2785

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After creating the pull request: in order to pass the release_notes_updated check you will need to update the "Future Release" section of docs/source/release_notes.rst to include this pull request by adding :pr:123.

[codecov]

Codecov Report

Merging #2786 (23aeeb5) into main (d54173a) will increase coverage by 0.8%.
The diff coverage is 100.0%.

@@           Coverage Diff           @@
##            main   #2786     +/-   ##
=======================================
+ Coverage   99.0%   99.8%   +0.8%     
=======================================
  Files        298     298             
  Lines      27646   27681     +35     
=======================================
+ Hits       27364   27613    +249     
+ Misses       282      68    -214     

Impacted Files	Coverage Δ
evalml/automl/automl_search.py	99.9% <100.0%> (+0.2%)	⬆️
evalml/automl/engine/cf_engine.py	100.0% <100.0%> (ø)
evalml/automl/engine/dask_engine.py	100.0% <100.0%> (ø)
evalml/automl/engine/engine_base.py	100.0% <100.0%> (ø)
evalml/automl/engine/sequential_engine.py	100.0% <100.0%> (ø)
evalml/tests/automl_tests/dask_test_utils.py	100.0% <100.0%> (ø)
...ts/automl_tests/parallel_tests/test_automl_dask.py	100.0% <100.0%> (ø)
evalml/tests/automl_tests/test_automl.py	99.7% <0.0%> (+0.1%)	⬆️
evalml/automl/utils.py	100.0% <0.0%> (+1.7%)	⬆️
... and 6 more

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[freddyaboulton]

@chukarsten Check it out - threaded engines respect mocks

[ParthivNaresh]

Solid catch, looks good!

[angela97lin]

Looks good! 😁

[angela97lin]

Just for my own curiosity: theoretically, if send_data_to_cluster supported more arguments, this could have been combined with the line above, right? 🤔

[angela97lin]

Omega nitpick: could probably combine these lines to:

X_train, y_train = pd.DataFrame(X[:50]), pd.Series(y[:50])
X_test, y_test = pd.DataFrame(X[50:]), pd.Series(y[50:])

But might just be personal preference 😅

Side note: This is probably a task for the larger test refactoring/cleanup PR, but I wonder if it's worth making our fixtures dataframes, since we've slowly been moving away from explicitly supporting numpy arrays lol

[freddyaboulton]

@angela97lin Agreed that having our most common fixtures be numpy arrays is not ideal - maybe tests our code with unrepresentative inputs compared to what a user would pass in!