[feat] Add new task inference for APT

[nabenabe0928]

Types of changes

• Bug fix (non-breaking change which fixes an issue)

Checklist:

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.

• Have you checked to ensure there aren't other open Pull Requests for the same update/change?
• Have you added an explanation of what your changes do and why you'd like us to include them?
• Have you written new tests for your core changes, as applicable?
• Have you successfully ran tests with your changes locally?

Description

This is the hotfix for the issue#352.
Since the inference of the task type in sklearn does not properly handle the continuous, I added a feature to filter continuous (i.e. regression task) from multiclass.

Motivation and Context

see issue#352..

How has this been tested?

It is not tested by proper pytest, but I checked by the following locally.
Note that data.csv is available in issue#352.

from autoPyTorch.api.tabular_regression import TabularRegressionTask
import pandas as pd
from sklearn.model_selection import train_test_split


input = [
    "P1",
    "P5p1",
    "P6p2",
    "P11p4",
    "P14p9",
    "P15p1",
    "P15p3",
    "P16p2",
    "P18p2",
    "P27p4",
    "H2p2",
    "H8p2",
    "H10p1",
    "H13p1",
    "H18pA",
    "H40p4",
]
output = ["price"]

if __name__ == '__main__':
    # read dataframe
    df = pd.read_csv("data.csv")

    # split data
    X = df[input]
    y = df[output]
    X_train, X_test, y_train, y_test = train_test_split(
        X, y, train_size=0.8, random_state=1
    )

    # train model
    api = TabularRegressionTask(n_jobs=7)
    api.search(
        X_train=X_train,
        y_train=y_train,
        X_test=X_test.copy(),
        y_test=y_test.copy(),
        optimize_metric="r2",
        total_walltime_limit=120,
    )

Note that the original code yields the following error by the same code:

Traceback (most recent call last):
  File "bug_test.py", line 39, in <module>
    api.search(
  File "/home/Auto-PyTorch/autoPyTorch/api/tabular_regression.py", line 300, in search
    return self._search(
  File "/home/Auto-PyTorch/autoPyTorch/api/base_task.py", line 876, in _search
    raise ValueError("Incompatible dataset entered for current task,"
ValueError: Incompatible dataset entered for current task,expected dataset to have task type :tabular_regression got :tabular_classification

[codecov]

Codecov Report

Merging #386 (0d9344b) into development (4a0c773) will increase coverage by 0.24%.
The diff coverage is 96.07%.

@@               Coverage Diff               @@
##           development     #386      +/-   ##
===============================================
+ Coverage        83.31%   83.55%   +0.24%     
===============================================
  Files              162      162              
  Lines             9492     9519      +27     
  Branches          1653     1659       +6     
===============================================
+ Hits              7908     7954      +46     
+ Misses            1109     1090      -19     
  Partials           475      475              

Impacted Files	Coverage Δ
autoPyTorch/datasets/base_dataset.py	80.28% <83.33%> (-0.32%)	⬇️
autoPyTorch/data/base_feature_validator.py	100.00% <100.00%> (ø)
autoPyTorch/data/base_target_validator.py	97.95% <100.00%> (ø)
autoPyTorch/data/base_validator.py	92.00% <100.00%> (ø)
autoPyTorch/data/tabular_feature_validator.py	91.13% <100.00%> (ø)
autoPyTorch/data/tabular_target_validator.py	93.04% <100.00%> (+1.29%)	⬆️
autoPyTorch/utils/common.py	89.74% <100.00%> (+0.13%)	⬆️
...ipeline/components/setup/network_backbone/utils.py	87.12% <0.00%> (-1.52%)	⬇️
...orch/pipeline/components/training/metrics/utils.py	90.00% <0.00%> (+2.50%)	⬆️
...omponents/training/data_loader/base_data_loader.py	94.66% <0.00%> (+2.66%)	⬆️
... and 8 more

---

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[ravinkohli]

Thanks for these changes. I have left a suggestion and I have a minor question otherwise I think we can merge this

[ravinkohli]

could you tell me why are you adding 1?

[nabenabe0928]

I added an explanation and changed 1 to 1e12 + 10.
Basically, I would like to test here if the function catches a possibility of overflow and raise an error.