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[MNT] Avoid CI fail on deep test by generating at least 2 classes in random data #485

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merged 5 commits into from
Jun 13, 2023
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[MNT] Avoid CI fail on deep test by generating at least 2 classes in random data #485

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1eaefb1
[MNT] added try and catch to test deep classifier
hadifawaz1999 Jun 12, 2023
244f572
[MNT] same for deep regressors test
hadifawaz1999 Jun 12, 2023
881a0b1
[MNT] added message in catch
hadifawaz1999 Jun 12, 2023
038740e
removed try and catch just generate insuring at least 2 classes
hadifawaz1999 Jun 13, 2023
44056c6
same for regression
hadifawaz1999 Jun 13, 2023
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11 changes: 6 additions & 5 deletions aeon/classification/deep_learning/tests/test_deep_classifier_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
import pytest

from aeon.classification.deep_learning.base import BaseDeepClassifier
from aeon.utils._testing.collection import make_2d_test_data
from aeon.utils.validation._dependencies import _check_soft_dependencies

__author__ = ["achieveordie", "hadifawaz1999"]
Expand Down Expand Up @@ -56,17 +57,17 @@ def _fit(self, X, y):
reason="skip test if required soft dependency not available",
)
def test_dummy_deep_classifier():
import numpy as np

last_file_name = str(time.time_ns())

# create a dummy deep classifier
dummy_deep_clf = _DummyDeepClassifier(last_file_name=last_file_name)

# generate random data

X, y = make_2d_test_data()

# test fit function on random data
dummy_deep_clf.fit(
X=np.random.normal(size=(10, 100)), y=np.random.choice([0, 1], size=(10,))
)
dummy_deep_clf.fit(X=X, y=y)

# test save last model to file than delete it

Expand Down
11 changes: 6 additions & 5 deletions aeon/regression/deep_learning/tests/test_deep_regressor_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
import pytest

from aeon.regression.deep_learning.base import BaseDeepRegressor
from aeon.utils._testing.collection import make_2d_test_data
from aeon.utils.validation._dependencies import _check_soft_dependencies

__author__ = ["achieveordie", "hadifawaz1999"]
Expand Down Expand Up @@ -53,17 +54,17 @@ def _fit(self, X, y):
reason="skip test if required soft dependency not available",
)
def test_dummy_deep_regressor():
import numpy as np

last_file_name = str(time.time_ns())

# create a dummy regressor
dummy_deep_rg = _DummyDeepRegressor(last_file_name=last_file_name)

# generate random data

X, y = make_2d_test_data()

# test fit function on random data
dummy_deep_rg.fit(
X=np.random.normal(size=(10, 100)), y=np.random.normal(size=(10,))
)
dummy_deep_rg.fit(X=X, y=y)

# test save last model to file than delete it

Expand Down