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Merge branch 'wrappers' into dataset_wrapper_anonimizer

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Ola Saadi 2022-03-28 17:11:41 +03:00 • committed by GitHub Enterprise
commit 5f6a258f8f
2 changed files with 6 additions and 2 deletions
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4
apt/utils/datasets/datasets.py
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@ -18,12 +18,14 @@ from torch import Tensor
logger = logging.getLogger(__name__)
INPUT_DATA_ARRAY_TYPE = Union[np.ndarray, pd.DataFrame, List, Tensor]
OUTPUT_DATA_ARRAY_TYPE = np.ndarray
DATA_PANDAS_NUMPY_TYPE = Union[np.ndarray, pd.DataFrame]
def array2numpy(self, arr: INPUT_DATA_ARRAY_TYPE) -> OUTPUT_DATA_ARRAY_TYPE:
"""
converts from INPUT_DATA_ARRAY_TYPE to numpy array
"""
@ -210,11 +212,13 @@ class PytorchData(Dataset):
if y is not None and len(self._x) != len(self._y):
raise ValueError('Non equivalent lengths of x and y')
if self._y is not None:
self.__getitem__ = self.get_item
else:
self.__getitem__ = self.get_sample_item
def get_samples(self) -> OUTPUT_DATA_ARRAY_TYPE:
"""Return data samples as numpy array"""
return array2numpy(self._x)

4
tests/test_model.py
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@ -1,6 +1,6 @@
import pytest
from apt.utils.models import SklearnClassifier, SklearnRegressor
from apt.utils.models import SklearnClassifier, SklearnRegressor, ModelOutputType
from apt.utils.datasets import ArrayDataset
from apt.utils import dataset_utils
@ -11,7 +11,7 @@ from sklearn.ensemble import RandomForestClassifier
def test_sklearn_classifier():
(x_train, y_train), (x_test, y_test) = dataset_utils.get_iris_dataset()
underlying_model = RandomForestClassifier()
model = SklearnClassifier(underlying_model)
model = SklearnClassifier(underlying_model, ModelOutputType.CLASSIFIER_VECTOR)
train = ArrayDataset(x_train, y_train)
test = ArrayDataset(x_test, y_test)
model.fit(train)