Change scipy.sparse.csr.csr_matrix to scipy.sparse.csr_matrix

Signed-off-by: Avi Shinnar <shinnar@us.ibm.com>

lale/helpers.py

@@ -832,7 +832,7 @@ def create_data_loader(X, y=None, batch_size=1, num_workers=0, shuffle=True):
     elif isinstance(X, pd.DataFrame):
         dataset = PandasTorchDataset(X, y)
         collate_fn = pandas_collate_fn
-    elif isinstance(X, scipy.sparse.csr.csr_matrix):
+    elif isinstance(X, scipy.sparse.csr_matrix):
         # unfortunately, NumpyTorchDataset won't accept a subclass of np.ndarray
         X = X.toarray()  # type: ignore
         if isinstance(y, lale.datasets.data_schemas.NDArrayWithSchema):

lale/lib/sklearn/one_hot_encoder.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import pandas as pd
-import scipy.sparse.csr
+import scipy.sparse
 import sklearn
 import sklearn.preprocessing
 from packaging import version
@@ -155,7 +155,7 @@ def transform(self, X):
                 columns = self._wrapped_model.get_feature_names_out(X.columns)
             else:
                 columns = self._wrapped_model.get_feature_names(X.columns)
-            if isinstance(result, scipy.sparse.csr.csr_matrix):
+            if isinstance(result, scipy.sparse.csr_matrix):
                 result = result.toarray()
             result = pd.DataFrame(data=result, index=X.index, columns=columns)
         return result