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[fix] Change int to np.int32 for the ndarray dtype specification #371

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Jan 31, 2022
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[fix] Change int to np.int32 for the ndarray dtype specification #371

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2 changes: 1 addition & 1 deletion autoPyTorch/pipeline/components/setup/network_embedding/base_network_embedding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ def _get_args(self, X: Dict[str, Any]) -> Tuple[int, np.ndarray]:
num_numerical_columns = numerical_column_transformer.transform(
X_train[:, X['dataset_properties']['numerical_columns']]).shape[1]
num_input_features = np.zeros((num_numerical_columns + len(X['dataset_properties']['categorical_columns'])),
dtype=int)
dtype=np.int32)
categories = X['dataset_properties']['categories']

for i, category in enumerate(categories):
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2 changes: 1 addition & 1 deletion autoPyTorch/pipeline/create_searchspace_util.py
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Expand Up @@ -47,7 +47,7 @@ def get_match_array(
matches_dimensions = [len(choices) for choices in node_i_choices]
# Start by allowing every combination of nodes. Go through all
# combinations/pipelines and erase the illegal ones
matches = np.ones(matches_dimensions, dtype=int)
matches = np.ones(matches_dimensions, dtype=np.int32)

# TODO: Check if we need this, like are there combinations from the
# pipeline we should dynamically avoid?
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