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Raise a friendly message when a str is provided to TensorFrame(col_names_dict) instead of a list[str] #469

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Dec 7, 2024
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Raise a friendly message when a str is provided to TensorFrame(col_names_dict) instead of a list[str] #469

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8 changes: 8 additions & 0 deletions test/data/test_tensor_frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -245,3 +245,11 @@ def test_custom_tf_get_col_feat():
assert torch.equal(feat, feat_dict['numerical'][:, 0:1])
feat = tf.get_col_feat('num_2')
assert torch.equal(feat, feat_dict['numerical'][:, 1:2])


def test_non_list_col_names_dict():
feat_dict = {torch_frame.categorical: torch.randint(0, 3, size=(10, 1))}
# Oops, user provided a single column name without wrapping it in a list:
col_names_dict = {torch_frame.categorical: 'cat_1'}
with pytest.raises(ValueError, match='must be a list of column names'):
TensorFrame(feat_dict, col_names_dict)
8 changes: 7 additions & 1 deletion torch_frame/data/tensor_frame.py
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Expand Up @@ -95,7 +95,13 @@ def validate(self) -> None:
num_rows = self.num_rows
empty_stypes: list[torch_frame.stype] = []
for stype_name, feats in self.feat_dict.items():
num_cols = len(self.col_names_dict[stype_name])
col_names = self.col_names_dict[stype_name]
if not isinstance(col_names, list):
raise ValueError(
f"col_names_dict[{stype_name}] must be a list of column "
f"names.")

num_cols = len(col_names)
if num_cols == 0:
empty_stypes.append(stype_name)

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