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Fix: Issue 261 - Prediction irregularity format for LoadedModel #262

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Fix: Issue 261 - Prediction irregularity format for LoadedModel #262

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15 changes: 9 additions & 6 deletions ctlearn/tools/predict_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -473,6 +473,7 @@ def _predict_with_model(self, model_path):
prediction_colname = (
"type" if isinstance(model.layers[-1], keras.layers.Softmax) else model.layers[-1].name
)
self.log.info("Checking column name for prediction : %s", prediction_colname)
backbone_model, feature_vectors = None, None
if self.dl1_features:
# Get the backbone model which is the second layer of the model
Expand Down Expand Up @@ -525,21 +526,23 @@ def _predict_with_model(self, model_path):
# which returns the probabilities for each class in an array, while
# the regression tasks have output neurons which returns the
# predicted value for the task in a dictionary.
if prediction_colname == "type":
predict_data = Table({prediction_colname: predict_data})
if isinstance(predict_data, dict) and prediction_colname in predict_data:
predict_data = Table({prediction_colname: predict_data[prediction_colname]})
else:
predict_data = Table(predict_data)
predict_data = Table({prediction_colname: predict_data})
# Predict the last batch and stack the results to the prediction data
if data_loader_last_batch is not None:
predict_data_last_batch = model.predict(
data_loader_last_batch, verbose=self.keras_verbose
)
if model.layers[-1].name == "type":
if isinstance(predict_data_last_batch, dict) and prediction_colname in predict_data_last_batch:
predict_data_last_batch = Table(
{prediction_colname: predict_data_last_batch}
{prediction_colname: predict_data_last_batch[prediction_colname]}
)
else:
predict_data_last_batch = Table(predict_data_last_batch)
predict_data_last_batch = Table(
{prediction_colname: predict_data_last_batch}
)
predict_data = vstack([predict_data, predict_data_last_batch])
return predict_data, feature_vectors

Expand Down