Update metric_for_tp_fp_samples.py

metric_for_tp_fp_samples.py

@@ -191,7 +191,7 @@ class metric_tp_fp_Datasets(evaluate.Metric):
 		return results
 
 	#Computes the metric for each prediction strategy##############################################
-	def _compute(self, predictions, references, prediction_strategies = ['argmax_max']):
+	def _compute(self, predictions, references, prediction_strategies = ["argmax_max"]):
 		"""Returns the scores"""
 		# TODO: Compute the different scores of the metric
 		predictions = torch.from_numpy(np.array(predictions, dtype = 'float32'))
@@ -202,6 +202,7 @@ class metric_tp_fp_Datasets(evaluate.Metric):
 		results = {}
 		for prediction_strategy in prediction_strategies:
 			prediction_strategy_name = '-'.join(map(str, prediction_strategy))
+			print(prediction_strategy_name)
 			results[prediction_strategy_name] = {}
 			predicted_labels = self.predict(predictions, prediction_strategy)
 			samples = [0 for i in range(len(classes))]