Update metric_for_tp_fp_samples.py

metric_for_tp_fp_samples.py

@@ -119,8 +119,7 @@ class metric_tp_fp_Datasets(evaluate.Metric):
 		return predictions
 	def softmax_topk(self, logits, topk):
 		softmax = torch.softmax(logits, dim=-1)
-		predictions = softmax.topk(topk).indices.tolist()
-		print(predictions)        
+		predictions = softmax.topk(topk).indices.tolist()       
 		return predictions
 	def threshold(self, logits, threshold):
 		predictions = []
@@ -133,7 +132,8 @@ class metric_tp_fp_Datasets(evaluate.Metric):
 		return predictions
 	def topk(self, logits, topk):
 		predictions = logits.topk(topk).indices.tolist()
-		return predictions
+		print(predictions) 
+        return predictions
 
 	#Builds a report with the metrics####################################################
 	def metrics_report(self, true_positives = "", false_positives = ""):