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iris.py

@@ -22,7 +22,8 @@ def ClassifyIris(sliSepalLength, sliSepalWidth, sliPetalLength, sliPetalWidth):
     intPrediction = a1intPredictions[0]
     dstrIndexToSpecies = {0: "setosa", 1: "versicolor", 2: "virginica"}
     strSpecies = dstrIndexToSpecies[intPrediction]
-    return f"Iris {strSpecies}"
+    result = f"Iris {strSpecies}"
+    return result
 
 # interface elements
 sliSepalLength = gr.Slider(minimum=4, maximum=9, value=6, label="Sepal length (cm)")
@@ -30,7 +31,7 @@ sliSepalWidth  = gr.Slider(minimum=0, maximum=5, value=3, label="Sepal width (cm
 sliPetalLength = gr.Slider(minimum=1, maximum=8, value=4, label="Petal length (cm)")
 sliPetalWidth  = gr.Slider(minimum=0, maximum=3, value=2, label="Petal width (cm)")
 
-outputs = gr.TextOutput()
+###outputs = gr.TextOutput()
 
 ### result.label = "Iris species" # does not work on Hugging Face
 
@@ -44,5 +45,5 @@ gr.Interface(
         "learning rate = 0.001, maximum depth = 3, n estimators = 3",
     fn=ClassifyIris, 
     inputs=[sliSepalLength, sliSepalWidth, sliPetalLength, sliPetalWidth], 
-    outputs=outputs,  # does not work on Hugging Face
+    outputs=result,  # does not work on Hugging Face
     flagging_options=[]).launch(share=True)