Update app.py

app.py

@@ -10,6 +10,10 @@ class NumpyArrayEncoder(JSONEncoder):
             return obj.tolist()
         return JSONEncoder.default(self, obj)
 
+def print_shape_through(x):
+    print(x.shape)
+    return x
+
 analysis_network = from_pretrained_keras("cmudrc/wave-energy-analysis")
 synthesis_network = from_pretrained_keras("cmudrc/wave-energy-synthesis")
    
@@ -20,7 +24,7 @@ with gradio.Blocks() as demo:
     analyze_it = gradio.Button("Analyze")
     synthesize_it = gradio.Button("Synthesize")
 
-    analyze_it.click(fn=lambda x: json.dumps(analysis_network.predict(numpy.asarray(json.loads(x))), cls=NumpyArrayEncoder), inputs=[geometry], outputs=[spectrum], api_name="analyze")
-    synthesize_it.click(fn=lambda x: json.dumps(synthesis_network.predict(numpy.asarray(json.loads(x))), cls=NumpyArrayEncoder), inputs=[spectrum], outputs=[geometry], api_name="synthesize")
+    analyze_it.click(fn=lambda x: json.dumps(analysis_network.predict(print_shape_through(numpy.asarray(json.loads(x)))), cls=NumpyArrayEncoder), inputs=[geometry], outputs=[spectrum], api_name="analyze")
+    synthesize_it.click(fn=lambda x: json.dumps(synthesis_network.predict(print_shape_through(numpy.asarray(json.loads(x)))), cls=NumpyArrayEncoder), inputs=[spectrum], outputs=[geometry], api_name="synthesize")
     
 demo.launch()