Update app.py

app.py

@@ -45,6 +45,14 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc):
 
     default_config = sr100_model_compiler.sr100_default_config()
     success, perf_data = sr100_model_compiler.sr100_check_model(results=results, config=default_config)
+
+    output_text = ''
+    if success:
+        output_text = 'SUCCESS, model fits on SR100'
+    else:
+        output_text = 'FAILULRE model does not fit on SR100'
+    for key, value in perf_data.items():
+        output_text += '\n{key} = {value}'
     
 #    try:
 #        epochs = int(epochs_text)
@@ -53,16 +61,14 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc):
 #        epochs = 100
 #        batch = 16
 #        print(f'ERROR converting {epochs_text}, and {batch_text}')
+    return output_text
+    
+    
+def update_sliders(sram_slider_value, tensor_slider_value):
 
-    # Run the training
-#    return model.run_training(epochs=epochs, batch=batch)
-
-    return f"Compiled model: {sram_size} {tensor_size} {success} {perf_data}"
-
-#def process_data(slider_value):
-#    return slider_value * 2
-def update_sliders(sram_slider_value):
-    return gr.update(maximum=sram_slider_value, value=sram_slider_value>>1)
+    if tensor_slider_value > sram_slider_value:
+        tensor_slider_value = sram_slider_value-0.1
+    return gr.update(maximum=sram_slider_value, value=tensor_slider_value)    
 
 with gr.Blocks() as demo:
     gr.LoginButton()
@@ -84,7 +90,7 @@ with gr.Blocks() as demo:
     
     # Compute options
     compile_btn.click(compile_model, inputs=[model_text, sram_slider, tensor_slider, optimize, model_loc], outputs=[compile_text])
-    sram_slider.change(fn=update_sliders, inputs=sram_slider, outputs=tensor_slider)
+    sram_slider.change(fn=update_sliders, inputs=[sram_slider, tensor_slider], outputs=tensor_slider)
     demo.load(get_oauth_info, inputs=None, outputs=user_text)
 
 if __name__ == "__main__":