Update app.py

app.py

@@ -25,19 +25,18 @@ def get_oauth_info(profile: gr.OAuthProfile | None, oauth_token: gr.OAuthToken |
         return print(f'{profile.username}: {org_names}')
 
 
-def compile_model(model_name):
+def compile_model(model_name, sram_size, tensor_size):
 
     if oauth_info['token'] is None:
         return "ERROR - please log into HuggingFace to continue"
 
     # Run the comparison
-    model = 'hello_world.tflite'
     out_dir = './tmp'
     model_loc = 'sram'
 
     # Run the model fitter
     results = sr100_model_compiler.sr100_model_compiler(
-        model_file=model,
+        model_file=model_name,
         output_dir=f"{out_dir}",
         model_loc=f"{model_loc}",
     )
@@ -57,19 +56,31 @@ def compile_model(model_name):
     # Run the training
 #    return model.run_training(epochs=epochs, batch=batch)
 
-    return f"Compiled model {success} {perf_data}"
+    return f"Compiled model: {sram_size} {tensor_size} {success} {perf_data}"
+
+#def process_data(slider_value):
+#    return slider_value * 2
+
 
 with gr.Blocks() as demo:
     gr.LoginButton()
-    text1 = gr.Markdown("Starting to test SyNet")
-    user_text = gr.Markdown("")
+    text1 = gr.Markdown("SR100 Model Compiler - Compile a tflite model to SR100")
+    
 
-    model_text = gr.Textbox(label='LiteRT Model', value='Synaptics/my_model')
+    # Deploy the two slides
+    sram_slider = gr.Slider(minimum=0, maximum=3, step=0.1, label="Set total SRAM size available in MB", value=3)
+    tensor_slider = gr.Slider(minimum=0, maximum=3, step=0.1, label="Set the SRAM size for tensor calculations in MB", value=1.5)
+    #output_text = gr.Textbox(label="Output")
+    
+    model_text = gr.Textbox(label='TFlite model', value='hello_world.tflite')
 
     compile_btn = gr.Button("Compile Model")
-    compile_text = gr.Markdown("Click to load dataset")
-
-    compile_btn.click(compile_model, inputs=[model_text], outputs=[compile_text])
+    compile_text = gr.Markdown("Waiting for model")
+    user_text = gr.Markdown("")
+    
+    # Compute options
+    compile_btn.click(compile_model, inputs=[model_text, sram_slider, tensor_slider], outputs=[compile_text])
+    #my_slider.change(fn=process_data, inputs=my_slider, outputs=output_text)
     demo.load(get_oauth_info, inputs=None, outputs=user_text)
 
 if __name__ == "__main__":