Update app.py

app.py

@@ -25,7 +25,7 @@ def get_oauth_info(profile: gr.OAuthProfile | None, oauth_token: gr.OAuthToken |
         return print(f'{profile.username}: {org_names}')
 
 
-def compile_model(model_name, sram_size, tensor_size, optimize, model_loc):
+def compile_model(model_name, sram_size, tensor_size, optimize, model_loc, clock):
 
     if oauth_info['token'] is None:
         return "ERROR - please log into HuggingFace to continue"
@@ -44,6 +44,9 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc):
     print(results)
 
     default_config = sr100_model_compiler.sr100_default_config()
+
+    default_config['sram_size'] = int(float(sram_size)*1.0e6)
+    default_config['core_clock'] = int(float(clock)*1.0e6)
     success, perf_data = sr100_model_compiler.sr100_check_model(results=results, config=default_config)
 
     output_text = ''
@@ -52,7 +55,7 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc):
     else:
         output_text = 'FAILULRE model does not fit on SR100'
     for key, value in perf_data.items():
-        output_text += '\n{key} = {value}'
+        output_text += f'<br>{key} = {value}'
     
 #    try:
 #        epochs = int(epochs_text)
@@ -66,9 +69,9 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc):
     
 def update_sliders(sram_slider_value, tensor_slider_value):
 
-    if tensor_slider_value > sram_slider_value:
+    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)    
+    return gr.update(value=tensor_slider_value)    
 
 with gr.Blocks() as demo:
     gr.LoginButton()
@@ -79,6 +82,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         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)
+        clock_slider = gr.Slider(minimum=100, maximum=400, step=10, label="Sets core clock frequeny (MHz)", value=400)
     optimize = gr.Radio(choices=["Performance", "Size"], value='Performance', label='Performance model')
     model_loc = gr.Radio(choices=["sram", "flash"], value="sram", label='Model weights target')
     
@@ -89,7 +93,7 @@ with gr.Blocks() as demo:
     compile_text = gr.Markdown("Waiting for model results")
     
     # Compute options
-    compile_btn.click(compile_model, inputs=[model_text, sram_slider, tensor_slider, optimize, model_loc], outputs=[compile_text])
+    compile_btn.click(compile_model, inputs=[model_text, sram_slider, tensor_slider, optimize, model_loc, clock_slider], outputs=[compile_text])
     sram_slider.change(fn=update_sliders, inputs=[sram_slider, tensor_slider], outputs=tensor_slider)
     demo.load(get_oauth_info, inputs=None, outputs=user_text)