Update app.py

app.py

@@ -38,6 +38,7 @@ def predict(code_txt):
     return with_omp_str if y_hat==1 else without_omp_str, torch.nn.Softmax(dim=1)(pred).squeeze()[y_hat].item()
 
 
+
 def is_private(code_txt):
     if predict(code_txt)[0] == without_omp_str:
         return gr.update(visible=False)
@@ -55,7 +56,7 @@ def is_private(code_txt):
     # if y_hat == 0:
     #     return gr.update(visible=False)
     # else:
-    return gr.update(value=f"{'should not contain private' if y_hat==0 else 'should contain private'} with confidence: {torch.nn.Softmax(dim=1)(pred).squeeze()[y_hat].item()}", visible=True)
+    return gr.update(value=f"Should {'not' if y_hat==0 else ''} contain private with confidence: {torch.nn.Softmax(dim=1)(pred).squeeze()[y_hat].item()}", visible=True)
 
 
 def is_reduction(code_txt, label):
@@ -75,7 +76,7 @@ def is_reduction(code_txt, label):
     # if y_hat == 0:
     #     return gr.update(visible=False)
     # else:
-    return gr.update(value=f"{'should not contain reduction' if y_hat==0 else 'should contain reduction'} with confidence: {torch.nn.Softmax(dim=1)(pred).squeeze()[y_hat].item()}", visible=True)
+    return gr.update(value=f"Should {'not' if y_hat==0 else ''} contain reduction with confidence: {torch.nn.Softmax(dim=1)(pred).squeeze()[y_hat].item()}", visible=True)
 
 
 # Define GUI
@@ -96,7 +97,7 @@ with gr.Blocks() as pragformer_gui:
                 drop = gr.Dropdown(list(data.keys()), label="Mix of parallel and not-parallel code snippets", value="Minyoung-Kim1110/OpenMP/Excercise/atomic/0")
                 sample_btn = gr.Button("Sample")
             
-            pragma =  gr.Textbox(label="Original Parallelization Classification (if any)")
+            pragma =  gr.Textbox(label="Original parallelization classification (if any)")
 
         code_in = gr.Textbox(lines=5, label="Write some code and see if it should contain a parallel work-sharing loop construct")
         submit_btn = gr.Button("Submit")
@@ -108,8 +109,8 @@ with gr.Blocks() as pragformer_gui:
             confidence_out = gr.Textbox(label="Confidence")
 
         with gr.Row():
-            private = gr.Textbox(label="Private", visible=False)
-            reduction = gr.Textbox(label="Reduction", visible=False)
+            private = gr.Textbox(label="Data-sharing attribute clause- private", visible=False)
+            reduction = gr.Textbox(label="Data-sharing attribute clause- reduction", visible=False)
 
     submit_btn.click(fn=predict, inputs=code_in, outputs=[label_out, confidence_out])
     submit_btn.click(fn=is_private, inputs=code_in, outputs=private)