Clean up

app.py

@@ -70,6 +70,18 @@ except Exception:
     restart_space()
 
 
+# Get dataframes
+
+(
+    FINISHED_EVAL_QUEUE_DF,
+    RUNNING_EVAL_QUEUE_DF,
+    PENDING_EVAL_QUEUE_DF,
+    FAILED_EVAL_QUEUE_DF,
+) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
+
+ORIGINAL_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
+
+
 # Searching and filtering
 
 
@@ -232,15 +244,8 @@ def load_query(request: gr.Request):  # triggered only once at startup => read q
 
 # Prepare the dataframes
 
-(
-    finished_eval_queue_df,
-    running_eval_queue_df,
-    pending_eval_queue_df,
-    failed_eval_queue_df,
-) = get_evaluation_queue_df(EVAL_REQUESTS_PATH, EVAL_COLS)
 
-original_df = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
-leaderboard_df = original_df.copy()
+leaderboard_df = ORIGINAL_DF.copy()
 leaderboard_df = filter_models(
     leaderboard_df,
     [t.to_str(" : ") for t in ModelType],
@@ -257,7 +262,7 @@ INITIAL_COLUMNS = ["T"] + [
 ]
 leaderboard_df = select_columns(leaderboard_df, INITIAL_COLUMNS)
 
-MAX_MODEL_SIZE = original_df["#Params (B)"].max()
+MAX_MODEL_SIZE = ORIGINAL_DF["#Params (B)"].max()
 
 
 # Leaderboard demo
@@ -495,7 +500,7 @@ with gr.Blocks() as demo_leaderboard:
 
     # Dummy leaderboard for handling the case when the user uses backspace key
     hidden_leaderboard_table_for_search = gr.Dataframe(
-        value=original_df[COLS],
+        value=ORIGINAL_DF[COLS],
         headers=COLS,
         datatype=TYPES,
         visible=False,
@@ -581,46 +586,46 @@ with gr.Blocks() as demo_submission:
 
         with gr.Column():
             with gr.Accordion(
-                f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
+                f"✅ Finished Evaluations ({len(FINISHED_EVAL_QUEUE_DF)})",
                 open=False,
             ):
                 with gr.Row():
                     finished_eval_table = gr.Dataframe(
-                        value=finished_eval_queue_df,
+                        value=FINISHED_EVAL_QUEUE_DF,
                         headers=EVAL_COLS,
                         datatype=EVAL_TYPES,
                         row_count=5,
                     )
             with gr.Accordion(
-                f"🔄 Running Evaluation Queue ({len(running_eval_queue_df)})",
+                f"🔄 Running Evaluation Queue ({len(RUNNING_EVAL_QUEUE_DF)})",
                 open=False,
             ):
                 with gr.Row():
                     running_eval_table = gr.Dataframe(
-                        value=running_eval_queue_df,
+                        value=RUNNING_EVAL_QUEUE_DF,
                         headers=EVAL_COLS,
                         datatype=EVAL_TYPES,
                         row_count=5,
                     )
 
             with gr.Accordion(
-                f"⏳ Pending Evaluation Queue ({len(pending_eval_queue_df)})",
+                f"⏳ Pending Evaluation Queue ({len(PENDING_EVAL_QUEUE_DF)})",
                 open=False,
             ):
                 with gr.Row():
                     pending_eval_table = gr.Dataframe(
-                        value=pending_eval_queue_df,
+                        value=PENDING_EVAL_QUEUE_DF,
                         headers=EVAL_COLS,
                         datatype=EVAL_TYPES,
                         row_count=5,
                     )
             with gr.Accordion(
-                f"❎ Failed Evaluation Queue ({len(failed_eval_queue_df)})",
+                f"❎ Failed Evaluation Queue ({len(FAILED_EVAL_QUEUE_DF)})",
                 open=False,
             ):
                 with gr.Row():
                     failed_eval_table = gr.Dataframe(
-                        value=failed_eval_queue_df,
+                        value=FAILED_EVAL_QUEUE_DF,
                         headers=EVAL_COLS,
                         datatype=EVAL_TYPES,
                         row_count=5,