Update app.py

app.py

@@ -161,75 +161,46 @@ dataset = st.sidebar.selectbox(
     index=0,
 )
 
-selectable_configs = list(set(dataset_df["config"]))
-selectable_configs.sort(key=lambda name: name.lower())
-selectable_configs.remove("-unspecified-")
-selectable_configs = [config for config in selectable_configs if config in LANGUAGES]
-
-visual_configs = [f"{config}: {LANGUAGES[config]}" for config in selectable_configs]
-
-config = st.sidebar.selectbox(
-    "Language",
-    visual_configs,
-    index=0,
-    help="Filter the results on the current leaderboard by language."
-)
-
-config = config.split(":")[0]
-
-dataset_df = dataset_df[dataset_df.config == config]
-
 split = st.sidebar.selectbox(
     "Split",
     [split],
     index=0,
 )
 
-not_selectable_metrics = ["model_id", "dataset", "split", "config", "pipeline_tag", "only_verified"]
-# also ignore irrelevant ASR metrics
-not_selectable_metrics.extend(["wer_without_norm", "mer"])
+selectable_metrics = ["wer", "cer"]
+sorting_metric = "wer"
 
-selectable_metrics = list(filter(lambda column: column not in not_selectable_metrics, dataset_df.columns))
-
-dataset_df = dataset_df.filter(["model_id"] + (["dataset"] if dataset == "-any-" else []) + selectable_metrics)
-dataset_df = dataset_df.dropna(thresh=2)  # Want at least two non-na values (one for model_id and one for a metric).
-
-sorting_metric = st.sidebar.radio(
-    "Sorting Metric",
-    selectable_metrics,
-    index=selectable_metrics.index(default_metric) if default_metric in selectable_metrics else 0,
-    help="Select the metric to sort the leaderboard by. Click on the metric name in the leaderboard to reverse the sorting order."
-)
+selectable_configs = list(set(dataset_df["config"]))
+selectable_configs.sort(key=lambda name: name.lower())
+selectable_configs.remove("-unspecified-")
+selectable_configs = [config for config in selectable_configs if config in LANGUAGES]
+visual_configs = [f"{config}: {LANGUAGES[config]}" for config in selectable_configs]
 
-current_query_params.update({"metric": [sorting_metric]})
+dataset_df = dataset_df[["config", "model_id"] + selectable_metrics]
+all_ds = []
 
-st.experimental_set_query_params(**current_query_params)
+for config in selectable_configs:
+    dataset_df_ds = dataset_df[dataset_df.config == config]
 
-st.markdown(
-    f"This is the leaderboard for {LANGUAGES[config]} ({config})."
-)
+    dataset_df_ds = dataset_df_ds.dropna(thresh=2)  # Want at least two non-na values (one for model_id and one for a metric)
 
-st.markdown(
-    "Please click on the model's name to be redirected to its model card."
-)
+    # Make the default metric appear right after model names and dataset names
+    cols = dataset_df_ds.columns.tolist()
+    cols.remove(sorting_metric)
+    sorting_metric_index = 1 if dataset != "-any-" else 2
+    cols = cols[:sorting_metric_index] + [sorting_metric] + cols[sorting_metric_index:]
+    dataset_df_ds = dataset_df_ds[cols]
 
-st.markdown(
-    "Want to beat the leaderboard? Don't see your model here? Simply ..."
-)
+    # Sort the leaderboard, giving the sorting metric highest priority and then ordering by other metrics in the case of equal values.
+    dataset_df_ds = dataset_df_ds.sort_values(by=cols[sorting_metric_index:], ascending=[metric in ascending_metrics for metric in cols[sorting_metric_index:]])
+    dataset_df_ds = dataset_df_ds.replace(np.nan, '-')
 
-# Make the default metric appear right after model names and dataset names
-cols = dataset_df.columns.tolist()
-cols.remove(sorting_metric)
-sorting_metric_index = 1 if dataset != "-any-" else 2
-cols = cols[:sorting_metric_index] + [sorting_metric] + cols[sorting_metric_index:]
-dataset_df = dataset_df[cols]
+    all_ds.append(dataset_df_ds.iloc[0])
 
-# Sort the leaderboard, giving the sorting metric highest priority and then ordering by other metrics in the case of equal values.
-dataset_df = dataset_df.sort_values(by=cols[sorting_metric_index:], ascending=[metric in ascending_metrics for metric in cols[sorting_metric_index:]])
-dataset_df = dataset_df.replace(np.nan, '-')
+all_ds = pd.DataFrame(all_ds, columns=["config", "model_id", "wer", "cer"])
 
 # Make the leaderboard
-gb = GridOptionsBuilder.from_dataframe(dataset_df)
+gb = GridOptionsBuilder.from_dataframe(all_ds)
 gb.configure_default_column(sortable=False)
 gb.configure_column(
     "model_id",
@@ -242,9 +213,9 @@ for name in selectable_metrics:
 gb.configure_column(
     sorting_metric,
     sortable=True,
-    cellStyle=JsCode('''function(params) { return {'backgroundColor': '#FFD21E'}}''')
+    #cellStyle=JsCode('''function(params) { return {'backgroundColor': '#FFD21E'}}''')
 )
 
 go = gb.build()
-fit_columns = len(dataset_df.columns) < 10
-AgGrid(dataset_df, gridOptions=go, height=28*len(dataset_df) + (35 if fit_columns else 41), allow_unsafe_jscode=True, fit_columns_on_grid_load=fit_columns, enable_enterprise_modules=False)
+fit_columns = len(all_ds.columns) < 10
+AgGrid(all_ds, gridOptions=go, height=28*len(all_ds) + (35 if fit_columns else 41), allow_unsafe_jscode=True, fit_columns_on_grid_load=fit_columns, enable_enterprise_modules=False)