Update app.py

app.py

@@ -81,7 +81,7 @@ methods = list(set(df_results['Unlearned_Methods']))
 all_columns = ['Unlearned_Methods','Source', 'Diffusion_Models','Pre-ASR', 'Post-ASR','FID']
 show_columns = ['Unlearned_Methods','Source', 'Diffusion_Models','Pre-ASR', 'Post-ASR','FID']
 TYPES = ['str', 'markdown', 'str', 'number', 'number', 'number']
-
+files = ['church','garbage','parachute','tench', 'vangogh', 'nidity', 'violence','illgel_activity']
 df_results_init = df_results.copy()[show_columns]
 
 def update_table(
@@ -341,187 +341,7 @@ with demo:
                     leaderboard_table,
                 )
 
-    #                 with gr.Row():
-    #                     shown_columns = gr.CheckboxGroup(
-    #                         choices=[
-    #                             c.name
-    #                             for c in fields(AutoEvalColumn)
-    #                             if not c.hidden and not c.never_hidden
-    #                         ],
-    #                         value=[
-    #                             c.name
-    #                             for c in fields(AutoEvalColumn)
-    #                             if c.displayed_by_default and not c.hidden and not c.never_hidden
-    #                         ],
-    #                         label="Select columns to show",
-    #                         elem_id="column-select",
-    #                         interactive=True,
-    #                     )
-    #                 with gr.Row():
-    #                     deleted_models_visibility = gr.Checkbox(
-    #                         value=False, label="Show gated/private/deleted models", interactive=True
-    #                     )
-    #             with gr.Column(min_width=320):
-    #                 #with gr.Box(elem_id="box-filter"):
-    #                 filter_columns_type = gr.CheckboxGroup(
-    #                     label="Unlearning types",
-    #                     choices=[t.to_str() for t in ModelType],
-    #                     value=[t.to_str() for t in ModelType],
-    #                     interactive=True,
-    #                     elem_id="filter-columns-type",
-    #                 )
-    #                 filter_columns_precision = gr.CheckboxGroup(
-    #                     label="Precision",
-    #                     choices=[i.value.name for i in Precision],
-    #                     value=[i.value.name for i in Precision],
-    #                     interactive=True,
-    #                     elem_id="filter-columns-precision",
-    #                 )
-    #                 filter_columns_size = gr.CheckboxGroup(
-    #                     label="Model sizes (in billions of parameters)",
-    #                     choices=list(NUMERIC_INTERVALS.keys()),
-    #                     value=list(NUMERIC_INTERVALS.keys()),
-    #                     interactive=True,
-    #                     elem_id="filter-columns-size",
-    #                 )
-
-    #         leaderboard_table = gr.components.Dataframe(
-    #             value=leaderboard_df[
-    #                 [c.name for c in fields(AutoEvalColumn) if c.never_hidden]
-    #                 + shown_columns.value
-    #             ],
-    #             headers=[c.name for c in fields(AutoEvalColumn) if c.never_hidden] + shown_columns.value,
-    #             datatype=TYPES,
-    #             elem_id="leaderboard-table",
-    #             interactive=False,
-    #             visible=True,
-    #         )
-
-    #         # Dummy leaderboard for handling the case when the user uses backspace key
-    #         hidden_leaderboard_table_for_search = gr.components.Dataframe(
-    #             value=original_df[COLS],
-    #             headers=COLS,
-    #             datatype=TYPES,
-    #             visible=False,
-    #         )
-    #         search_bar.submit(
-    #             update_table,
-    #             [
-    #                 hidden_leaderboard_table_for_search,
-    #                 shown_columns,
-    #                 filter_columns_type,
-    #                 filter_columns_precision,
-    #                 filter_columns_size,
-    #                 deleted_models_visibility,
-    #                 search_bar,
-    #             ],
-    #             leaderboard_table,
-    #         )
-    #         for selector in [shown_columns, filter_columns_type, filter_columns_precision, filter_columns_size, deleted_models_visibility]:
-    #             selector.change(
-    #                 update_table,
-    #                 [
-    #                     hidden_leaderboard_table_for_search,
-    #                     shown_columns,
-    #                     filter_columns_type,
-    #                     filter_columns_precision,
-    #                     filter_columns_size,
-    #                     deleted_models_visibility,
-    #                     search_bar,
-    #                 ],
-    #                 leaderboard_table,
-    #                 queue=True,
-    #             )
-
-    #     with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
-    #         gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
-
-    #     with gr.TabItem("🚀 Submit here! ", elem_id="llm-benchmark-tab-table", id=3):
-    #         with gr.Column():
-    #             with gr.Row():
-    #                 gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")
-
-    #             with gr.Column():
-    #                 with gr.Accordion(
-    #                     f"✅ Finished Evaluations ({len(finished_eval_queue_df)})",
-    #                     open=False,
-    #                 ):
-    #                     with gr.Row():
-    #                         finished_eval_table = gr.components.Dataframe(
-    #                             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)})",
-    #                     open=False,
-    #                 ):
-    #                     with gr.Row():
-    #                         running_eval_table = gr.components.Dataframe(
-    #                             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)})",
-    #                     open=False,
-    #                 ):
-    #                     with gr.Row():
-    #                         pending_eval_table = gr.components.Dataframe(
-    #                             value=pending_eval_queue_df,
-    #                             headers=EVAL_COLS,
-    #                             datatype=EVAL_TYPES,
-    #                             row_count=5,
-    #                         )
-    #         with gr.Row():
-    #             gr.Markdown("# ✉️✨ Submit your model here!", elem_classes="markdown-text")
-
-    #         with gr.Row():
-    #             with gr.Column():
-    #                 model_name_textbox = gr.Textbox(label="Model name")
-    #                 revision_name_textbox = gr.Textbox(label="Revision commit", placeholder="main")
-    #                 model_type = gr.Dropdown(
-    #                     choices=[t.to_str(" : ") for t in ModelType if t != ModelType.Unknown],
-    #                     label="Model type",
-    #                     multiselect=False,
-    #                     value=None,
-    #                     interactive=True,
-    #                 )
-
-    #             with gr.Column():
-    #                 precision = gr.Dropdown(
-    #                     choices=[i.value.name for i in Precision if i != Precision.Unknown],
-    #                     label="Precision",
-    #                     multiselect=False,
-    #                     value="float16",
-    #                     interactive=True,
-    #                 )
-    #                 weight_type = gr.Dropdown(
-    #                     choices=[i.value.name for i in WeightType],
-    #                     label="Weights type",
-    #                     multiselect=False,
-    #                     value="Original",
-    #                     interactive=True,
-    #                 )
-    #                 base_model_name_textbox = gr.Textbox(label="Base model (for delta or adapter weights)")
-
-    #         submit_button = gr.Button("Submit Eval")
-    #         submission_result = gr.Markdown()
-    #         submit_button.click(
-    #             add_new_eval,
-    #             [
-    #                 model_name_textbox,
-    #                 base_model_name_textbox,
-    #                 revision_name_textbox,
-    #                 precision,
-    #                 weight_type,
-    #                 model_type,
-    #             ],
-    #             submission_result,
-    #         )
+
 
     with gr.Row():
         with gr.Accordion("📙 Citation", open=True):