[Update]Comment all

app.py

@@ -137,207 +137,207 @@ with demo:
     gr.HTML(TITLE)
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
 
-    with gr.Tabs(elem_classes="tab-buttons") as tabs:
-        with gr.TabItem("UnlearnDiffAtk Benchmark", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=0):
-            with gr.Row():
-                with gr.Column():
-                    with gr.Row():
-                        search_bar = gr.Textbox(
-                            placeholder=" 🔍 Search for your model (separate multiple queries with `;`) and press ENTER...",
-                            show_label=False,
-                            elem_id="search-bar",
-                        )
-                    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=False):
-            citation_button = gr.Textbox(
-                value=CITATION_BUTTON_TEXT,
-                label=CITATION_BUTTON_LABEL,
-                lines=10,
-                elem_id="citation-button",
-                show_copy_button=True,
-            )
+    # with gr.Tabs(elem_classes="tab-buttons") as tabs:
+    #     with gr.TabItem("UnlearnDiffAtk Benchmark", elem_id="UnlearnDiffAtk-benchmark-tab-table", id=0):
+    #         with gr.Row():
+    #             with gr.Column():
+    #                 with gr.Row():
+    #                     search_bar = gr.Textbox(
+    #                         placeholder=" 🔍 Search for your model (separate multiple queries with `;`) and press ENTER...",
+    #                         show_label=False,
+    #                         elem_id="search-bar",
+    #                     )
+    #                 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=False):
+    #         citation_button = gr.Textbox(
+    #             value=CITATION_BUTTON_TEXT,
+    #             label=CITATION_BUTTON_LABEL,
+    #             lines=10,
+    #             elem_id="citation-button",
+    #             show_copy_button=True,
+    #         )
 
 scheduler = BackgroundScheduler()
 scheduler.add_job(restart_space, "interval", seconds=1800)