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import gradio as gr |
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import analysis_util |
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import generate_annotated_diffs |
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import dataset_statistics |
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df_manual = generate_annotated_diffs.manual_data_with_annotated_diffs() |
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df_manual["end_to_start"] = False |
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df_manual["start_to_end"] = False |
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n_diffs_manual = len(df_manual) |
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df_synthetic = generate_annotated_diffs.synthetic_data_with_annotated_diffs() |
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n_diffs_synthetic = len(df_synthetic) |
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def golden(): |
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return df_synthetic[(df_synthetic['end_to_start'] == False) & (df_synthetic['start_to_end'] == False)] |
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def e2s(): |
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return df_synthetic[(df_synthetic['end_to_start'] == True) & (df_synthetic['start_to_end'] == False)] |
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def s2e(): |
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return df_synthetic[(df_synthetic['end_to_start'] == False) & (df_synthetic['start_to_end'] == True)] |
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def e2s_s2e(): |
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return df_synthetic[(df_synthetic['end_to_start'] == True) & (df_synthetic['start_to_end'] == True)] |
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def synthetic(): |
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return df_synthetic[(df_synthetic['end_to_start'] == True) | (df_synthetic['start_to_end'] == True)] |
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STATISTICS = {"manual": dataset_statistics.get_statistics_for_df(golden()), |
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"e2s": dataset_statistics.get_statistics_for_df(e2s()), |
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"s2e": dataset_statistics.get_statistics_for_df(s2e()), |
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"e2s_s2e": dataset_statistics.get_statistics_for_df(e2s_s2e()), |
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"synthetic": dataset_statistics.get_statistics_for_df(synthetic()), |
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"all": dataset_statistics.get_statistics_for_df(df_synthetic)} |
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STATISTICS_T_TEST = dataset_statistics.t_test(STATISTICS, main_group='manual') |
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STAT_NAMES = list(STATISTICS['manual'].keys()) |
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def update_dataset_view(diff_idx, df): |
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diff_idx -= 1 |
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return (df.iloc[diff_idx]['annotated_diff'], |
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df.iloc[diff_idx]['commit_msg_start'], |
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df.iloc[diff_idx]['commit_msg_end'], |
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df.iloc[diff_idx]['session'], |
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str(df.iloc[diff_idx]['end_to_start']), |
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str(df.iloc[diff_idx]['start_to_end']), |
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f"https://github.com/{df.iloc[diff_idx]['repo']}/commit/{df.iloc[diff_idx]['hash']}",) |
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def update_dataset_view_manual(diff_idx): |
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return update_dataset_view(diff_idx, df_manual) |
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def update_dataset_view_synthetic(diff_idx): |
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return update_dataset_view(diff_idx, df_synthetic) |
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force_light_theme_js_func = """ |
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function refresh() { |
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const url = new URL(window.location); |
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if (url.searchParams.get('__theme') !== 'light') { |
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url.searchParams.set('__theme', 'light'); |
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window.location.href = url.href; |
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} |
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} |
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""" |
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if __name__ == '__main__': |
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with gr.Blocks(theme=gr.themes.Soft(), js=force_light_theme_js_func) as application: |
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def dataset_view_tab(n_items): |
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slider = gr.Slider(minimum=1, maximum=n_items, step=1, value=1, |
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label=f"Sample number (total: {n_items})") |
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diff_view = gr.Highlightedtext(combine_adjacent=True, color_map={'+': "green", '-': "red"}) |
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start_view = gr.Textbox(interactive=False, label="Start message", container=True) |
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end_view = gr.Textbox(interactive=False, label="End message", container=True) |
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session_view = gr.Textbox(interactive=False, label="Session", container=True) |
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is_end_to_start_view = gr.Textbox(interactive=False, |
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label="Is generated on the 'end-to-start' synthesis step?", |
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container=True) |
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is_start_to_end_view = gr.Textbox(interactive=False, |
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label="Is generated on the 'start-to-end' synthesis step?", |
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container=True) |
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link_view = gr.Markdown() |
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view = [ |
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diff_view, |
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start_view, |
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end_view, |
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session_view, |
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is_end_to_start_view, |
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is_start_to_end_view, |
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link_view |
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] |
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return slider, view |
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with gr.Tab("Manual"): |
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slider_manual, view_manual = dataset_view_tab(n_diffs_manual) |
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slider_manual.change(update_dataset_view_manual, inputs=slider_manual, |
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outputs=view_manual) |
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with gr.Tab("Synthetic"): |
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slider_synthetic, view_synthetic = dataset_view_tab(n_diffs_synthetic) |
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slider_synthetic.change(update_dataset_view_synthetic, inputs=slider_synthetic, |
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outputs=view_synthetic) |
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with gr.Tab("Analysis"): |
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def layout_for_statistics(statistics_group_name): |
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gr.Markdown(f"### {statistics_group_name}") |
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stats = STATISTICS[statistics_group_name] |
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gr.Number(label="Count", interactive=False, |
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value=len(stats['deletions_norm']), min_width=00) |
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gr.Number(label="Avg deletions number (rel to the initial msg length)", interactive=False, |
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value=stats['deletions_norm'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg insertions number (rel to the result length)", interactive=False, |
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value=stats['insertions_norm'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg changes number (rel to the initial msg length)", interactive=False, |
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value=stats['changes_norm'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg deletions number", interactive=False, |
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value=stats['deletions'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg insertions number", interactive=False, |
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value=stats['insertions'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg changes number", interactive=False, |
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value=stats['changes'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg edit distance", interactive=False, |
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value=stats['editdist'].mean().item(), precision=3, min_width=00) |
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gr.Number(label="Avg length difference", interactive=False, |
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value=stats['lendiff'].mean().item(), precision=3, min_width=00) |
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def layout_for_statistics_t_test(statistics_group_name): |
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gr.Markdown(f"### {statistics_group_name}") |
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stats = STATISTICS_T_TEST[statistics_group_name] |
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gr.Number(label="Deletions number (rel to the initial msg length)", interactive=False, |
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value=stats['deletions_norm'], precision=3, min_width=00) |
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gr.Number(label="Insertions number (rel to the result length)", interactive=False, |
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value=stats['insertions_norm'], precision=3, min_width=00) |
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gr.Number(label="Changes number (rel to the initial msg length)", interactive=False, |
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value=stats['changes_norm'], precision=3, min_width=00) |
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gr.Number(label="Deletions number", interactive=False, |
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value=stats['deletions'], precision=3, min_width=00) |
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gr.Number(label="Insertions number", interactive=False, |
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value=stats['insertions'], precision=3, min_width=00) |
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gr.Number(label="Changes number", interactive=False, |
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value=stats['changes'], precision=3, min_width=00) |
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with gr.Row(): |
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with gr.Column(scale=1, min_width=100): |
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layout_for_statistics("manual") |
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with gr.Column(scale=1, min_width=100): |
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layout_for_statistics("e2s") |
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with gr.Column(scale=1, min_width=100): |
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layout_for_statistics("s2e") |
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with gr.Column(scale=1, min_width=100): |
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layout_for_statistics("e2s_s2e") |
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with gr.Column(scale=1, min_width=100): |
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layout_for_statistics("synthetic") |
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with gr.Column(scale=1, min_width=100): |
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layout_for_statistics("all") |
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with gr.Row(): |
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with gr.Column(scale=1): |
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for stat_name in filter(lambda s: "_norm" not in s, STAT_NAMES): |
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chart = dataset_statistics.build_plotly_chart( |
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stat_golden=STATISTICS['manual'][stat_name], |
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stat_e2s=STATISTICS['e2s'][stat_name], |
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stat_s2e=STATISTICS['s2e'][stat_name], |
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stat_e2s_s2e=STATISTICS['e2s_s2e'][stat_name], |
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stat_name=stat_name |
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) |
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gr.Plot(value=chart) |
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with gr.Column(scale=1): |
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with gr.Column(scale=1): |
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for stat_name in filter(lambda s: "_norm" in s, STAT_NAMES): |
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chart = dataset_statistics.build_plotly_chart( |
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stat_golden=STATISTICS['manual'][stat_name], |
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stat_e2s=STATISTICS['e2s'][stat_name], |
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stat_s2e=STATISTICS['s2e'][stat_name], |
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stat_e2s_s2e=STATISTICS['e2s_s2e'][stat_name], |
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stat_name=stat_name |
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) |
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gr.Plot(value=chart) |
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gr.Markdown(f"### Reference-only correlations") |
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gr.Markdown(value=analysis_util.get_correlations_for_groups(df_synthetic, right_side="ind").to_markdown()) |
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gr.Markdown(f"### Aggregated correlations") |
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gr.Markdown(value=analysis_util.get_correlations_for_groups(df_synthetic, right_side="aggr").to_markdown()) |
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application.load(update_dataset_view_manual, inputs=slider_manual, |
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outputs=view_manual) |
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application.load(update_dataset_view_synthetic, inputs=slider_synthetic, |
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outputs=view_synthetic) |
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application.launch() |
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