from bokeh.events import Tap from bokeh.io import curdoc from bokeh.layouts import column from bokeh.models import Div, TextInput, RadioButtonGroup, TextAreaInput, Span, Button, Panel, Tabs from bokeh.models.tools import CrosshairTool from demo_utils import ( get_data, prompt_boolq, pvp_colors, ctl_colors, clf_colors, reduct, task_best_pattern, plot_polygons_bokeh, advantage_text, data_difference, calculate_overlap, circ_easing, average_advantage_text, plot_three_polygons_bokeh, tasks, metric_tap, neutral_tasks, pattern_graph, ) from text import text1, text2, text3, text4, initial_passage, initial_question, text5 ######################################################################################################################## # Basic dimensions ######################################################################################################################## plot_width = 1200 plot_height = 400 sidebar_width = 400 in_text_plot_height = 300 text_width = 800 widget_size = 400 ######################################################################################################################## # Patternification widget ######################################################################################################################## passage = TextAreaInput(title="篇章", rows=3, value=initial_passage, max_width=text_width) passage.align = "center" question = TextInput(title="问题", value=initial_question, max_width=text_width) question.align = "center" radio_button_group = RadioButtonGroup(labels=["模板 1", "模板 2", "模板 3"], active=0, max_width=text_width) radio_button_group.align = "center" box_style = { "display": "block", "margin": "0 auto", "width": f"{text_width}px", "text-align": "center", "white-space": "pre-wrap", "background": "#f4f4f4", "border": "1px solid #ddd", # "border-left": "3px solid #4d4945", "color": "#666", "page-break-inside": "avoid", # "font-family": "monospace", "font-size": "15px", "line-height": "1.6", "max-width": "100%", "overflow": "hidden", "min-height": "30px", "word-wrap": "break-word", } prompt_box = Div( text=prompt_boolq(passage.value, question.value, radio_button_group.active), width=text_width, style=box_style, sizing_mode="scale_width", ) prompt_box.align = "center" def update_prompt(attrname, old, new): prompt_box.text = prompt_boolq(passage.value, question.value, radio_button_group.active) passage.on_change("value", update_prompt) question.on_change("value", update_prompt) radio_button_group.on_change("active", update_prompt) patternification = column(passage, question, radio_button_group, prompt_box, sizing_mode="scale_width") patternification.align = "center" ######################################################################################################################## # Advantage diagram ######################################################################################################################## advantage_plots_per_task = [] overlapping_range_per_task = [] training_points_per_task = [] clf_results_per_task = [] pvp_results_per_task = [] advantage_tabs = [] advantage_all_figures = Tabs(tabs=advantage_tabs) advantage_box = Div( text="在比较区域内点击某点以计算该点对应的性能点上的数据优势", width=text_width, style=box_style, sizing_mode="scale_width", ) advantage_box.align = "center" for task in tasks: training_points, classifier_performances, pattern_performances = get_data(task) training_points_per_task.append(list(training_points)) clf_results_per_task.append(reduct(classifier_performances, "accmax")) pvp_results_per_task.append(reduct(pattern_performances, "accmax", task_best_pattern[task], "normal")) advantage_plots_per_task.append(plot_polygons_bokeh( task, training_points_per_task[-1], clf_results_per_task[-1], pvp_results_per_task[-1], clf_colors, pvp_colors )) advantage_plots_per_task[-1].align = "center" advantage_plots_per_task[-1].add_tools(CrosshairTool(dimensions="width", line_alpha=0.2)) overlapping_range_per_task.append(calculate_overlap(clf_results_per_task[-1], pvp_results_per_task[-1])) advantage_tabs.append(Panel(child=advantage_plots_per_task[-1], title=task)) advantage_plots_per_task[-1].on_event( Tap, lambda event: metric_tap( event, overlapping_range_per_task[advantage_all_figures.active], training_points_per_task[advantage_all_figures.active], clf_results_per_task[advantage_all_figures.active], pvp_results_per_task[advantage_all_figures.active], advantage_box, advantage_plots_per_task[advantage_all_figures.active], ), ) if task == "MNLI": training_points_per_task.append(list(training_points)) clf_results_per_task.append(reduct(classifier_performances, "accmax")) pvp_results_per_task.append(reduct(pattern_performances, "accmax", task_best_pattern[task], "normal")) advantage_plots_per_task.append(plot_polygons_bokeh( task, training_points_per_task[-1], clf_results_per_task[-1], pvp_results_per_task[-1], clf_colors, pvp_colors, x_log_scale=True )) advantage_plots_per_task[-1].align = "center" advantage_plots_per_task[-1].add_tools(CrosshairTool(dimensions="width", line_alpha=0.2)) overlapping_range_per_task.append(calculate_overlap(clf_results_per_task[-1], pvp_results_per_task[-1])) advantage_tabs.append(Panel(child=advantage_plots_per_task[-1], title="MNLI (log scale)")) advantage_plots_per_task[-1].on_event( Tap, lambda event: metric_tap( event, overlapping_range_per_task[advantage_all_figures.active], training_points_per_task[advantage_all_figures.active], clf_results_per_task[advantage_all_figures.active], pvp_results_per_task[advantage_all_figures.active], advantage_box, advantage_plots_per_task[advantage_all_figures.active], ), ) advantage_all_figures = Tabs(tabs=advantage_tabs) advantage_all_figures.align = "center" def on_integrate_click(): frames = 200 initial_placement = overlapping_range_per_task[advantage_all_figures.active][0] if not isinstance(advantage_plots_per_task[advantage_all_figures.active].renderers[-1], Span): metric_line = Span( location=initial_placement, line_alpha=0.7, dimension="width", line_color=clf_colors[0] if initial_placement < 0 else pvp_colors[0], line_dash="dashed", line_width=1, ) advantage_plots_per_task[advantage_all_figures.active].renderers.extend([metric_line]) else: advantage_plots_per_task[advantage_all_figures.active].renderers[-1].location = initial_placement advantage_plots_per_task[advantage_all_figures.active].renderers[-1].line_color = clf_colors[ 0] if initial_placement < 0 else pvp_colors[0] average_advantage = 0 for i in range(1, frames): metric_value = overlapping_range_per_task[advantage_all_figures.active][0] + ( overlapping_range_per_task[advantage_all_figures.active][1] - overlapping_range_per_task[advantage_all_figures.active][0]) * (i / frames) advantage_value = data_difference(metric_value, overlapping_range_per_task[advantage_all_figures.active], training_points_per_task[advantage_all_figures.active], clf_results_per_task[advantage_all_figures.active], pvp_results_per_task[advantage_all_figures.active]) average_advantage = ((i - 1) * average_advantage + advantage_value) / i advantage_plots_per_task[advantage_all_figures.active].renderers[-1].location = metric_value advantage_plots_per_task[advantage_all_figures.active].renderers[-1].line_color = clf_colors[ 0] if advantage_value < 0 else pvp_colors[0] advantage_box.text = average_advantage_text(average_advantage) integrate = Button(width=175, max_width=175, label="对整个区域进行积分！") integrate.align = "center" integrate.on_click(on_integrate_click) def on_tab_change(attr, old, new): advantage_box.text = "在比较区域内点击某点以计算该点对应的性能点上的数据优势" advantage_all_figures.on_change('active', on_tab_change) advantage_column = column(advantage_all_figures, advantage_box, integrate, sizing_mode="scale_width") ######################################################################################################################## # Null verbalizer diagram ######################################################################################################################## null_tabs = [] null_all_figures = Tabs(tabs=null_tabs) for task in neutral_tasks: training_points, classifier_performances, pattern_performances = get_data(task) training_points = list(training_points) clf_results = reduct(classifier_performances, "accmax") pvp_results = reduct(pattern_performances, "accmax", task_best_pattern[task], "normal") ctl_results = reduct(pattern_performances, "accmax", task_best_pattern[task], "neutral") null_plot = plot_three_polygons_bokeh(task, training_points, clf_results, pvp_results, ctl_results, clf_colors, pvp_colors, ctl_colors) null_plot.align = "center" null_plot.add_tools(CrosshairTool(dimensions="width", line_alpha=0.2)) null_tabs.append(Panel(child=null_plot, title=task)) if task == "MNLI": null_plot = plot_three_polygons_bokeh(task, training_points, clf_results, pvp_results, ctl_results, clf_colors, pvp_colors, ctl_colors, x_log_scale=True) null_plot.align = "center" null_plot.add_tools(CrosshairTool(dimensions="width", line_alpha=0.2)) null_tabs.append(Panel(child=null_plot, title="MNLI (log scale)")) null_all_figures = Tabs(tabs=null_tabs) null_all_figures.align = "center" ######################################################################################################################## # Patterns diagram ######################################################################################################################## pattern_tabs = [] pattern_all_figures = Tabs(tabs=pattern_tabs) for task in tasks: pattern_plot = pattern_graph(task) pattern_plot.align = "center" pattern_plot.add_tools(CrosshairTool(dimensions="width", line_alpha=0.2)) pattern_tabs.append(Panel(child=pattern_plot, title=task)) pattern_all_figures = Tabs(tabs=pattern_tabs) pattern_all_figures.align = "center" ######################################################################################################################## # Add write-up text ######################################################################################################################## main_text_style = { "min-height": "100px", "overflow": "hidden", "display": "block", "margin": "auto", "width": f"{text_width}px", "font-size": "18px", } textbox1 = Div(text=text1, style=main_text_style) textbox2 = Div(text=text2, style=main_text_style) textbox3 = Div(text=text3, style=main_text_style) textbox4 = Div(text=text4, style=main_text_style) textbox5 = Div(text=text5, style=main_text_style) textbox1.align = "center" textbox2.align = "center" textbox3.align = "center" textbox4.align = "center" textbox5.align = "center" ######################################################################################################################## # Set up layouts and add to document ######################################################################################################################## main_body = column(textbox1, patternification, textbox2, advantage_column, textbox3, null_all_figures, textbox4, pattern_all_figures, textbox5, sizing_mode="scale_width") main_body.align = "center" curdoc().add_root(main_body) curdoc().title = "一条提示抵得上多少样本数据？"