Spaces:
Running
on
CPU Upgrade
Running
on
CPU Upgrade
Tie model and language selection to selected tab
Browse files
app.py
CHANGED
@@ -101,23 +101,23 @@ with demo:
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demo.load(
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core.update_task_groups_and_fewshot,
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[gr.State(value=0), fewshot],
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[shown_tasks, fewshot, selected_tab],
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)
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fewshot.change(
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core.update_task_groups_and_fewshot,
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[selected_tab, fewshot],
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[shown_tasks, fewshot, selected_tab],
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)
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acc.select(
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core.update_task_groups_and_fewshot,
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inputs=[gr.State(value=0), fewshot],
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outputs=[shown_tasks, fewshot, selected_tab],
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)
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misc.select(
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core.update_task_groups_and_fewshot,
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inputs=[gr.State(value=1), fewshot],
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outputs=[shown_tasks, fewshot, selected_tab],
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)
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for comp, fn in [
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(search_bar, "submit"),
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demo.load(
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core.update_task_groups_and_fewshot,
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[gr.State(value=0), model_types, langs_bar,fewshot],
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[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
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)
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fewshot.change(
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core.update_task_groups_and_fewshot,
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[selected_tab, model_types, langs_bar, fewshot],
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[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
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)
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acc.select(
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core.update_task_groups_and_fewshot,
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inputs=[gr.State(value=0), model_types, langs_bar, fewshot],
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outputs=[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
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)
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misc.select(
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core.update_task_groups_and_fewshot,
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inputs=[gr.State(value=1), model_types, langs_bar, fewshot],
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outputs=[shown_tasks, fewshot, selected_tab, model_types, langs_bar],
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)
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for comp, fn in [
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(search_bar, "submit"),
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core.py
CHANGED
@@ -4,10 +4,10 @@ import os
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import gradio as gr
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import numpy as np
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import pandas as pd
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import plotly.express as px
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from datasets import load_dataset
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import style
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ZERO_SHOT_ONLY = ["BELEBELE"]
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FEW_SHOT_ONLY = ["GSM8K", "TruthfulQA"]
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@@ -127,7 +127,7 @@ def update_df(
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return sort_cols(df, fewshot)
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-
def update_task_groups_and_fewshot(current_selected_tab: int, is_fewshot_current: bool = False):
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selected_task_type = get_selected_task_type(current_selected_tab)
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available_tasks = get_available_task_groups(selected_task_type, is_fewshot_current)
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new_selected_tasks = available_tasks.copy()
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@@ -149,7 +149,25 @@ def update_task_groups_and_fewshot(current_selected_tab: int, is_fewshot_current
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interactive=fewshot_available,
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)
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-
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def get_selected_task_type(task_type_id):
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import gradio as gr
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import numpy as np
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import pandas as pd
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from datasets import load_dataset
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import style
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from style import T_SYMBOLS, LANG_SYMBOLS
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ZERO_SHOT_ONLY = ["BELEBELE"]
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FEW_SHOT_ONLY = ["GSM8K", "TruthfulQA"]
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return sort_cols(df, fewshot)
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def update_task_groups_and_fewshot(current_selected_tab: int, model_types, langs_bar, is_fewshot_current: bool = False, ):
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selected_task_type = get_selected_task_type(current_selected_tab)
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available_tasks = get_available_task_groups(selected_task_type, is_fewshot_current)
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new_selected_tasks = available_tasks.copy()
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interactive=fewshot_available,
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)
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model_types = gr.CheckboxGroup(
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label="Select model type",
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choices=[
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(
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f"Pretrained {T_SYMBOLS['pretrained']}",
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T_SYMBOLS["pretrained"],
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),
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(f"Chat {T_SYMBOLS['chat']}", T_SYMBOLS["chat"]),
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],
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value=list(T_SYMBOLS.values()),
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interactive=True
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)
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langs_bar = gr.CheckboxGroup(
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choices=[(LANG_SYMBOLS.get(l, l), l) for l in languages_list],
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value=languages_list,
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interactive=True,
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)
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return [tasks_checkbox_group_update, fewshot_radio_update, current_selected_tab, model_types, langs_bar]
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def get_selected_task_type(task_type_id):
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