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import streamlit as st | |
import pandas as pd | |
import numpy as np | |
from streamlit_echarts import st_echarts | |
from streamlit.components.v1 import html | |
import pandas as pd | |
from model_information import get_dataframe | |
info_df = get_dataframe() | |
def draw(folder_name, category_one, category_two, sort, num_sort, model_size_range): | |
folder = f"./results/{folder_name}/" | |
data_path = f'{folder}/{category_one}/{category_two}.csv' | |
chart_data = pd.read_csv(data_path).dropna(axis='columns').round(3) | |
st.markdown(""" | |
<style> | |
.stMultiSelect [data-baseweb=select] span { | |
max-width: 800px; | |
font-size: 0.9rem; | |
background-color: #3C6478 !important; /* Background color for selected items */ | |
color: white; /* Change text color */ | |
back | |
} | |
</style> | |
""", unsafe_allow_html=True) | |
# remap model names | |
display_model_names = {key.strip() :val.strip() for key, val in zip(info_df['Original Name'], info_df['Proper Display Name'])} | |
model2sizes = {key.strip() :val.strip() for key, val in zip(info_df['Original Name'], info_df['Model Size'])} | |
chart_data['model_show'] = chart_data['Model'].map(display_model_names) | |
chart_data['model_show'] = chart_data['model_show'].fillna(chart_data['Model'].apply(lambda x: x.replace('_', '-'))) | |
chart_data['model_size'] = chart_data['Model'].map(model2sizes) | |
chart_data['model_size'] = chart_data['model_size'].fillna('99999') | |
# How to work on the model size range, filter the ones that are not in the range | |
if model_size_range != 'All': | |
if model_size_range == '<10B': | |
chart_data = chart_data[chart_data['model_size'].astype(float) < 10] | |
elif model_size_range == '10B-30B': | |
chart_data = chart_data[(chart_data['model_size'].astype(float) >= 10) & (chart_data['model_size'].astype(float) < 30)] | |
elif model_size_range == '>30B': | |
chart_data = chart_data[chart_data['model_size'].astype(float) >= 30] | |
chart_data.drop(columns=['model_size'], inplace=True) | |
models = st.multiselect("Please choose the model", | |
sorted(chart_data['model_show'].tolist()), | |
default = sorted(chart_data['model_show'].tolist()), | |
) | |
# if 'Select All' in st.session_state.models: | |
# st.session_state.models = chart_data['model_show'].tolist() | |
chart_data = chart_data[chart_data['model_show'].isin(models)] | |
if len(chart_data) == 0: return | |
min_value = round(min(chart_data.iloc[:, 1]) - 0.1*min(chart_data.iloc[:, 1]), 1) | |
max_value = round(max(chart_data.iloc[:, 1]) + 0.1*max(chart_data.iloc[:, 1]), 1) | |
display_names = { | |
'cross_mmlu' : 'Cross-MMLU', | |
'cross_mmlu_no_prompt' : 'Cross-MMLU-No-Prompt', | |
'cross_logiqa' : 'Cross-LogiQA', | |
'cross_logiqa_no_prompt' : 'Cross-LogiQA-No-Prompt', | |
'cross_xquad' : 'Cross-XQUAD', | |
'cross_xquad_no_prompt' : 'Cross-XQUAD-No-Prompt', | |
'sg_eval' : 'SG EVAL', | |
'sg_eval_v1_cleaned' : 'SG EVAL V1 Cleaned', | |
'sg_eval_v2_mcq' : 'SG EVAL V2 MCQ', | |
'sg_eval_v2_mcq_no_prompt': 'SG EVAL V2 MCQ No Prompt', | |
'sg_eval_v2_open' : 'SG EVAL V2 Open Ended', | |
'us_eval' : 'US EVAL', | |
'cn_eval' : 'CN EVAL', | |
'ph_eval' : 'PH EVAL' | |
} | |
data_columns = [i for i in chart_data.columns if i not in ['Model', 'model_show']] | |
''' | |
Show Table | |
''' | |
with st.container(): | |
st.markdown('##### TABLE') | |
model_link = {key.strip(): val for key, val in zip(info_df['Proper Display Name'], info_df['Link'])} | |
chart_data['model_link'] = chart_data['model_show'].map(model_link) | |
chart_data_table = chart_data[['model_show', 'model_link'] + data_columns] | |
# Format numeric columns to 2 decimal places | |
chart_data_table[chart_data_table.columns[2]] = chart_data_table[chart_data_table.columns[2]].apply(lambda x: round(float(x), 3) if isinstance(x, (int, float)) else x) | |
chart_data_table = chart_data_table.sort_values( | |
by=chart_data_table.columns[2], | |
ascending=False | |
).reset_index(drop=True) | |
styled_df = chart_data_table.style.format( | |
{ | |
chart_data_table.columns[i]: "{:.3f}" for i in range(2, len(chart_data_table.columns)) | |
} | |
).highlight_max( | |
subset=[chart_data_table.columns[2]], color='yellow' | |
) | |
st.dataframe( | |
styled_df, | |
column_config={ | |
'model_show': 'Model', | |
chart_data_table.columns[1]: {'alignment': 'center'}, | |
"model_link": st.column_config.LinkColumn( | |
"Model Link", | |
), | |
}, | |
hide_index=True, | |
use_container_width=True | |
) | |
# = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = | |
# Initialize a session state variable for toggling the chart visibility | |
if "show_chart" not in st.session_state: | |
st.session_state.show_chart = False | |
# Create a button to toggle visibility | |
if st.button("Show Chart"): | |
st.session_state.show_chart = not st.session_state.show_chart | |
if st.session_state.show_chart: | |
with st.container(): | |
st.markdown('##### CHART') | |
if num_sort == 'Ascending': ascend = True | |
else: ascend = False | |
chart_data = chart_data.sort_values(by=[sort], ascending=ascend).dropna(axis=0) | |
options = { | |
# "title": {"text": f"{display_names[category_two]}"}, | |
"tooltip": { | |
"trigger": "axis", | |
"axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}}, | |
"triggerOn": 'mousemove', | |
}, | |
"legend": {"data": data_columns}, | |
"toolbox": {"feature": {"saveAsImage": {}}}, | |
"grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True}, | |
"xAxis": [ | |
{ | |
"type": "category", | |
"boundaryGap": True, | |
"triggerEvent": True, | |
"data": chart_data['model_show'].tolist(), | |
} | |
], | |
"yAxis": [{"type": "value", | |
"min": min_value, | |
"max": max_value, | |
"boundaryGap": True | |
# "splitNumber": 10 | |
}], | |
"series": [{ | |
"name": f"{col}", | |
"type": "bar", | |
"data": chart_data[f'{col}'].tolist(), | |
} for col in data_columns], | |
} | |
events = { | |
"click": "function(params) { return params.value }" | |
} | |
value = st_echarts(options=options, events=events, height="500px") |