# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import streamlit as st
import json
import pandas as pd
import plotly.express as px
import numpy as np

carbon_df= pd.read_pickle('./data/carbon_df.pkl')
carbon_df.drop(carbon_df.loc[carbon_df['task']==''].index, inplace=True)

st.set_page_config(
    page_title="Comparing the Carbon Footprint of Transformers",
    page_icon="./hf-earth.png",
    layout="wide",
)

st.title("Hugging Face Carbon Compare Tool")

# Get the sidebar details
with st.sidebar.expander("Models", expanded=True):
    st.image('./hf-earth.png')
    models=[]
    # choose a dataset to analyze
    for m in carbon_df['name'].items():
        try:
            modelname= m[1].split('/')[1]
        except:
            modelname = m[1]
        models.append(modelname)
    model_name = st.selectbox(
        f"Choose model to explore:",
        models)

with st.expander("Model Comparison", expanded=False):

    st.markdown("### Here is how the model " + model_name + " compares to other models:")
    fig_model = px.bar(carbon_df.sort_values(by=['carbon']), x=models, y='carbon', hover_name= models, color_discrete_map = {model_name : 'red'})
    st.plotly_chart(fig_model, use_container_width=True)

with st.expander("Task Comparison", expanded=False):
    fig = px.box(carbon_df, x=carbon_df['task'], y=carbon_df['carbon'], color='task', hover_name=carbon_df['name'])
    #fig.update_traces(quartilemethod="exclusive") # or "inclusive", or "linear" by default
    st.plotly_chart(fig, use_container_width=True)