Carbon-Compare / app.py
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Refactor Streamlit app: improve data loading, error handling, and plot labeling
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# 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 pandas as pd
import plotly.express as px
import numpy as np
import os
# --- Utility Functions ---
def load_carbon_data(path):
"""Load carbon data from pickle file, handle errors gracefully."""
if not os.path.exists(path):
st.error(f"Data file not found: {path}")
return None
try:
df = pd.read_pickle(path)
return df
except Exception as e:
st.error(f"Failed to load data: {e}")
return None
# --- Load Data ---
carbon_df = load_carbon_data('./data/carbon_df.pkl')
if carbon_df is not None:
# Drop rows with missing task
carbon_df = carbon_df[carbon_df['task'].astype(str).str.strip() != '']
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")
# --- Sidebar: Model Selection ---
with st.sidebar.expander("Models", expanded=True):
st.image('./hf-earth.png')
models = []
model_full_names = []
for m in carbon_df['name'].items():
try:
modelname = m[1].split('/')[1]
except Exception:
modelname = m[1]
models.append(modelname)
model_full_names.append(m[1])
model_name = st.selectbox(
"Choose model to explore:",
models,
help="Select a model to compare its carbon footprint."
)
# --- Model Comparison ---
with st.expander("Model Comparison", expanded=False):
st.markdown(f"### How does **{model_name}** compare to other models?")
# Highlight the selected model in red, others in blue
color_map = {m: ('red' if m == model_name else '#1f77b4') for m in models}
sorted_df = carbon_df.copy()
sorted_df['short_name'] = models
sorted_df = sorted_df.sort_values(by=['carbon'])
fig_model = px.bar(
sorted_df,
x='short_name',
y='carbon',
hover_name='name',
color='short_name',
color_discrete_map=color_map,
labels={'short_name': 'Model', 'carbon': 'Carbon Footprint (kg CO₂e)'},
)
fig_model.update_layout(showlegend=False)
st.plotly_chart(fig_model, use_container_width=True)
# --- Task Comparison ---
with st.expander("Task Comparison", expanded=False):
fig = px.box(
carbon_df,
x='task',
y='carbon',
color='task',
hover_name='name',
labels={'task': 'Task', 'carbon': 'Carbon Footprint (kg CO₂e)'},
)
fig.update_layout(showlegend=False)
st.plotly_chart(fig, use_container_width=True)
else:
st.stop()