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import pandas as pd
import streamlit as st
import wandb
from dashboard_utils.bubbles import get_global_metrics, get_new_bubble_data, get_leaderboard
from dashboard_utils.main_metrics import get_main_metrics
from streamlit_observable import observable
import time
import requests
import streamlit as st
from streamlit_lottie import st_lottie
def load_lottieurl(url: str):
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
# Only need to set these here as we are add controls outside of Hydralit, to customise a run Hydralit!
st.set_page_config(page_title="Dashboard", layout="wide")
st.markdown("<h1 style='text-align: center;'>Dashboard</h1>", unsafe_allow_html=True)
key_figures_margin_left, key_figures_c1, key_figures_c2, key_figures_c3, key_figures_margin_right = st.columns(
(2, 1, 1, 1, 2)
)
chart_c1, chart_c2 = st.columns((3, 2))
lottie_url_loading = "https://assets5.lottiefiles.com/packages/lf20_OdNgAj.json"
lottie_loading = load_lottieurl(lottie_url_loading)
with key_figures_c1:
st.caption("\# of contributing users")
placeholder_key_figures_c1 = st.empty()
with placeholder_key_figures_c1:
st_lottie(lottie_loading, height=100, key="loading_key_figure_c1")
with key_figures_c2:
st.caption("\# active users")
placeholder_key_figures_c2 = st.empty()
with placeholder_key_figures_c2:
st_lottie(lottie_loading, height=100, key="loading_key_figure_c2")
with key_figures_c3:
st.caption("Total runtime")
placeholder_key_figures_c3 = st.empty()
with placeholder_key_figures_c3:
st_lottie(lottie_loading, height=100, key="loading_key_figure_c3")
with chart_c1:
st.subheader("Metrics over time")
st.caption("Training Loss")
placeholder_chart_c1_1 = st.empty()
with placeholder_chart_c1_1:
st_lottie(lottie_loading, height=100, key="loading_c1_1")
st.caption("Number of alive runs over time")
placeholder_chart_c1_2 = st.empty()
with placeholder_chart_c1_2:
st_lottie(lottie_loading, height=100, key="loading_c1_2")
st.caption("Number of steps")
placeholder_chart_c1_3 = st.empty()
with placeholder_chart_c1_3:
st_lottie(lottie_loading, height=100, key="loading_c1_3")
with chart_c2:
st.subheader("Global metrics")
st.caption("Collaborative training participants")
placeholder_chart_c2_1 = st.empty()
with placeholder_chart_c2_1:
st_lottie(lottie_loading, height=100, key="loading_c2_1")
st.write("Chart showing participants of the collaborative-training. Circle radius is relative to the total time contributed, "
"the profile picture is circled in purple if the participant is active. Every purple square represents an "
"active device.")
st.caption("Leaderboard")
placeholder_chart_c2_3 = st.empty()
with placeholder_chart_c2_3:
st_lottie(lottie_loading, height=100, key="loading_c2_2")
wandb.login(anonymous="must")
steps, dates, losses, alive_peers = get_main_metrics()
source = pd.DataFrame({"steps": steps, "loss": losses, "alive sessions": alive_peers, "date": dates})
placeholder_chart_c1_1.vega_lite_chart(
source,
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"description": "Training Loss",
"mark": {"type": "line", "point": {"tooltip": True, "filled": False, "strokeOpacity": 0}},
"encoding": {"x": {"field": "date", "type": "temporal"}, "y": {"field": "loss", "type": "quantitative"}},
"config": {"axisX": {"labelAngle": -40}},
},
use_container_width=True,
)
placeholder_chart_c1_2.vega_lite_chart(
source,
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"description": "Alive sessions",
"mark": {"type": "line", "point": {"tooltip": True, "filled": False, "strokeOpacity": 0}},
"encoding": {
"x": {"field": "date", "type": "temporal"},
"y": {"field": "alive sessions", "type": "quantitative"},
},
"config": {"axisX": {"labelAngle": -40}},
},
use_container_width=True,
)
placeholder_chart_c1_3.vega_lite_chart(
source,
{
"$schema": "https://vega.github.io/schema/vega-lite/v5.json",
"description": "Training Loss",
"mark": {"type": "line", "point": {"tooltip": True, "filled": False, "strokeOpacity": 0}},
"encoding": {"x": {"field": "date", "type": "temporal"}, "y": {"field": "steps", "type": "quantitative"}},
"config": {"axisX": {"labelAngle": -40}},
},
use_container_width=True,
)
serialized_data, profiles = get_new_bubble_data()
df_leaderboard = get_leaderboard(serialized_data)
observable(
"_",
notebook="d/9ae236a507f54046", # "@huggingface/participants-bubbles-chart",
targets=["c_noaws"],
redefine={"serializedData": serialized_data, "profileSimple": profiles, "width": 0},
render_empty=True,
)
placeholder_chart_c2_3.dataframe(df_leaderboard[["User", "Total time contributed"]])
global_metrics = get_global_metrics(serialized_data)
placeholder_key_figures_c1.write(f"<b>{global_metrics['num_contributing_users']}</b>", unsafe_allow_html=True)
placeholder_key_figures_c2.write(f"<b>{global_metrics['num_active_users']}</b>", unsafe_allow_html=True)
placeholder_key_figures_c3.write(f"<b>{global_metrics['total_runtime']}</b>", unsafe_allow_html=True)
with placeholder_chart_c2_1:
observable(
"Participants",
notebook="d/9ae236a507f54046", # "@huggingface/participants-bubbles-chart",
targets=["c_noaws"],
redefine={"serializedData": serialized_data, "profileSimple": profiles},
)
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