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import streamlit as st
from huggingface_hub import list_models
from datetime import date, timedelta, datetime, timezone
import pandas as pd
import asyncio
# os.environ["KAGGLE_USERNAME"] = "hahunavth"
# os.environ["KAGGLE_KEY"] = ""
from kaggle.api.kaggle_api_extended import KaggleApi
st.set_page_config(layout="wide")
st.header("Experiments")
@st.cache_resource
def init_kaggle():
api = KaggleApi()
api.authenticate()
return api
api = init_kaggle()
# @st.cache_resource
# def get_model_list():
# return [model for model in list(list_models(author="hahunavth", filter="emofs2"))]
def get_ckpt_list(model):
files = model.siblings
file_names = [file.rfilename for file in files if "pytorch_model" in file.rfilename]
return file_names
with st.expander("Filter:"):
with st.form("my_form"):
_author = st.text_input("Author", "hahunavth")
_filter = st.text_input("Slug", "emofs2")
submit = st.form_submit_button("Submit")
models = list(
list_models(author=_author, filter=_filter, sort="last_modified", direction=-1)
)
_models = []
now = datetime.now(timezone.utc)
for model in models:
ckpts = get_ckpt_list(model)
ckpts_step = [ckpt.replace("pytorch_model.", "").replace(".bin", "") for ckpt in ckpts]
ckpts_step = [int(ckpt) for ckpt in ckpts_step if ckpt.isdigit()]
ckpts_step.sort()
last_ckpt = "{:,}".format(ckpts_step[-1]) if ckpts_step else None
diff = None
if model.last_modified:
now = now.replace(microsecond=0)
last_modified = model.last_modified.replace(microsecond=0)
diff = now - last_modified
diff = str(diff)
step = model.id.replace('hahunavth/emofs2-exp', '').split('_')[0]
_models.append(
{
"id": model.id,
"last_modified": diff,
"ckpt_list": last_ckpt,
"status": None,
"huggingface": f'https://huggingface.co/{model.id}/tree/main' if model.id else None,
"notebook": f"https://www.kaggle.com/code/hahunavth/ess-vlsp2023-train-{step}" if model.id else None,
"config": f"/kaggle/repo/vlsp2023-ess/config/exp{step}",
# "command": "st.balloons",
# "is_widget": True
}
)
df = pd.DataFrame(_models)
@st.cache_data
def get_kernel_status(step):
kaggle_slug = f"ess-vlsp2023-train-{step}"
try:
kernel_status = api.kernel_status(user_name="hahunavth", kernel_slug=kaggle_slug)["status"]
except:
kernel_status = "not found"
return kernel_status
async def set_df_kernel_status(df, n=12):
for i in range(min(len(df), n)):
step = df.iloc[i]["id"].replace('hahunavth/emofs2-exp', '').split('_')[0]
status = get_kernel_status(step)
df.at[i, "status"] = status
print(i, status)
def on_update_kernel_status_click():
st.session_state["last_update"] = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
get_kernel_status.clear()
st.button("Update kernel status", on_click=on_update_kernel_status_click)
st.text(f"Last updated: {st.session_state.get('last_update', 'not yet')}")
asyncio.run(set_df_kernel_status(df))
edit_df = st.data_editor(
df,
column_config={
"huggingface": st.column_config.LinkColumn(),
"notebook": st.column_config.LinkColumn(),
# "a": st.button("Click me"),
},
)
# st.dataframe(
# edit_df,
# column_config={
# "huggingface": st.column_config.LinkColumn(),
# "notebook": st.column_config.LinkColumn(),
# },
# use_container_width=True
# )
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