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import os
import wandb
import streamlit as st
import streamlit.components.v1 as components
from utils import train
project = "st"
entity = "capecape"
HEIGHT = 720
def get_project(api, name, entity=None):
return api.project(name, entity=entity).to_html(height=HEIGHT)
st.title("Let's log some metrics to wandb 👇")
# Sidebar
sb = st.sidebar
sb.title("Train your model")
# wandb_token = sb.text_input("paste your wandb Api key if you want: https://wandb.ai/authorize", type="password")
# wandb.login(key=wandb_token)
wandb.login(anonymous="allow")
api = wandb.Api()
# render wandb dashboard
components.html(get_project(api, project, entity), height=HEIGHT)
# run params
runs = sb.number_input('Number of runs:', min_value=1, max_value=10, value=1)
epochs = sb.number_input('Number of epochs:', min_value=1, max_value=1000, value=100)
pseudo_code = """
We will execute a simple training loop
```python
wandb.init(project="st", ...)
for i in range(epochs):
acc = 1 - 2 ** -i - random()
loss = 2 ** -i + random()
wandb.log({"acc": acc,
"loss": loss})
```
"""
sb.write(pseudo_code)
# train model
if sb.button("Run Example"):
my_bar = sb.progress(0)
print("Running training")
for i in range(runs):
train(project=project, entity=entity, epochs=epochs)
my_bar.progress((i+1)/runs) |