Streamlit component for TensorBoard, TensorFlow's visualization toolkit

Related tags

Deep Learning tensorflow tensorboard streamlit
Overview

streamlit-tensorboard

Streamlit App

This is a work-in-progress, providing a function to embed TensorBoard, TensorFlow's visualization toolkit, in Streamlit apps.

Installation 🎈

pip install --upgrade streamlit-tensorboard

Example Usage 💻 

import streamlit as st
from streamlit_tensorboard import st_tensorboard
import tensorflow as tf

import datetime
import random

mnist = tf.keras.datasets.mnist

(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

def create_model():
    return tf.keras.models.Sequential(
        [
            tf.keras.layers.Flatten(input_shape=(28, 28)),
            tf.keras.layers.Dense(512, activation="relu"),
            tf.keras.layers.Dropout(0.2),
            tf.keras.layers.Dense(10, activation="softmax"),
        ]
    )

model = create_model()
model.compile(
    optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]
)

logdir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=logdir, histogram_freq=1)

model.fit(
    x=x_train,
    y=y_train,
    epochs=5,
    validation_data=(x_test, y_test),
    callbacks=[tensorboard_callback],
)

# Start TensorBoard
st_tensorboard(logdir=logdir, port=6006, width=1080)

st_tensorboard

Contributing 🛠️

Please file a new GitHub issue (if one doesn't already exist) for bugs, feature requests, suggestions for improvements, etc. If you have solutions to any open issues, feel free to open a Pull Request!

Supported Platforms

  1. Ubuntu
  2. Debian GNU/Linux
  3. macOS ( ⚠️ unverified)

Windows is currently not supported. PRs for added Windows support are welcome as fix to this issue.

Comments
  • Fixing Windows support by changing logdir to POSIX format

    Fixing Windows support by changing logdir to POSIX format

    Using pathlib to change the logdir path to POSIX format. The change would make the shlex.split work properly, thus making it work on Windows, and it will still work on Linux.

    opened by ansonnn07 2
  • Refuses to connect on Streamlit sharing

    Refuses to connect on Streamlit sharing

    image

    The issue has to do with network permissions on the remote host. Port 6006 should be opened on the remote host and incoming/outgoing connections should be allowed at remote host:6006.

    opened by snehankekre 1
  • Works on MacOS

    Works on MacOS

    I read in the readme that Streamlit-tensorboard is unverified on macOS. Upon trying, I noticed a delay in the TensorBoard loading. Opening the port 6006 on another tab, helped solve this issue of the delay.

    opened by 259mit 0
  • Support several comma-separated paths in logdir

    Support several comma-separated paths in logdir

    Hi @snehankekre Many thanks for the contribution. Just wondering whether it would be possible to support passing to the logdir argument of st_tensorboard a list of comma-separated paths to render several specific experiments, e.g. in the original tensorboard call you can specify it as follows:

    tensorboard --logdir=name1:/path/to/logs/1,name2:/path/to/logs/2

    Regards

    enhancement help wanted good first issue 
    opened by davidjimenezphd 1
  • Reuse TensorBoard on port {port} (pid {pid}) if opened previously

    Reuse TensorBoard on port {port} (pid {pid}) if opened previously

    Each widget interaction with Streamlitt causes the script to rerun from top to bottom. This execution model leads to the creation of a new TensorBoard server for every interaction and new connection to the Streamlit app.

    Desired behavior:

    1. If a TensorBoard server is running, connect to it instead of opening a new one.
    2. Reuse cached connection for viewers of the app. Do not open a new TensorBoard for each viewer.
    bug help wanted 
    opened by snehankekre 3
Releases(0.0.2)
Owner
Snehan Kekre
Documentation Writer @streamlit. Formerly, @Coursera.
Snehan Kekre
GitHub https://pypi.org/project/streamlit-tensorboard/
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