Streamlit component for TensorBoard, TensorFlow's visualization toolkit

Last update: Nov 13, 2022

Overview

streamlit-tensorboard

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)

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

Ubuntu
Debian GNU/Linux
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

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

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

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

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
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:

If a TensorBoard server is running, connect to it instead of opening a new one.

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)

0.0.2(Jun 14, 2021)

Fixes issue #5
Source code(tar.gz)
Source code(zip)
0.0.1(Jun 13, 2021)

A lot of room for improvement! First release 0.0.1
Source code(tar.gz)
Source code(zip)

Owner

Snehan Kekre

Documentation Writer @streamlit. Formerly, @Coursera.

GitHub Repository https://pypi.org/project/streamlit-tensorboard/

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Streamlit component for TensorBoard, TensorFlow's visualization toolkit

Related tags

Overview

streamlit-tensorboard

Installation 🎈

Example Usage 💻

Contributing 🛠️

Supported Platforms

Comments

Fixing Windows support by changing logdir to POSIX format

Refuses to connect on Streamlit sharing

Works on MacOS

Support several comma-separated paths in logdir

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

Releases(0.0.2)

0.0.2(Jun 14, 2021)

0.0.1(Jun 13, 2021)

Owner

Snehan Kekre

A simple and lightweight genetic algorithm for optimization of any machine learning model

用强化学习DQN算法，训练AI模型来玩合成大西瓜游戏，提供Keras版本和PARL（paddle）版本

Training data extraction on GPT-2

This is the code for the paper "Motion-Focused Contrastive Learning of Video Representations" (ICCV'21).

Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies

Pneumonia Detection using machine learning - with PyTorch

PyTorch implementation of Off-policy Learning in Two-stage Recommender Systems

Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting

Distributing reference energies for SMIRNOFF implementations

Negative Interactions for Improved Collaborative Filtering:

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long, Evan Shelhamer, and Trevor Darrell. CVPR 2015 and PAMI 2016.

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RoFormer_pytorch

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Streamlit component for TensorBoard, TensorFlow's visualization toolkit

Related tags

Overview

streamlit-tensorboard

Installation 🎈

Example Usage 💻

Contributing 🛠️

Supported Platforms

Comments

Fixing Windows support by changing logdir to POSIX format

Refuses to connect on Streamlit sharing

Works on MacOS

Support several comma-separated paths in logdir

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

Releases(0.0.2)

0.0.2(Jun 14, 2021)

0.0.1(Jun 13, 2021)

Owner

Snehan Kekre

A simple and lightweight genetic algorithm for optimization of any machine learning model

用强化学习DQN算法，训练AI模型来玩合成大西瓜游戏，提供Keras版本和PARL（paddle）版本

Training data extraction on GPT-2

This is the code for the paper "Motion-Focused Contrastive Learning of Video Representations" (ICCV'21).

Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies

Pneumonia Detection using machine learning - with PyTorch

PyTorch implementation of Off-policy Learning in Two-stage Recommender Systems

Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting

Distributing reference energies for SMIRNOFF implementations

Negative Interactions for Improved Collaborative Filtering:

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

An OpenAI Gym environment for multi-agent car racing based on Gym's original car racing environment.

Pytorch code for our paper "Feedback Network for Image Super-Resolution" (CVPR2019)

Generative vs Discriminative: Rethinking The Meta-Continual Learning (NeurIPS 2021)

A set of tools for converting a darknet dataset to COCO format working with YOLOX

Synthetic Humans for Action Recognition, IJCV 2021

[SIGGRAPH 2022 Journal Track] AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars

RoFormer_pytorch

Asterisk is a framework to generate high-quality training datasets at scale

Official implementation for “Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior”

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long, Evan Shelhamer, and Trevor Darrell. CVPR 2015 and PAMI 2016.