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/

Pytorch library for end-to-end transformer models training and serving

768 Jan 01, 2023

Sketch-Based 3D Exploration with Stacked Generative Adversarial Networks

pix2vox [Demonstration video] Sketch-Based 3D Exploration with Stacked Generative Adversarial Networks. Generated samples Single-category generation M

232 Nov 14, 2022

This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.

1 Oct 25, 2021

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

249 Dec 22, 2022

Caffe-like explicit model constructor. C(onfig)Model

cmodel Caffe-like explicit model constructor. C(onfig)Model Installation pip install git+https://github.com/bonlime/cmodel Usage In order to allow usi

1 Feb 18, 2022

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

MIMIC Code Repository The MIMIC Code Repository is intended to be a central hub for sharing, refining, and reusing code used for analysis of the MIMIC

1.8k Dec 26, 2022

Training BERT with Compute/Time (Academic) Budget

Training BERT with Compute/Time (Academic) Budget This repository contains scripts for pre-training and finetuning BERT-like models with limited time

263 Jan 07, 2023

SwinIR: Image Restoration Using Swin Transformer

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

2.4k Jan 08, 2023

LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura

4 Oct 05, 2022

Codebase for "ProtoAttend: Attention-Based Prototypical Learning."

Codebase for "ProtoAttend: Attention-Based Prototypical Learning." Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister,

2 May 17, 2022

Official public repository of paper "Intention Adaptive Graph Neural Network for Category-Aware Session-Based Recommendation"

Intention Adaptive Graph Neural Network (IAGNN) This is the official repository of paper Intention Adaptive Graph Neural Network for Category-Aware Se

9 Nov 22, 2022

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

Pytorch library for end-to-end transformer models training and serving

Sketch-Based 3D Exploration with Stacked Generative Adversarial Networks

This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.

The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining

Caffe-like explicit model constructor. C(onfig)Model

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

Training BERT with Compute/Time (Academic) Budget

SwinIR: Image Restoration Using Swin Transformer

LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

Codebase for "ProtoAttend: Attention-Based Prototypical Learning."

Official public repository of paper "Intention Adaptive Graph Neural Network for Category-Aware Session-Based Recommendation"

Employee-Managment - Company employee registration software in the face recognition system

StackNet is a computational, scalable and analytical Meta modelling framework

GANsformer: Generative Adversarial Transformers Drew A

Measure WWjj polarization fraction

A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners

Pytorch implementation of face attention network

sssegmentation is a general framework for our research on strongly supervised semantic segmentation.

An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax

Freecodecamp Scientific Computing with Python Certification; Solution for Challenge 2: Time Calculator