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TensorBoard can be used directly within notebook experiences such as Colab and Jupyter. This can be helpful for sharing results, integrating TensorBoard into existing workflows, and using TensorBoard without installing anything locally.
Setup
Notebooks 2 0 2 Fraction Worksheets
Start by installing TF 2.0 and loading the TensorBoard notebook extension:
For Jupyter users: If you’ve installed Jupyter and TensorBoard intothe same virtualenv, then you should be good to go. If you’re using amore complicated setup, like a global Jupyter installation and kernelsfor different Conda/virtualenv environments, then you must ensure thatthe
tensorboard
binary is on your PATH
inside the Jupyter notebookcontext. One way to do this is to modify the kernel_spec
to prependthe environment’s bin
directory to PATH
, as described here.For Docker users: In case you are running a Docker image of Jupyter Notebook server using TensorFlow's nightly, it is necessary to expose not only the notebook's port, but the TensorBoard's port. Thus, run the container with the following command:
where the
-p 6006
is the default port of TensorBoard. This will allocate a port for you to run one TensorBoard instance. To have concurrent instances, it is necessary to allocate more ports. Also, pass --bind_all
to %tensorboard
to expose the port outside the container.Import TensorFlow, datetime, and os: Faststone capture portable.
TensorBoard in notebooks
Download the FashionMNIST dataset and scale it:
Mac game ibomber defense pacific 1 0. Create a very simple model:
Train the model using Keras and the TensorBoard callback:
Start TensorBoard within the notebook using magics:
You can now view dashboards such as scalars, graphs, histograms, and others. Some dashboards are not available yet in Colab (such as the profile plugin).
The
%tensorboard
magic has exactly the same format as the TensorBoard command line invocation, but with a %
-sign in front of it.You can also start TensorBoard before training to monitor it in progress:
The same TensorBoard backend is reused by issuing the same command. If a different logs directory was chosen, a new instance of TensorBoard would be opened. Ports are managed automatically.
Start training a new model and watch TensorBoard update automatically every 30 seconds or refresh it with the button on the top right:
You can use the
tensorboard.notebook
APIs for a bit more control:The Markdown parser included in the Jupyter Notebook is MathJax-aware. This means that you can freely mix in mathematical expressions using the MathJax subset of Tex and LaTeX. Some examples from the MathJax demos site are reproduced below, as well as the Markdown+TeX source.
The Lorenz Equations¶
Source¶
Display¶
(begin{align} dot{x} & = sigma(y-x) dot{y} & = rho x - y - xz dot{z} & = -beta z + xy end{align})
The Cauchy-Schwarz Inequality¶
Source¶
Display¶
(begin{equation*} left( sum_{k=1}^n a_k b_k right)^2 leq left( sum_{k=1}^n a_k^2 right) left( sum_{k=1}^n b_k^2 right) end{equation*})
A Cross Product Formula¶
Source¶
Display¶
(begin{equation*} mathbf{V}_1 times mathbf{V}_2 = begin{vmatrix} mathbf{i} & mathbf{j} & mathbf{k} frac{partial X}{partial u} & frac{partial Y}{partial u} & 0 frac{partial X}{partial v} & frac{partial Y}{partial v} & 0 end{vmatrix} end{equation*})
The probability of getting (k) heads when flipping (n) coins is¶
Source¶
Display¶
(begin{equation*} P(E) = {n choose k} p^k (1-p)^{ n-k} end{equation*})
An Identity of Ramanujan¶
Source¶
Display¶
(begin{equation*} frac{1}{Bigl(sqrt{phi sqrt{5}}-phiBigr) e^{frac25 pi}} = 1+frac{e^{-2pi}} {1+frac{e^{-4pi}} {1+frac{e^{-6pi}} {1+frac{e^{-8pi}} {1+ldots} } } } end{equation*})
A Rogers-Ramanujan Identity¶
Source¶
Display¶
[begin{equation*}1 + frac{q^2}{(1-q)}+frac{q^6}{(1-q)(1-q^2)}+cdots =prod_{j=0}^{infty}frac{1}{(1-q^{5j+2})(1-q^{5j+3})},quadquad text{for $|q|<1$}.end{equation*}]
Maxwell’s Equations¶
Source¶
Display¶
(begin{align} nabla times vec{mathbf{B}} -, frac1c, frac{partialvec{mathbf{E}}}{partial t} & = frac{4pi}{c}vec{mathbf{j}} nabla cdot vec{mathbf{E}} & = 4 pi rho nabla times vec{mathbf{E}}, +, frac1c, frac{partialvec{mathbf{B}}}{partial t} & = vec{mathbf{0}} nabla cdot vec{mathbf{B}} & = 0 end{align})
Equation Numbering and References¶
Equation numbering and referencing will be available in a future version of the Jupyter notebook. Reaper 5 70 – digital audio workstation 15 5.
Inline Typesetting (Mixing Markdown and TeX)¶
While display equations look good for a page of samples, the ability to mix math and formattedtext in a paragraph is also important.
Source¶
Display¶
This expression (sqrt{3x-1}+(1+x)^2) is an example of a TeX inline equation in a Markdown-formatted sentence.
Other Syntax¶
You will notice in other places on the web that
$$
are needed explicitly to begin and end MathJax typesetting. This is not required if you will be using TeX environments, but the Jupyter notebook will accept this syntax on legacy notebooks.Source¶
Display¶
[begin{split}begin{array}{c}y_1 y_2 mathtt{t}_i z_{3,4}end{array}end{split}]
[begin{array}{c}y_1 cry_2 mathtt{t}_i cry_{3}end{array}]
Simplified Fraction 0.2
[begin{split}begin{eqnarray}x' &=& &x sinphi &+& z cosphi z' &=& - &x cosphi &+& z sinphi end{eqnarray}end{split}]