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https://github.com/lucacappelletti94/plot_keras_history

A simple python package to print a keras NN training history.
https://github.com/lucacappelletti94/plot_keras_history

Last synced: 14 days ago
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A simple python package to print a keras NN training history.

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README 

        
Plot Keras History

=========================================================================================

|pip| |downloads|



A python package to print a `Keras model training history `_



How do I install this package?

----------------------------------------------

As usual, just download it using pip:



.. code:: shell



    pip install plot_keras_history



Usage

------------------------------------------------

Let's say you have a model generated by the function my_keras_model:



Plotting a training history

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the following example we will see how to plot and either show or save the training history:



|standard|



.. code:: python



    from plot_keras_history import show_history, plot_history

    import matplotlib.pyplot as plt



    model = my_keras_model()

    history = model.fit(...)

    show_history(history)

    plot_history(history, path="standard.png")

    plt.close()



Plotting into separate graphs

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

By default, the graphs are all in one big image, but for various reasons you might need them one by one:



.. code:: python



    from plot_keras_history import plot_history

    import matplotlib.pyplot as plt



    model = my_keras_model()

    history = model.fit(...)

    plot_history(history, path="singleton", single_graphs=True)

    plt.close()



Plotting multiple histories

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Let's suppose you are training your model on multiple holdouts and you would like to plot all of them,

plus an average. Fortunately, we got you covered!



|multiple_histories|



.. code:: python



    from plot_keras_history import plot_history

    import matplotlib.pyplot as plt



    histories = []

    for holdout in range(10):

        model = my_keras_model()

        histories.append(model.fit(...))

    

    plot_history(

        histories,

        show_standard_deviation=False,

        show_average=True

    )

    plt.close()



Reducing the history noise with Savgol Filters

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In some occasion it is necessary to be able to see the progress of the history to interpolate the results to remove a bit of noise. A parameter is offered to automatically apply a Savgol filter:



|interpolated|



.. code:: python



    from plot_keras_history import plot_history

    import matplotlib.pyplot as plt



    model = my_keras_model()

    history = model.fit(...)

    plot_history(history, path="interpolated.png", interpolate=True)

    plt.close()



Automatic aliases

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A number of metrics are automatically converted from the default ones to more talking ones, for example "lr" becomes "Learning Rate", or "acc" becomes "Accuracy".



Automatic normalization

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The library automatically normalizes the ranges of metrics that are known to be either in [-1, 1] or [0, 1] ranges in order

to avoid visual biases.



All the available options

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~



.. code:: python



    def plot_history(

        history, # Either the history object or a pandas DataFrame. When using a dataframe, the index name is used as abscissae label.

        style:str="-", # The style of the lines.

        interpolate: bool = False, # Wethever to interpolate or not the graphs datapoints.

        side: float = 5, # Dimension of the graphs side.

        graphs_per_row: int = 4, # Number of graphs for each row.

        customization_callback: Callable = None, # Callback for customizing the graphs.

        path: str = None, # Path where to store the resulting image or images (in the case of single_graphs)

        single_graphs: bool = False #  Wethever to save the graphs as single of multiples.

    )



Chaining histories

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It's common to stop and restart a model's training, and this would break the history object into two: for this reason the method `chain_histories `_ is available:



.. code:: python



    from plot_keras_history import chain_histories



    model = my_keras_model()

    history1 = model.fit(...)

    history2 = model.fit(...)

    history = chain_histories(history1, history2)



Extras

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Numerous additional metrics are available in `extra_keras_metrics `_



Cite this software

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If you need a bib file to cite this work, here you have it:



.. code:: bib



    @software{Cappelletti_Plot_Keras_History_2022,

        author = {Cappelletti, Luca},

        doi = {10.5072/zenodo.1054923},

        month = {4},

        title = {{Plot Keras History}},

        version = {1.1.36},

        year = {2022}

    }



.. |pip| image:: https://badge.fury.io/py/plot-keras-history.svg

    :target: https://badge.fury.io/py/plot-keras-history

    :alt: Pypi project



.. |downloads| image:: https://pepy.tech/badge/plot-keras-history

    :target: https://pepy.tech/badge/plot-keras-history

    :alt: Pypi total project downloads 



.. |standard| image:: https://github.com/LucaCappelletti94/plot_keras_history/blob/master/plots/normal.png?raw=true

.. |interpolated| image:: https://github.com/LucaCappelletti94/plot_keras_history/blob/master/plots/interpolated.png?raw=true

.. |multiple_histories| image:: https://github.com/LucaCappelletti94/plot_keras_history/blob/master/plots/multiple_histories.png?raw=true