tf.keras.utils.plot_model

Converts a Keras model to dot format and save to a file.

tf.keras.utils.plot_model(
    model,
    to_file='model.png',
    show_shapes=False,
    show_dtype=False,
    show_layer_names=False,
    rankdir='TB',
    expand_nested=False,
    dpi=200,
    show_layer_activations=False,
    show_trainable=False,
    **kwargs
)

Used in the notebooks

Used in the tutorials
Load text pix2pix: Image-to-image translation with a conditional GAN Load a pandas DataFrame Transfer learning with YAMNet for environmental sound classification Image segmentation

Example:

inputs = ...
outputs = ...
model = keras.Model(inputs=inputs, outputs=outputs)

dot_img_file = '/tmp/model_1.png'
keras.utils.plot_model(model, to_file=dot_img_file, show_shapes=True)

Args
`model`	A Keras model instance
`to_file`	File name of the plot image.
`show_shapes`	whether to display shape information.
`show_dtype`	whether to display layer dtypes.
`show_layer_names`	whether to display layer names.
`rankdir`	`rankdir` argument passed to PyDot, a string specifying the format of the plot: `"TB"` creates a vertical plot; `"LR"` creates a horizontal plot.
`expand_nested`	whether to expand nested Functional models into clusters.
`dpi`	Image resolution in dots per inch.
`show_layer_activations`	Display layer activations (only for layers that have an `activation` property).
`show_trainable`	whether to display if a layer is trainable.

Returns
A Jupyter notebook Image object if Jupyter is installed. This enables in-line display of the model plots in notebooks.

© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/utils/plot_model