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=True, rankdir='TB', expand_nested=False, dpi=96
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
Example:
input = tf.keras.Input(shape=(100,), dtype='int32', name='input')
x = tf.keras.layers.Embedding(
output_dim=512, input_dim=10000, input_length=100)(input)
x = tf.keras.layers.LSTM(32)(x)
x = tf.keras.layers.Dense(64, activation='relu')(x)
x = tf.keras.layers.Dense(64, activation='relu')(x)
x = tf.keras.layers.Dense(64, activation='relu')(x)
output = tf.keras.layers.Dense(1, activation='sigmoid', name='output')(x)
model = tf.keras.Model(inputs=[input], outputs=[output])
dot_img_file = '/tmp/model_1.png'
tf.keras.utils.plot_model(model, to_file=dot_img_file, show_shapes=True)
Arguments |
|---|
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 models into clusters.
|
dpi
|
Dots per inch.
|
Returns |
|---|
|
A Jupyter notebook Image object if Jupyter is installed.
This enables in-line display of the model plots in notebooks.
|
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TensorFlow 1 version
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