Convert a Keras model to dot format.
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`tf.compat.v1.keras.utils.model_to_dot`
tf.keras.utils.model_to_dot(
model,
show_shapes=False,
show_dtype=False,
show_layer_names=True,
rankdir='TB',
expand_nested=False,
dpi=96,
subgraph=False,
layer_range=None,
show_layer_activations=False,
show_trainable=False
)
Args |
model
|
A Keras model instance.
|
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.
|
subgraph
|
whether to return a pydot.Cluster instance.
|
layer_range
|
input of list containing two str items, which is the
starting layer name and ending layer name (both inclusive) indicating
the range of layers for which the pydot.Dot will be generated. It
also accepts regex patterns instead of exact name. In such case, start
predicate will be the first element it matches to layer_range[0]
and the end predicate will be the last element it matches to
layer_range[1] . By default None which considers all layers of
model. Note that you must pass range such that the resultant subgraph
must be complete.
|
show_layer_activations
|
Display layer activations (only for layers that
have an activation property).
|
show_trainable
|
whether to display if a layer is trainable. Displays 'T'
when the layer is trainable and 'NT' when it is not trainable.
|
Returns |
A pydot.Dot instance representing the Keras model or
a pydot.Cluster instance representing nested model if
subgraph=True .
|
Raises |
ValueError
|
if model_to_dot is called before the model is built.
|
ImportError
|
if pydot is not available.
|