Instantiates a NASNet model in ImageNet mode.
View aliases
Main aliases
tf.keras.applications.NASNetLarge
See Migration guide for more details.
`tf.compat.v1.keras.applications.NASNetLarge`, `tf.compat.v1.keras.applications.nasnet.NASNetLarge`
tf.keras.applications.nasnet.NASNetLarge(
input_shape=None,
include_top=True,
weights='imagenet',
input_tensor=None,
pooling=None,
classes=1000,
classifier_activation='softmax'
)
Reference:
Optionally loads weights pre-trained on ImageNet.
Note that the data format convention used by the model is
the one specified in your Keras config at ~/.keras/keras.json
.
Args | |
---|---|
input_
|
Optional shape tuple, only to be specified
if include_ is False (otherwise the input shape
has to be (331, for NASNetLarge.
It should have exactly 3 inputs channels,
and width and height should be no smaller than 32.
E.g. (224, would be one valid value.
|
include_
|
Whether to include the fully-connected layer at the top of the network. |
weights
|
None (random initialization) or
imagenet (ImageNet weights). For loading imagenet weights,
input_ should be (331, 331, 3)
|
input_
|
Optional Keras tensor (i.e. output of
layers.Input() )
to use as image input for the model.
|
pooling
|
Optional pooling mode for feature extraction
when include_ is False .
|
classes
|
Optional number of classes to classify images
into, only to be specified if include_top is True, and
if no weights argument is specified.
|
classifier_activation
|
A str or callable. The activation function to
use on the "top" layer. Ignored unless include_top=True . Set
classifier_activation=None to return the logits of the "top"
layer. When loading pretrained weights, classifier_activation can
only be None or "softmax" .
|
Returns | |
---|---|
A Keras model instance. |