tf.keras.applications.NASNetMobile
Instantiates a Mobile NASNet model in ImageNet mode.
tf.keras.applications.NASNetMobile(
input_shape=None, include_top=True, weights='imagenet', input_tensor=None,
pooling=None, classes=1000
)
Optionally loads weights pretrained on ImageNet. Note that the data format convention used by the model is the one specified in your Keras config at ~/.keras/keras.json
.
Arguments 
input_shape  Optional shape tuple, only to be specified if include_top is False (otherwise the input shape has to be (224, 224, 3) for NASNetMobile It should have exactly 3 inputs channels, and width and height should be no smaller than 32. E.g. (224, 224, 3) would be one valid value. 
include_top  Whether to include the fullyconnected layer at the top of the network. 
weights  None (random initialization) or imagenet (ImageNet weights) 
input_tensor  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_top is False . 
None means that the output of the model will be the 4D tensor output of the last convolutional layer. 
avg means that global average pooling will be applied to the output of the last convolutional layer, and thus the output of the model will be a 2D tensor. 
max means that global max pooling will be applied.

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. 
Returns 
A Keras model instance. 
Raises 
ValueError  In case of invalid argument for weights , or invalid input shape. 
RuntimeError  If attempting to run this model with a backend that does not support separable convolutions. 