application_nasnet_large {keras3}

Instantiates a NASNet model in ImageNet mode.

Description

Instantiates a NASNet model in ImageNet mode.

Usage

application_nasnet_large(
  input_shape = NULL,
  include_top = TRUE,
  weights = "imagenet",
  input_tensor = NULL,
  pooling = NULL,
  classes = 1000L,
  classifier_activation = "softmax",
  name = "nasnet_large"
)

Arguments

input_shape

Optional shape tuple, only to be specified if include_top is FALSE (otherwise the input shape has to be ⁠(331, 331, 3)⁠ for NASNetLarge. 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 fully-connected layer at the top of the network.

weights

NULL (random initialization) or imagenet (ImageNet weights). For loading imagenet weights, input_shape should be (331, 331, 3)

input_tensor

Optional Keras tensor (i.e. output of keras_input()) to use as image input for the model.

pooling

Optional pooling mode for feature extraction when include_top is FALSE.

• NULL 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.

classifier_activation

A str or callable. The activation function to use on the "top" layer. Ignored unless include_top=TRUE. Set classifier_activation=NULL to return the logits of the "top" layer. When loading pretrained weights, classifier_activation can only be NULL or "softmax".

name

The name of the model (string).

Value

A Keras model instance.

Reference

• Learning Transferable Architectures for Scalable Image Recognition (CVPR 2018)

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.

Note

Each Keras Application expects a specific kind of input preprocessing. For NASNet, call application_preprocess_inputs() on your inputs before passing them to the model.

See Also

• https://keras.io/api/applications/nasnet#nasnetlarge-function