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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
)
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.
Note: each Keras Application expects a specific kind of input preprocessing. For NASNet, call tf.keras.applications.nasnet.preprocess_input on your inputs before passing them to the model.
  
  | Arguments | |
|---|---|
| input_shape | Optional shape tuple, only to be specified if include_topis 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 fully-connected layer at the top of the network. | 
| weights | None(random initialization) orimagenet(ImageNet weights) For loadingimagenetweights,input_shapeshould be (224, 224, 3) | 
| 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_topisFalse.
 | 
| classes | Optional number of classes to classify images into, only to be specified if include_topis True, and if noweightsargument 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. | 
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
 https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/applications/NASNetMobile