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tf.keras.applications.EfficientNetB6
Instantiates the EfficientNetB6 architecture.
tf.keras.applications.EfficientNetB6(
    include_top=True, weights='imagenet', input_tensor=None, input_shape=None,
    pooling=None, classes=1000, classifier_activation='softmax', **kwargs
)
  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. If you have never configured it, it defaults to "channels_last".
| Arguments | |
|---|---|
include_top | 
      Whether to include the fully-connected layer at the top of the network. Defaults to True. | 
weights | 
      One of None (random initialization), 'imagenet' (pre-training on ImageNet), or the path to the weights file to be loaded. Defaults to 'imagenet'. | 
     
input_tensor | 
      Optional Keras tensor (i.e. output of layers.Input()) to use as image input for the model. | 
     
input_shape | 
      Optional shape tuple, only to be specified if include_top is False. It should have exactly 3 inputs channels. | 
     
pooling | 
      Optional pooling mode for feature extraction when include_top is False. Defaults to None. 
       
  | 
     
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. Defaults to 1000 (number of ImageNet classes). | 
     
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. Defaults to 'softmax'. | 
     
| Returns | |
|---|---|
A keras.Model instance. | 
     
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
 https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/applications/EfficientNetB6