Instantiates the EfficientNetB3 architecture.
tf.keras.applications.EfficientNetB3( include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000, classifier_activation='softmax', **kwargs )
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/r2.4/api_docs/python/tf/keras/applications/EfficientNetB3