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Instantiates the ResNet152V2 architecture.
tf.keras.applications.ResNet152V2( include_top=True, weights='imagenet', input_tensor=None, input_shape=None, pooling=None, classes=1000, classifier_activation='softmax' )
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  

include_top  whether to include the fullyconnected layer at the top of the network. 
weights  one of None (random initialization), 'imagenet' (pretraining on ImageNet), or the path to the weights file to be loaded. 
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 (otherwise the input shape has to be (224, 224, 3) (with 'channels_last' data format) or (3, 224, 224) (with 'channels_first' data format). It should have exactly 3 inputs channels, and width and height should be no smaller than 32. E.g. (200, 200, 3) would be one valid value. 
pooling  Optional pooling mode for feature extraction when include_top is False .

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=None to return the logits of the "top" layer. 
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/ResNet152V2