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tf.keras.applications.ResNet101V2
Instantiates the ResNet101V2 architecture.
tf.keras.applications.ResNet101V2(
    include_top=True, weights='imagenet', input_tensor=None, input_shape=None,
    pooling=None, classes=1000, classifier_activation='softmax'
)
  Reference:
- Identity Mappings in Deep Residual Networks (CVPR 2016)
 
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.
| Arguments | |
|---|---|
include_top | 
      whether to include the fully-connected layer at the top of the network. | 
weights | 
      one of None (random initialization), 'imagenet' (pre-training 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/ResNet101V2