tf.keras.applications.InceptionResNetV2
Instantiates the Inception-ResNet v2 architecture.
tf.keras.applications.InceptionResNetV2(
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.
Note: each Keras Application expects a specific kind of input preprocessing. For InceptionResNetV2, call tf.keras.applications.inception_resnet_v2.preprocess_input on your inputs before passing them to the model.
| 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 (299, 299, 3) (with 'channels_last' data format) or (3, 299, 299) (with 'channels_first' data format). It should have exactly 3 inputs channels, and width and height should be no smaller than 75. E.g. (150, 150, 3) would be one valid value. |
pooling | Optional pooling mode for feature extraction when include_top is False. -
None means that the output of the model will be the 4D tensor output of the last convolutional block. -
'avg' means that global average pooling will be applied to the output of the last convolutional block, and thus the output of the model will be a 2D tensor. -
'max' means that global max pooling will be applied.
|
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. |
**kwargs | For backwards compatibility only. |
| Raises |
|---|
ValueError | in case of invalid argument for weights, or invalid input shape. |
ValueError | if classifier_activation is not softmax or None when using a pretrained top layer. |