tf.keras.applications.InceptionResNetV2

Instantiates the Inception-ResNet v2 architecture.

View aliases

Main aliases

tf.keras.applications.inception_resnet_v2.InceptionResNetV2

Compat aliases for migration

tf.compat.v1.keras.applications.InceptionResNetV2, tf.compat.v1.keras.applications.inception_resnet_v2.InceptionResNetV2

tf.keras.applications.InceptionResNetV2(
    include_top=True, weights='imagenet', input_tensor=None,
    input_shape=None, pooling=None, classes=1000,
    classifier_activation='softmax', **kwargs
)

Reference:

Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning (AAAI 2017)

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.

Returns
A `keras.Model` instance.

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.

© 2020 The TensorFlow Authors. All rights reserved.
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/InceptionResNetV2