fusionlab.encoders.alexnet.tfalexnet module#

class fusionlab.encoders.alexnet.tfalexnet.TFAlexNet(*args, **kwargs)[source]#

Bases: Model

call(inputs)[source]#

Calls the model on new inputs and returns the outputs as tensors.

In this case call() just reapplies all ops in the graph to the new inputs (e.g. build a new computational graph from the provided inputs).

Note: This method should not be called directly. It is only meant to be overridden when subclassing tf.keras.Model. To call a model on an input, always use the __call__() method, i.e. model(inputs), which relies on the underlying call() method.

Parameters:

  • inputs – Input tensor, or dict/list/tuple of input tensors.

  • training – Boolean or boolean scalar tensor, indicating whether to run the Network in training mode or inference mode.

  • mask – A mask or list of masks. A mask can be either a boolean tensor or None (no mask). For more details, check the guide [here](https://www.tensorflow.org/guide/keras/masking_and_padding).

Returns:

A tensor if there is a single output, or a list of tensors if there are more than one outputs.