Attend the Women in ML Symposium on December 7 Register now

tfm.nlp.models.XLNetPretrainer

Stay organized with collections Save and categorize content based on your preferences.

XLNet-based pretrainer.

This is an implementation of the network structure surrounding a Transformer-XL encoder as described in "XLNet: Generalized Autoregressive Pretraining for Language Understanding" (https://arxiv.org/abs/1906.08237).

network An XLNet/Transformer-XL based network. This network should output a sequence output and list of state tensors.
mlm_activation The activation (if any) to use in the Masked LM network. If None, then no activation will be used.
mlm_initializer The initializer (if any) to use in the masked LM. Defaults to a Glorot uniform initializer.

checkpoint_items

Methods

call

View 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).

Args
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.

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