A single training/test example for simple sequence classification.

A single training/test example for simple sequence classification.

A single set of features of data.

Fake example so the num input examples is a multiple of the batch size. When running eval/predict on the TPU, we need to pad the number of examples

A single training/test example for simple sequence classification.

A single set of features of data.

A single set of features of data.

Fake example so the num input examples is a multiple of the batch size. When running eval/predict on the TPU, we need to pad the number of examples

A single training instance (sentence pair).

A single training instance (sentence pair).

A basic Adam optimizer that includes "correct" L2 weight decay.

A basic Adam optimizer that includes "correct" L2 weight decay.

Configuration for `AlbertModel`. The default settings match the configuration of model `albert_xxlarge`.

Configuration for `AlbertModel`. The default settings match the configuration of model `albert_xxlarge`.

Runs basic tokenization (punctuation splitting, lower casing, etc.).

Runs basic tokenization (punctuation splitting, lower casing, etc.).

Configuration for `BertModel`.

LAMBOptimizer optimizer. https://github.com/ymcui/LAMB_Optimizer_TF # IMPORTANT NOTE - This is NOT an official implementation. -

A single training instance (sentence pair).

Runs WordPiece tokenziation.

Runs WordPiece tokenziation.

Processor for the internal data set. sentence pair classification

A basic Adam optimizer that includes "correct" L2 weight decay.

BERT model ("Bidirectional Encoder Representations from Transformers"). Example usage: ```python # Already been converted from strings into ids

BERT model ("Bidirectional Encoder Representations from Transformers"). Example usage: ```python # Already been converted from strings into ids

BERT model ("Bidirectional Encoder Representations from Transformers"). Example usage: ```python # Already been converted into WordPiece token

Processor for the CMNLI data set.

Processor for the internal data set. sentence pair classification

Processor for the CoLA data set (GLUE version).

Processor for the CSL data set.

Base class for data converters for sequence classification data sets.

Base class for data converters for sequence classification data sets.

Base class for data converters for sequence classification data sets.

Runs end-to-end tokenziation.

Runs end-to-end tokenziation.

LAMB (Layer-wise Adaptive Moments optimizer for Batch training).

Processor for the internal data set. sentence pair classification

Processor for the internal data set. sentence pair classification

Processor for the MultiNLI data set (GLUE version).

Processor for the MRPC data set (GLUE version).

Fake example so the num input examples is a multiple of the batch size. When running eval/predict on the TPU, we need to pad the number of examples

Processor for the internal data set. sentence pair classification

Processor for the MRPC data set (GLUE version).

Processor for the internal data set. sentence pair classification

Processor for the XNLI data set.

Processor for the XNLI data set.

Processor for the iFLYTEKData data set (GLUE version).