Uses of Class
org.deeplearning4j.iterator.BertIterator.Builder

Packages that use BertIterator.Builder

Package	Description
org.deeplearning4j.iterator

Uses of BertIterator.Builder in org.deeplearning4j.iterator

Methods in org.deeplearning4j.iterator that return BertIterator.Builder

Modifier and Type	Method and Description
BertIterator.Builder	BertIterator.Builder.appendToken(String appendToken) Append the specified token to the sequences, when doing training on sentence pairs. Generally "[SEP]" is used No token in appended by default.
static BertIterator.Builder	BertIterator.builder()
BertIterator.Builder	BertIterator.Builder.featureArrays(BertIterator.FeatureArrays featureArrays) Specify what arrays should be returned.
BertIterator.Builder	BertIterator.Builder.lengthHandling(@NonNull BertIterator.LengthHandling lengthHandling, int maxLength) Specifies how the sequence length of the output data should be handled.
BertIterator.Builder	BertIterator.Builder.masker(BertSequenceMasker masker) Used only for unsupervised training (i.e., when task is set to BertIterator.Task.UNSUPERVISED for learning a masked language model.
BertIterator.Builder	BertIterator.Builder.maskToken(String maskToken) Used only for unsupervised training (i.e., when task is set to BertIterator.Task.UNSUPERVISED for learning a masked language model.
BertIterator.Builder	BertIterator.Builder.minibatchSize(int minibatchSize) Minibatch size to use (number of examples to train on for each iteration) See also: padMinibatches
BertIterator.Builder	BertIterator.Builder.padMinibatches(boolean padMinibatches) Default: false (disabled) If the dataset is not an exact multiple of the minibatch size, should we pad the smaller final minibatch? For example, if we have 100 examples total, and 32 minibatch size, the following number of examples will be returned for subsequent calls of next() in the one epoch: padMinibatches = false (default): 32, 32, 32, 4. padMinibatches = true: 32, 32, 32, 32 (note: the last minibatch will have 4 real examples, and 28 masked out padding examples). Both options should result in exactly the same model.
BertIterator.Builder	BertIterator.Builder.prependToken(String prependToken) Prepend the specified token to the sequences, when doing supervised training. i.e., any token sequences will have this added at the start. Some BERT/Transformer models may need this - for example sequences starting with a "[CLS]" token. No token is prepended by default.
BertIterator.Builder	BertIterator.Builder.preProcessor(org.nd4j.linalg.dataset.api.MultiDataSetPreProcessor preProcessor) Set the preprocessor to be used on the MultiDataSets before returning them.
BertIterator.Builder	BertIterator.Builder.sentencePairProvider(LabeledPairSentenceProvider sentencePairProvider) Specify the source of the data for classification on sentence pairs.
BertIterator.Builder	BertIterator.Builder.sentenceProvider(LabeledSentenceProvider sentenceProvider) Specify the source of the data for classification.
BertIterator.Builder	BertIterator.Builder.task(BertIterator.Task task) Specify the BertIterator.Task the iterator should be set up for.
BertIterator.Builder	BertIterator.Builder.tokenizer(TokenizerFactory tokenizerFactory) Specify the TokenizerFactory to use.
BertIterator.Builder	BertIterator.Builder.unsupervisedLabelFormat(BertIterator.UnsupervisedLabelFormat labelFormat) Used only for unsupervised training (i.e., when task is set to BertIterator.Task.UNSUPERVISED for learning a masked language model.
BertIterator.Builder	BertIterator.Builder.vocabMap(Map<String,Integer> vocabMap) Provide the vocabulary as a map.

Constructors in org.deeplearning4j.iterator with parameters of type BertIterator.Builder

Constructor and Description
BertIterator(BertIterator.Builder b)