Methodtokenize(sample: dict, tokenizer, max_src_length=400, max_tgt_length=1024, unified_input=True, amr="src",
hanlp/components/amr/amrbart/data_interface/dataset.py:27
Methodtrain_batch(self, words, feats, arcs, rels, mask, optimizer, arc_loss, rel_loss)
hanlp/components/parsers/biaffine_parser_tf.py:510
Methodtrain_loop(self, trn_data, dev_data, epochs, num_examples, train_steps_per_epoch, dev_steps, model, optimizer,
hanlp/components/taggers/transformers/transformer_tagger_tf.py:73
Methodtrain_loop(self, trn_data, dev_data, epochs, num_examples,
train_steps_per_epoch, dev_steps, model, o
hanlp/components/parsers/biaffine_parser_tf.py:94
Methodtransform_batch(self, batch: Dict[str, Any], results: Dict[str, Any] = None, cls_is_bos=False,
sep_is
hanlp/components/lemmatizer.py:52
Methodtransform_batch(self, batch: Dict[str, Any], results: Dict[str, Any] = None, cls_is_bos=False,
sep_is
hanlp/components/mtl/tasks/amr.py:163
Functionuncombine_initial_dimsGiven a tensor of embeddings with shape (d1 * ... * dn, sequence_length, embedding_dim) and the original shape (d1, ..., dn, sequence_leng
hanlp/components/parsers/ud/udify_util.py:318