:py:mod:`medcat.utils.relation_extraction.pad_seq`
==================================================

.. py:module:: medcat.utils.relation_extraction.pad_seq


Module Contents
---------------

Classes
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.. autoapisummary::

   medcat.utils.relation_extraction.pad_seq.Pad_Sequence




.. py:class:: Pad_Sequence(seq_pad_value, label_pad_value = -1)


   .. py:method:: __init__(seq_pad_value, label_pad_value = -1)

      Used in rel_cat.py in RelCAT to create DataLoaders for train/test datasets.
          collate_fn for dataloader to collate sequences of different input_ids, ent1/ent2, and label
          lengths into a fixed length batch.
          This is applied per batch and not on the whole DataLoader data,
          padded x sequence, y sequence, x lengths and y lengths of batch.

      :param seq_pad_value: pad value for input_ids.
      :type seq_pad_value: int
      :param label_pad_value: pad value for labels. Defaults to -1.
      :type label_pad_value: int


   .. py:method:: __call__(batch)

      Pads a batch of input_ids.

      :param batch: gets the batch of Tensors from
                    RelData.dataset (check __getitem__() method for data returned)
                    and pads the token sequence + labels as needed
                    See https://pytorch.org/docs/stable/_modules/torch/nn/utils/rnn.html#pad_sequence
                    for extra info.
      :type batch: List[torch.Tensor]

      :Returns: **Tuple[Tensor, Tensor, Tensor, LongTensor, LongTensor]** -- padded data
                padded input ids, ent1&ent2 start token pos, padded labels, padded input_id_lengths, padded labels length