class_docstr: A batch of data and associated metadata for a text matching task.
  
  Consists of one :class:`AttrTensor` (containing the data and metadata) for each
  attribute. For example, the :class:`AttrTensor` s of a :class:`MatchingBatch` object
  ``mbatch`` for a matching task with two attribtues ``name`` and ``category``, can be
  accessed as follows::
  
      name_attr = mbatch.name
      category_attr = mbatch.category
code: def __init__(self, input, train_info):
      copy_fields = train_info.all_text_fields
      for name in copy_fields:
          setattr(
              self,
              name,
              AttrTensor(
                  name=name,
                  attr=getattr(input, name),
                  train_info=train_info,
              ),
          )
      for name in [train_info.label_field, train_info.id_field]:
          if name is not None and hasattr(input, name):
              setattr(self, name, getattr(input, name))
  
file_path: deepmatcher/deepmatcher/batch.py
imports: from collections import namedtuple
  import torch
label_desc: Use image node_id 1 to create a new MatchingBatch object from inherited base classes: object with example: obj = MatchingBatch(input, train_info)