class_docstr: Base class of converters.
  
  Converters receive batched data retrieved from iterators and perform
  arbitrary transforms as well as device transfer.
  
  Implementation should override the ``__call__`` method.
  
  .. seealso::
      :meth:`chainer.dataset.converter` --- a decorator to turn a converter
      function into a ``Converter`` instance.
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docstr: Performs conversion.
  
  Args:
      batch:
          A batch. The type and value are arbitrary, depending on usage.
      device(~chainer.backend.Device):
          Device to which the converter is expected to send the batch.
  
  Returns: A converted batch.
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code: def __call__(self, batch, device):
      """Performs conversion.
  
      Args:
          batch:
              A batch. The type and value are arbitrary, depending on usage.
          device(~chainer.backend.Device):
              Device to which the converter is expected to send the batch.
  
      Returns: A converted batch.
      """
      raise NotImplementedError(
          "Concrete class must implement __call__."
      )
  
imports: import collections
  import numpy
  import six
  import chainer
  from chainer import backend
  from chainer.backends import cuda
label_desc: Use image node_id 1 for calling the Converter obj's underlying member method code with example usage: obj.__call__(batch, device) without return types