class_docstr: Internal representation of minibatch data.
  
  Args:
      batch: batch input for `var`.
       It can be:
  
        * a pure Python structure (list of lists, ...),
        * a list of NumPy arrays or SciPy sparse CSR matrices
        * a :class:`~cntk.core.Value` object (e.g. returned by :func:`one_hot`)
      seq_starts (list of `bool`\ s or None): if None, every sequence is
       treated as a new sequence. Otherwise, it is interpreted as a list of
       Booleans that tell whether a sequence is a new sequence (`True`) or a
       continuation of the sequence in the same slot of the previous
       minibatch (`False`)
      device (:class:`~cntk.device.DeviceDescriptor`): device this value
       should be put on
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docstr: The rectangular shape of this value. I.e., if this value has sequences
  of varying lengths, the shape will have the max sequence length in the
  sequence dimension.
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code: def shape(self):
      """
      The rectangular shape of this value. I.e., if this value has sequences
      of varying lengths, the shape will have the max sequence length in the
      sequence dimension.
      """
      return super(Value, self).shape().dimensions()
  
imports: import warnings
  import numbers
  import numpy
  from scipy import sparse
  from .None import cntk_py
  from .device import use_default_device, cpu, DeviceKind
  from cntk.internal import typemap
  from cntk.internal.sanitize import sanitize_batch, _sparse_to_dense_network_cache, data_type_to_dtype
label_desc: Use image node_id 6 for calling the Value obj's underlying member method code with example usage: obj.shape() and returns: super