class_docstr: Abstract dataset class. All datasets should have this interface.
  
  Subclasses need to override `__getitem__`, which returns the i-th
  element, and `__len__`, which returns the total number elements.
  
  .. note:: An mxnet or numpy array can be directly used as a dataset.
docstr: Returns a new dataset with at most `count` number of samples in it.
  
  Parameters
  ----------
  count : int or None
      A integer representing the number of elements of this dataset that
      should be taken to form the new dataset. If count is None, or if count
      is greater than the size of this dataset, the new dataset will contain
      all elements of this dataset.
  
  Returns
  -------
  Dataset
      The result dataset.
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code: def take(self, count):
      """Returns a new dataset with at most `count` number of samples in it.
  
      Parameters
      ----------
      count : int or None
          A integer representing the number of elements of this dataset that
          should be taken to form the new dataset. If count is None, or if count
          is greater than the size of this dataset, the new dataset will contain
          all elements of this dataset.
  
      Returns
      -------
      Dataset
          The result dataset.
      """
      if count is None or count > len(self):
          count = len(self)
      from . import SequentialSampler
  
      return _SampledDataset(self, SequentialSampler(count))
  
imports: import os
  from ...None import recordio, ndarray
  from ...util import default_array
label_desc: Use image node_id 5 for calling the Dataset obj's underlying member method code with example usage: obj.take(count) and returns: _SampledDataset