class_docstr: Represents an in-memory dataset with fixed schema.
  
  Use this to store and iterate through datasets with complex schema that
  fit in memory.
  
  Iterating through entries of this dataset is very fast since the dataset
  is stored as a set of native Caffe2 tensors, thus no type conversion or
  deserialization is necessary.
docstr: Return the list of field names for this dataset.
code: def field_names(self):
      """Return the list of field names for this dataset."""
      return self.fields
  
imports: from caffe2.python import core, workspace
  from caffe2.python.dataio import Reader, Writer
  from caffe2.python.schema import Struct, from_blob_list, from_column_list, InitEmptyRecord
  import numpy
label_desc: Use image node_id 7 for calling the Dataset obj's underlying member method code with example usage: obj.field_names() and returns: self