class_docstr: Read X,y from an SVMlight file, and produce [X_i, y_i] pairs. 
class_docstr_tok: ["Read","X",",","y","from","an","SVMlight","file",",","and","produce","[","X_i",",","y_i","]","pairs","."]
docstr: Args:
      filename (str): input file
      shuffle (bool): shuffle the data
docstr_tok: ["Args",":","filename","(","str",")",":","input","file","shuffle","(","bool",")",":","shuffle","the","data"]
code: def __init__(self, filename, shuffle=True):
      """
      Args:
          filename (str): input file
          shuffle (bool): shuffle the data
      """
      import sklearn.datasets  # noqa
  
      self.X, self.y = sklearn.datasets.load_svmlight_file(filename)
      self.X = np.asarray(self.X.todense())
      self.shuffle = shuffle
  
imports: import numpy
  import os
  import six
  from ..utils import logger
  from ..utils.argtools import log_once
  from ..utils.serialize import loads
  from ..utils.develop import create_dummy_class
  from ..utils.loadcaffe import get_caffe_pb
  from ..utils.timer import timed_operation
  from ..utils.utils import get_tqdm
  from .base import DataFlowReentrantGuard, RNGDataFlow
  from .common import MapData
label_desc: Use image node_id 1 to create a new SVMLightData object from inherited base classes: RNGDataFlow with example: obj = SVMLightData(filename, shuffle)