class_docstr: Equivalent to HashingVectorizer but with chunked prediction
  
  Args:
      chunksize (int): size of transform chunks
class_docstr_tok: ["Equivalent","to","HashingVectorizer","but","with","chunked","prediction","Args",":","chunksize","(","int",")",":","size","of","transform","chunks"]
code: def __init__(self, chunksize=100000, **kwargs):
      self.chunksize = chunksize
      HashingVectorizer.__init__(self, **kwargs)
  
imports: import warnings
  import pandas
  import numpy
  from scipy import sparse
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.preprocessing import MultiLabelBinarizer, FunctionTransformer, LabelEncoder, normalize
  from sklearn.feature_extraction.text import HashingVectorizer
  from sklearn import feature_selection
label_desc: Use image node_id 1 to create a new HashingVectorizerChunked object from inherited base classes: HashingVectorizer with example: obj = HashingVectorizerChunked(chunksize)