class_docstr: Deserialize a stream of bytes into a list of lists.
  
  Consider using :class:~`sagemaker.deserializers.NumpyDeserializer` or
  :class:~`sagemaker.deserializers.PandasDeserializer` instead, if you'd like to convert text/csv
  responses directly into other data types.
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docstr: Initialize a ``CSVDeserializer`` instance.
  
  Args:
      encoding (str): The string encoding to use (default: "utf-8").
      accept (union[str, tuple[str]]): The MIME type (or tuple of allowable MIME types) that
          is expected from the inference endpoint (default: "text/csv").
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code: def __init__(self, encoding="utf-8", accept="text/csv"):
      """Initialize a ``CSVDeserializer`` instance.
  
      Args:
          encoding (str): The string encoding to use (default: "utf-8").
          accept (union[str, tuple[str]]): The MIME type (or tuple of allowable MIME types) that
              is expected from the inference endpoint (default: "text/csv").
      """
      super(CSVDeserializer, self).__init__(accept=accept)
      self.encoding = encoding
  
imports: from __future__ import absolute_import
  import csv
  import abc
  import codecs
  import io
  import json
  import numpy
  from six import with_metaclass
  from sagemaker.utils import DeferredError
label_desc: Use image node_id 1 to create a new CSVDeserializer object from inherited base classes: SimpleBaseDeserializer with example: obj = CSVDeserializer(encoding, accept)