parameters: (value)
return_statement: return result
docstring: Converts an arg to numpy, avoiding dangerous string and unicode dtypes.
  
      Numpy pads with zeros when using string and unicode dtypes if different
      components of a tensor have different lengths.  This is bad: ignoring the
      padding is wrong for text data, and removing the padding is wrong for binary
      data.  To avoid this bug, we redo the conversion using an object dtype.
  
      Args:
        value: Value to convert to a numpy array.
  
      Returns:
        A numpy array.
docstring_summary: Converts an arg to numpy, avoiding dangerous string and unicode dtypes.
docstring_tokens: Converts an arg to numpy avoiding dangerous string and unicode dtypes .
function: def _convert(value):
      """Converts an arg to numpy, avoiding dangerous string and unicode dtypes.
  
      Numpy pads with zeros when using string and unicode dtypes if different
      components of a tensor have different lengths.  This is bad: ignoring the
      padding is wrong for text data, and removing the padding is wrong for binary
      data.  To avoid this bug, we redo the conversion using an object dtype.
  
      Args:
        value: Value to convert to a numpy array.
  
      Returns:
        A numpy array.
      """
      result = np.asarray(value, order="C")
      if result.dtype.char in "SU" and result is not value:
        return np.asarray(value, order="C", dtype=object)
      return result
function_tokens: def _convert ( value ) : result = np . asarray ( value , order = "C" ) if result . dtype . char in "SU" and result is not value : return np . asarray ( value , order = "C" , dtype = object ) return result