class_docstr: Array/scalar parameter
  
  Parameters
  ----------
  init: np.ndarray, or None
      initial value of the array (defaults to 0, with a provided shape)
  shape: tuple of ints, or None
      shape of the array, to be provided iff init is not provided
  lower: array, float or None
      minimum value
  upper: array, float or None
      maximum value
  mutable_sigma: bool
      whether the mutation standard deviation must mutate as well (for mutation based algorithms)
  
  Note
  ----
  - More specific behaviors can be obtained throught the following methods:
    set_bounds, set_mutation, set_integer_casting
  - if both lower and upper bounds are provided, sigma will be adapted so that the range spans 6 sigma.
    Also, if init is not provided, it will be set to the middle value.
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code: def __add__(self: D, offset: tp.Any) -> D:
      return self._new_with_data_layer("Add", offset)
  
imports: import numpy
  import nevergrad.common.typing
  from nevergrad.common import errors
  from .None import _layering
  from .None import core
  from .container import Dict
  from .None import utils
label_desc: Use image node_id 21 for calling the Data obj's underlying member method code with example usage: obj.__add__(offset) and returns: self