docstr: ivy.Array instance method variant of ivy.scaled_tanh. This method
  simply wraps the function, and so the docstring for ivy.scaled_tanh
  also applies to this method with minimal changes.
  
  Parameters
  ----------
  self
      input array.
  alpha
      The scaling parameter for the output.
      Determines the amplitude of the tanh function.
      Default: 1.7159
  beta
      The scaling parameter for the input.
      Determines the slope of the tanh function.
      Default: 0.67
  out
      optional output array, for writing the result to. It must have a shape
      that the inputs broadcast to.
  
  Returns
  -------
  ret
      an array after applying the scaled_tanh activation.
  
  Examples
  --------
  >>> x = ivy.array([-3., 2., 3.])
  >>> x.scaled_tanh()
  ivy.array([-1.65537548,  1.49570239,  1.65537548])
  
  >>> x = ivy.array([2., 2., 2.])
  >>> x.scaled_tanh(alpha=9, beta=0.1)
  ivy.array([1.77637792, 1.77637792, 1.77637792])
  
  >>> x = ivy.array([2., 2., 2.])
  >>> x.scaled_tanh(alpha=0.1, beta=9)
  ivy.array([0.1, 0.1, 0.1])
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code: def scaled_tanh(
      self: ivy.Array,
      /,
      *,
      alpha: float = 1.7159,
      beta: float = 0.67,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance method variant of ivy.scaled_tanh. This method
      simply wraps the function, and so the docstring for ivy.scaled_tanh
      also applies to this method with minimal changes.
  
      Parameters
      ----------
      self
          input array.
      alpha
          The scaling parameter for the output.
          Determines the amplitude of the tanh function.
          Default: 1.7159
      beta
          The scaling parameter for the input.
          Determines the slope of the tanh function.
          Default: 0.67
      out
          optional output array, for writing the result to. It must have a shape
          that the inputs broadcast to.
  
      Returns
      -------
      ret
          an array after applying the scaled_tanh activation.
  
      Examples
      --------
      >>> x = ivy.array([-3., 2., 3.])
      >>> x.scaled_tanh()
      ivy.array([-1.65537548,  1.49570239,  1.65537548])
  
      >>> x = ivy.array([2., 2., 2.])
      >>> x.scaled_tanh(alpha=9, beta=0.1)
      ivy.array([1.77637792, 1.77637792, 1.77637792])
  
      >>> x = ivy.array([2., 2., 2.])
      >>> x.scaled_tanh(alpha=0.1, beta=9)
      ivy.array([0.1, 0.1, 0.1])
      """
      return ivy.scaled_tanh(
          self._data, alpha=alpha, beta=beta, out=out
      )
  
file_path: ivy/ivy/data_classes/array/experimental/activations.py
imports: import abc
  from typing import Optional, Union, Literal
  import ivy
label_desc: Use image node_id 14 for calling the _ArrayWithActivationsExperimental obj's underlying member method code with example usage: obj.scaled_tanh() and returns: ivy