docstr: Prelu takes input data (Array) and slope array as input,
  
  and produces one output data (array) where the function
  f(x) = slope * x for x < 0, f(x) = x for x >= 0., is applied
  to the data array elementwise. This operator supports unidirectional
  broadcasting (array slope should be unidirectional broadcastable to
  input tensor X);
  
  Parameters
  ----------
  self
      input array.
  slope
      Slope Array. The shape of slope can be smaller than first input X;
      if so, its shape must be unidirectional broadcastable to X.
  out
      Optional output array.
  
  Returns
  -------
  ret
      input array with prelu applied elementwise.
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code: def prelu(
      self,
      slope: Union[float, ivy.NativeArray, ivy.Array],
      /,
      *,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """Prelu takes input data (Array) and slope array as input,
  
      and produces one output data (array) where the function
      f(x) = slope * x for x < 0, f(x) = x for x >= 0., is applied
      to the data array elementwise. This operator supports unidirectional
      broadcasting (array slope should be unidirectional broadcastable to
      input tensor X);
  
      Parameters
      ----------
      self
          input array.
      slope
          Slope Array. The shape of slope can be smaller than first input X;
          if so, its shape must be unidirectional broadcastable to X.
      out
          Optional output array.
  
      Returns
      -------
      ret
          input array with prelu applied elementwise.
      """
      return ivy.prelu(self._data, slope, 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 3 for calling the _ArrayWithActivationsExperimental obj's underlying member method code with example usage: obj.prelu() and returns: ivy