docstr: ivy.Array instance method variant of ivy.logit. This method simply
  wraps the function, and so the docstring for ivy.logit also applies to
  this method with minimal changes.
  
  Parameters
  ----------
  self
      Input array.
  eps
      When eps is None the function outputs NaN where x < 0 or x > 1.
      and inf or -inf where x = 1 or x = 0, respectively.
      Otherwise if eps is defined, x is clamped to [eps, 1 - eps]
  complex_mode
      optional specifier for how to handle complex data types. See
      ``ivy.func_wrapper.handle_complex_input`` for more detail.
  out
      Optional output array.
  
  Returns
  -------
  ret
      Array containing elementwise logits of x.
  
  Examples
  --------
  >>> x = ivy.array([1, 0, 0.9])
  >>> z = x.logit()
  >>> print(z)
  ivy.array([       inf,       -inf, 2.19722438])
  
  >>> x = ivy.array([1, 2, -0.9])
  >>> z = x.logit(eps=0.2)
  >>> print(z)
  ivy.array([ 1.38629448,  1.38629448, -1.38629436])
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code: def logit(
      self,
      /,
      *,
      eps: Optional[float] = None,
      complex_mode: Literal["split", "magnitude", "jax"] = "jax",
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance method variant of ivy.logit. This method simply
      wraps the function, and so the docstring for ivy.logit also applies to
      this method with minimal changes.
  
      Parameters
      ----------
      self
          Input array.
      eps
          When eps is None the function outputs NaN where x < 0 or x > 1.
          and inf or -inf where x = 1 or x = 0, respectively.
          Otherwise if eps is defined, x is clamped to [eps, 1 - eps]
      complex_mode
          optional specifier for how to handle complex data types. See
          ``ivy.func_wrapper.handle_complex_input`` for more detail.
      out
          Optional output array.
  
      Returns
      -------
      ret
          Array containing elementwise logits of x.
  
      Examples
      --------
      >>> x = ivy.array([1, 0, 0.9])
      >>> z = x.logit()
      >>> print(z)
      ivy.array([       inf,       -inf, 2.19722438])
  
      >>> x = ivy.array([1, 2, -0.9])
      >>> z = x.logit(eps=0.2)
      >>> print(z)
      ivy.array([ 1.38629448,  1.38629448, -1.38629436])
      """
      return ivy.logit(
          self, eps=eps, complex_mode=complex_mode, 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 1 for calling the _ArrayWithActivationsExperimental obj's underlying member method code with example usage: obj.logit() and returns: ivy