code: def logit(
      x: Union[tf.Tensor, tf.Variable],
      /,
      *,
      eps: Optional[float] = None,
      complex_mode: Literal["split", "magnitude", "jax"] = "jax",
      out: Optional[Tensor] = None,
  ) -> Tensor:
      x_dtype = x.dtype
      if eps is None:
          x = tf.where(tf.math.logical_or(x > 1, x < 0), ivy.nan, x)
      else:
          x = tf.clip_by_value(x, eps, 1 - eps)
      return tf.cast(tf.math.log(x / (1 - x)), x_dtype)
  
file_path: ivy/ivy/functional/backends/tensorflow/experimental/activations.py
imports: from typing import Optional, Union, Literal
  import tensorflow
  from tensorflow.python.types.core import Tensor
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
label_desc: Use image node_id 1 for calling a global function with example usage: logit() and returns: tf