code: def softplus(
      x: Tensor,
      /,
      *,
      beta: Optional[Union[int, float]] = None,
      threshold: Optional[Union[int, float]] = None,
      complex_mode="jax",
      out: Optional[Tensor] = None,
  ) -> Tensor:
      if beta is not None and beta != 1:
          x_beta = x * beta
          res = (tf.nn.softplus(x_beta)) / beta
      else:
          x_beta = x
          res = tf.nn.softplus(x)
      if threshold is not None:
          return tf.where(x_beta > threshold, x, res)
      return res
  
file_path: ivy/ivy/functional/backends/tensorflow/activations.py
imports: from typing import Optional, Union, Literal
  import tensorflow
  from tensorflow.python.types.core import Tensor
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  import ivy.functional.backends.tensorflow
label_desc: Use image node_id 6 for calling a global function with example usage: softplus() and returns: res, tf