docstr: Map the values of the input tensor to either 0 or 1, element-wise,
  based on the outcome of a comparison against a threshold value.
  
  Parameters
  ----------
  threshold
      Values greater than this are
      mapped to 1, others to 0.
  key_chains
      The keychains to apply or not apply the method to. Default is ``None``.
  to_apply
      If True, the method will be applied to key_chains, otherwise key_chains
      will be skipped. Default is ``True``.
  prune_unapplied
      Whether to prune key_chains for which the function was not applied.
      Default is ``False``.
  map_sequences
      Whether to also map method to sequences (lists, tuples).
      Default is ``False``.
  out
      optional output container, for writing the result to. It must have a shape
      that the inputs broadcast to.
  
  Returns
  -------
  ret
      Binarized output data
code: def binarizer(
      self: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      *,
      threshold: Union[float, ivy.Container] = 0,
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """Map the values of the input tensor to either 0 or 1, element-wise,
      based on the outcome of a comparison against a threshold value.
  
      Parameters
      ----------
      threshold
          Values greater than this are
          mapped to 1, others to 0.
      key_chains
          The keychains to apply or not apply the method to. Default is ``None``.
      to_apply
          If True, the method will be applied to key_chains, otherwise key_chains
          will be skipped. Default is ``True``.
      prune_unapplied
          Whether to prune key_chains for which the function was not applied.
          Default is ``False``.
      map_sequences
          Whether to also map method to sequences (lists, tuples).
          Default is ``False``.
      out
          optional output container, for writing the result to. It must have a shape
          that the inputs broadcast to.
  
      Returns
      -------
      ret
          Binarized output data
      """
      return self.static_binarizer(
          self,
          threshold=threshold,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Dict, Tuple, Sequence
  from numbers import Number
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 40 for calling the _ContainerWithElementWiseExperimental obj's underlying member method code with example usage: obj.binarizer() and returns: self