docstr: ivy.Container static method variant of ivy.slogdet. This method
  simply wraps the function, and so the docstring for ivy.slogdet also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  x
      input array or container having shape (..., M, M) and whose innermost two
      dimensions form square matrices. Should have a floating-point data type.
  key_chains
      The key-chains 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``.
  
  Returns
  -------
  ret
      This function returns a container containing NamedTuples.
      Each NamedTuple of output will have -
          sign:
          An array containing a number representing the sign of the determinant
          for each square matrix.
  
          logabsdet:
          An array containing natural log of the absolute determinant of each
          square matrix.
  
  Examples
  --------
  >>> x = ivy.Container(a=ivy.array([[1.0, 2.0],
  ...                                [3.0, 4.0]]),
  ...                   b=ivy.array([[1.0, 2.0],
  ...                                [2.0, 1.0]]))
  >>> y = ivy.Container.static_slogdet(x)
  >>> print(y)
  {
      a: [
          sign = ivy.array(-1.),
          logabsdet = ivy.array(0.6931472)
      ],
      b: [
          sign = ivy.array(-1.),
          logabsdet = ivy.array(1.0986123)
      ]
  }
code: def _static_slogdet(
      x: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      /,
      *,
      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,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.slogdet. This method
      simply wraps the function, and so the docstring for ivy.slogdet also
      applies to this method with minimal changes.
  
      Parameters
      ----------
      x
          input array or container having shape (..., M, M) and whose innermost two
          dimensions form square matrices. Should have a floating-point data type.
      key_chains
          The key-chains 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``.
  
      Returns
      -------
      ret
          This function returns a container containing NamedTuples.
          Each NamedTuple of output will have -
              sign:
              An array containing a number representing the sign of the determinant
              for each square matrix.
  
              logabsdet:
              An array containing natural log of the absolute determinant of each
              square matrix.
  
      Examples
      --------
      >>> x = ivy.Container(a=ivy.array([[1.0, 2.0],
      ...                                [3.0, 4.0]]),
      ...                   b=ivy.array([[1.0, 2.0],
      ...                                [2.0, 1.0]]))
      >>> y = ivy.Container.static_slogdet(x)
      >>> print(y)
      {
          a: [
              sign = ivy.array(-1.),
              logabsdet = ivy.array(0.6931472)
          ],
          b: [
              sign = ivy.array(-1.),
              logabsdet = ivy.array(1.0986123)
          ]
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "slogdet",
          x,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
      )
  
imports: from typing import Union, Optional, Tuple, Literal, List, Dict, Sequence
  from ivy.data_classes.container.base import ContainerBase
  import ivy
label_desc: Use image node_id 35 for calling the _ContainerWithLinearAlgebra obj's underlying member method code with example usage: obj._static_slogdet() and returns: ContainerBase