docstr: ivy.Container static method variant of ivy.inner. This method simply
  wraps the function, and so the docstring for ivy.inner also applies to
  this method with minimal changes.
  
  Return the inner product of two vectors ``x1`` and ``x2``.
  
  Parameters
  ----------
  x1
      first one-dimensional input array of size N.
      Should have a numeric data type.
      a(N,) array_like
      First input vector. Input is flattened if not already 1-dimensional.
  x2
      second one-dimensional input array of size M.
      Should have a numeric data type.
      b(M,) array_like
      Second input vector. Input is flattened if not already 1-dimensional.
  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``.
  out
      optional output array, for writing the result to.
      It must have a shape that the inputs broadcast to.
  
  Returns
  -------
  ret
      a two-dimensional array containing the inner product and whose
      shape is (N, M).
      The returned array must have a data type determined by Type Promotion Rules.
  
  Examples
  --------
  >>> x1 = ivy.Container(a=ivy.array([[1, 2], [3, 4]]))
  >>> x2 = ivy.Container(a=ivy.array([5, 6]))
  >>> y = ivy.Container.static_inner(x1, x2)
  >>> print(y)
  {
      a: ivy.array([17, 39])
  }
code: def _static_inner(
      x1: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      x2: 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,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.inner. This method simply
      wraps the function, and so the docstring for ivy.inner also applies to
      this method with minimal changes.
  
      Return the inner product of two vectors ``x1`` and ``x2``.
  
      Parameters
      ----------
      x1
          first one-dimensional input array of size N.
          Should have a numeric data type.
          a(N,) array_like
          First input vector. Input is flattened if not already 1-dimensional.
      x2
          second one-dimensional input array of size M.
          Should have a numeric data type.
          b(M,) array_like
          Second input vector. Input is flattened if not already 1-dimensional.
      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``.
      out
          optional output array, for writing the result to.
          It must have a shape that the inputs broadcast to.
  
      Returns
      -------
      ret
          a two-dimensional array containing the inner product and whose
          shape is (N, M).
          The returned array must have a data type determined by Type Promotion Rules.
  
      Examples
      --------
      >>> x1 = ivy.Container(a=ivy.array([[1, 2], [3, 4]]))
      >>> x2 = ivy.Container(a=ivy.array([5, 6]))
      >>> y = ivy.Container.static_inner(x1, x2)
      >>> print(y)
      {
          a: ivy.array([17, 39])
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "inner",
          x1,
          x2,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          out=out,
      )
  
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 17 for calling the _ContainerWithLinearAlgebra obj's underlying member method code with example usage: obj._static_inner() and returns: ContainerBase