docstr: ivy.Container static method variant of ivy.randint. This method
  simply wraps the function, and so the docstring for ivy.randint also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  low
      Lowest integer that can be drawn from the distribution.
  high
      One above the highest integer that can be drawn from the distribution.
  shape
      If the given shape is, e.g ``(m, n, k)``, then ``m * n * k`` samples
      are drawn. Can only be specified when ``low`` and ``high`` are numeric
      values, else exception will be raised.
      Default is ``None``, where a single value is returned.
  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``.
  device
      device on which to create the array 'cuda:0', 'cuda:1', 'cpu' etc.
      (Default value = None).
  dtype
       output array data type. If ``dtype`` is ``None``, the output array data
       type will be the default integer data type. Default ``None``
  seed
      A python integer. Used to create a random seed distribution
  out
      optional output array, for writing the result to. It must have a shape
      that the inputs broadcast to.
  
  Returns
  -------
  ret
      Returns an array with the given shape filled with integers from
      the uniform distribution in the “half-open” interval [low, high)
  
  Examples
  --------
  With :class:`ivy.Container` inputs:
  
  >>> x = ivy.Container(a=ivy.array([[9,7],[6,2]]),
  ...                   b=ivy.array([[0,2],[10,6]]))
  >>> y = ivy.Container(a=ivy.array([[10,32],[18,19]]),
  ...                   b=ivy.array([[44,5],[23,54]]))
  >>> ivy.Container.static_randint(x, y, device='cpu', dtype='int32')
  {
      a: ivy.array([[9, 27],
                    [16, 17]]),
      b: ivy.array([[13, 3],
                    [16, 19]])
  }
  
  With a mix of :class:`ivy.Array` and :class:`ivy.Container` inputs:
  
  >>> x = ivy.array([-1,-9,3])
  >>> y = ivy.Container(a=ivy.array([4,7,9]),b=ivy.array([14,17,34]))
  >>> ivy.Container.static_randint(x, y)
  {
      a: ivy.array([1, 6, 5]),
      b: ivy.array([0, 10, 17])
  }
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code: def _static_randint(
      low: Union[int, ivy.Container, ivy.Array, ivy.NativeArray],
      high: Union[int, ivy.Container, ivy.Array, ivy.NativeArray],
      /,
      *,
      shape: Optional[
          Union[ivy.Shape, ivy.NativeShape, ivy.Container]
      ] = None,
      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,
      device: Optional[
          Union[ivy.Device, ivy.NativeDevice, ivy.Container]
      ] = None,
      dtype: Optional[
          Union[ivy.Dtype, ivy.NativeDtype, ivy.Container]
      ] = None,
      seed: Optional[Union[int, ivy.Container]] = None,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.randint. This method
      simply wraps the function, and so the docstring for ivy.randint also
      applies to this method with minimal changes.
  
      Parameters
      ----------
      low
          Lowest integer that can be drawn from the distribution.
      high
          One above the highest integer that can be drawn from the distribution.
      shape
          If the given shape is, e.g ``(m, n, k)``, then ``m * n * k`` samples
          are drawn. Can only be specified when ``low`` and ``high`` are numeric
          values, else exception will be raised.
          Default is ``None``, where a single value is returned.
      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``.
      device
          device on which to create the array 'cuda:0', 'cuda:1', 'cpu' etc.
          (Default value = None).
      dtype
           output array data type. If ``dtype`` is ``None``, the output array data
           type will be the default integer data type. Default ``None``
      seed
          A python integer. Used to create a random seed distribution
      out
          optional output array, for writing the result to. It must have a shape
          that the inputs broadcast to.
  
      Returns
      -------
      ret
          Returns an array with the given shape filled with integers from
          the uniform distribution in the “half-open” interval [low, high)
  
      Examples
      --------
      With :class:`ivy.Container` inputs:
  
      >>> x = ivy.Container(a=ivy.array([[9,7],[6,2]]),
      ...                   b=ivy.array([[0,2],[10,6]]))
      >>> y = ivy.Container(a=ivy.array([[10,32],[18,19]]),
      ...                   b=ivy.array([[44,5],[23,54]]))
      >>> ivy.Container.static_randint(x, y, device='cpu', dtype='int32')
      {
          a: ivy.array([[9, 27],
                        [16, 17]]),
          b: ivy.array([[13, 3],
                        [16, 19]])
      }
  
      With a mix of :class:`ivy.Array` and :class:`ivy.Container` inputs:
  
      >>> x = ivy.array([-1,-9,3])
      >>> y = ivy.Container(a=ivy.array([4,7,9]),b=ivy.array([14,17,34]))
      >>> ivy.Container.static_randint(x, y)
      {
          a: ivy.array([1, 6, 5]),
          b: ivy.array([0, 10, 17])
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "randint",
          low,
          high,
          shape=shape,
          device=device,
          dtype=dtype,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          seed=seed,
          out=out,
      )
  
file_path: ivy/ivy/data_classes/container/random.py
imports: from typing import Optional, Union, List, Dict
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 7 for calling the _ContainerWithRandom obj's underlying member method code with example usage: obj._static_randint() and returns: ContainerBase