docstr: ivy.Container static method variant of ivy.logspace. This method
  simply wraps the function, and so the docstring for ivy.logspace also
  applies to this method with minimal changes.
  
  Parameters
  ----------
  start
      Container for first value in the range in log space.
  stop
      Container for last value in the range in log space.
  num
      Number of values to generate.
  base
      The base of the log space. Default is 10.0
  axis
      Axis along which the operation is performed. Relevant only if values in
      start or stop containers are array-like. Default is 0.
  endpoint
      If True, stop is the last sample. Otherwise, it is not included. Default is
      True.
  dtype
      The data type of the output tensor. If None, the dtype of on_value is used
      or if that is None, the dtype of off_value is used, or if that is None,
      defaults to float32. Default is None.
  device
      device on which to create the array 'cuda:0', 'cuda:1', 'cpu' etc. Default
      is None.
  out
      optional output array, for writing the result to. It must have a shape that
      the inputs broadcast to. Default is None.
  
  Returns
  -------
  ret
      a container having the same shape as ``start`` and filled with tensor of
      evenly-spaced values in log space.
  
  Examples
  --------
  >>> import ivy.container.creation.static_logspace as static_logspace
  >>> x = ivy.Container(a = 1, b = 0)
  >>> y = ivy.Container(a = 4, b = 1)
  >>> z = static_logspace(x, y, 4)
  {
      a: ivy.array([10.,  100.,  1000., 10000.]),
      b: ivy.array([ 1., 2.15443469, 4.64158883, 10.])
  }
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code: def _static_logspace(
      start: Union[ivy.Array, ivy.NativeArray, float, ivy.Container],
      stop: Union[ivy.Array, ivy.NativeArray, float, ivy.Container],
      /,
      num: Union[int, 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,
      *,
      base: Union[float, ivy.Container] = 10.0,
      axis: Union[int, ivy.Container] = 0,
      endpoint: Union[bool, ivy.Container] = True,
      dtype: Optional[
          Union[ivy.Dtype, ivy.NativeDtype, ivy.Container]
      ] = None,
      device: Optional[
          Union[ivy.Device, ivy.NativeDevice, ivy.Container]
      ] = None,
      out: Optional[ivy.Container] = None,
  ) -> ivy.Container:
      """ivy.Container static method variant of ivy.logspace. This method
      simply wraps the function, and so the docstring for ivy.logspace also
      applies to this method with minimal changes.
  
      Parameters
      ----------
      start
          Container for first value in the range in log space.
      stop
          Container for last value in the range in log space.
      num
          Number of values to generate.
      base
          The base of the log space. Default is 10.0
      axis
          Axis along which the operation is performed. Relevant only if values in
          start or stop containers are array-like. Default is 0.
      endpoint
          If True, stop is the last sample. Otherwise, it is not included. Default is
          True.
      dtype
          The data type of the output tensor. If None, the dtype of on_value is used
          or if that is None, the dtype of off_value is used, or if that is None,
          defaults to float32. Default is None.
      device
          device on which to create the array 'cuda:0', 'cuda:1', 'cpu' etc. Default
          is None.
      out
          optional output array, for writing the result to. It must have a shape that
          the inputs broadcast to. Default is None.
  
      Returns
      -------
      ret
          a container having the same shape as ``start`` and filled with tensor of
          evenly-spaced values in log space.
  
      Examples
      --------
      >>> import ivy.container.creation.static_logspace as static_logspace
      >>> x = ivy.Container(a = 1, b = 0)
      >>> y = ivy.Container(a = 4, b = 1)
      >>> z = static_logspace(x, y, 4)
      {
          a: ivy.array([10.,  100.,  1000., 10000.]),
          b: ivy.array([ 1., 2.15443469, 4.64158883, 10.])
      }
      """
      return ContainerBase.cont_multi_map_in_function(
          "logspace",
          start,
          stop,
          num=num,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
          base=base,
          axis=axis,
          endpoint=endpoint,
          dtype=dtype,
          device=device,
          out=out,
      )
  
imports: from typing import Optional, Union, List, Tuple, Dict, Sequence
  from numbers import Number
  import numpy
  import ivy
  from ivy.data_classes.container.base import ContainerBase
label_desc: Use image node_id 31 for calling the _ContainerWithCreation obj's underlying member method code with example usage: obj._static_logspace(num, key_chains, to_apply, prune_unapplied, map_sequences) and returns: ContainerBase