docstr: ivy.Array instance 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
  ----------
  self
      First value in the range in log space. base ** start is the starting value
      in the sequence. Can be an array or a float.
  stop
      Last value in the range in log space. base ** stop is the final value in the
      sequence. Can be an array or a float.
  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 start or stop
      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
      Tensor of evenly-spaced values in log space.
  
  Both the description and the type hints above assumes an array input for
  simplicity, but this function is *nestable*, and therefore also accepts
  :class:`ivy.Container` instances in place of any of the arguments.
  
  Examples
  --------
  With float input:
  
  >>> x = ivy.array([1, 2])
  >>> y = ivy.array([4, 5])
  >>> x.logspace(y, 4)
  ivy.array([[1.e+01, 1.e+02],
             [1.e+02, 1.e+03],
             [1.e+03, 1.e+04],
             [1.e+04, 1.e+05])
  
  >>> x.logspace(y, 4, axis = 1)
  ivy.array([[[1.e+01, 1.e+02, 1.e+03, 1.e+04],
             [1.e+02, 1.e+03, 1.e+04, 1.e+05]]])
  
  >>> x = ivy.array([1, 2])
  >>> y = ivy.array([4])      # Broadcasting example
  >>> x.logspace(y, 4)
  ivy.array([[10., 100.]
             [100., 464.15888336]
             [1000., 2154.43469003]
             [10000., 10000.]])
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code: def logspace(
      self: ivy.Array,
      stop: Union[ivy.Array, ivy.NativeArray, float],
      /,
      num: int,
      *,
      base: float = 10.0,
      axis: int = 0,
      endpoint: bool = True,
      dtype: Optional[Union[ivy.Dtype, ivy.NativeDtype]] = None,
      device: Optional[Union[ivy.Device, ivy.NativeDevice]] = None,
      out: Optional[ivy.Array] = None,
  ) -> ivy.Array:
      """ivy.Array instance 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
      ----------
      self
          First value in the range in log space. base ** start is the starting value
          in the sequence. Can be an array or a float.
      stop
          Last value in the range in log space. base ** stop is the final value in the
          sequence. Can be an array or a float.
      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 start or stop
          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
          Tensor of evenly-spaced values in log space.
  
      Both the description and the type hints above assumes an array input for
      simplicity, but this function is *nestable*, and therefore also accepts
      :class:`ivy.Container` instances in place of any of the arguments.
  
      Examples
      --------
      With float input:
  
      >>> x = ivy.array([1, 2])
      >>> y = ivy.array([4, 5])
      >>> x.logspace(y, 4)
      ivy.array([[1.e+01, 1.e+02],
                 [1.e+02, 1.e+03],
                 [1.e+03, 1.e+04],
                 [1.e+04, 1.e+05])
  
      >>> x.logspace(y, 4, axis = 1)
      ivy.array([[[1.e+01, 1.e+02, 1.e+03, 1.e+04],
                 [1.e+02, 1.e+03, 1.e+04, 1.e+05]]])
  
      >>> x = ivy.array([1, 2])
      >>> y = ivy.array([4])      # Broadcasting example
      >>> x.logspace(y, 4)
      ivy.array([[10., 100.]
                 [100., 464.15888336]
                 [1000., 2154.43469003]
                 [10000., 10000.]])
      """
      return ivy.logspace(
          self,
          stop,
          num=num,
          base=base,
          axis=axis,
          endpoint=endpoint,
          dtype=dtype,
          device=device,
          out=out,
      )
  
file_path: ivy/ivy/data_classes/array/creation.py
imports: import abc
  from numbers import Number
  from typing import Optional, Union, List
  import ivy
label_desc: Use image node_id 14 for calling the _ArrayWithCreation obj's underlying member method code with example usage: obj.logspace(num) and returns: ivy