code: def linspace(
      start: Union[torch.Tensor, float],
      stop: Union[torch.Tensor, float],
      /,
      num: int,
      *,
      axis: Optional[int] = None,
      endpoint: bool = True,
      dtype: torch.dtype,
      device: torch.device = None,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if axis is None:
          axis = -1
      if not endpoint:
          if dtype is not None:
              ans = linspace_helper(
                  start, stop, num + 1, axis, dtype=dtype, device=device
              )
          else:
              ans = linspace_helper(
                  start, stop, num + 1, axis, device=device
              )
          if axis < 0:
              axis += len(ans.shape)
          ans = ans[_slice_at_axis(slice(None, -1), axis)]
      else:
          if dtype is not None:
              ans = linspace_helper(
                  start, stop, num, axis, dtype=dtype, device=device
              )
          else:
              ans = linspace_helper(
                  start, stop, num, axis, device=device
              )
      if (
          endpoint
          and ans.shape[0] > 1
          and (not isinstance(start, torch.Tensor))
          and (not isinstance(stop, torch.Tensor))
      ):
          ans[-1] = stop
      if (
          ans.shape[0] >= 1
          and (not isinstance(start, torch.Tensor))
          and (not isinstance(stop, torch.Tensor))
          and ans[0] != start
      ):
          ans[0] = start
      if "int" in str(dtype) and torch.is_floating_point(ans):
          ans = torch.floor(ans)
      return ans.to(dtype)
  
imports: import copy
  from numbers import Number
  from typing import Union, List, Optional, Sequence, Tuple
  import numpy
  import torch
  from torch import Tensor
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_unsupported_device_and_dtypes
  from ivy.functional.ivy.creation import _asarray_to_native_arrays_and_back, _asarray_infer_device, _asarray_infer_dtype, _asarray_handle_nestable, NestedSequence, SupportsBufferProtocol, _asarray_inputs_to_native_shapes, _remove_np_bfloat16
  from .None import backend_version
label_desc: Use image node_id 13 for calling a global function with example usage: linspace(num) and returns: ans