code: def dot(
      a: torch.Tensor,
      b: torch.Tensor,
      /,
      *,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      a, b = ivy.promote_types_of_inputs(a, b)
      if a.dim() == 0 or b.dim() == 0:
          return torch.mul(a, b, out=out)
      if (
          a.dim() in [1, 2]
          and b.dim() in [1, 2]
          or (a.dim() >= 1 and b.dim() == 1)
      ):
          return torch.matmul(a, b, out=out)
  
      return torch.tensordot(a, b, dims=[[-1], [-2]], out=out)
  
file_path: ivy/ivy/functional/backends/torch/experimental/linear_algebra.py
imports: import math
  import torch
  from typing import Optional, Tuple, Sequence, Union
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.utils.exceptions import IvyNotImplementedException
  from ..None import backend_version
  from ivy.functional.ivy.experimental.linear_algebra import _check_valid_dimension_size
label_desc: Use image node_id 11 for calling a global function with example usage: dot() and returns: torch, torch, torch