code: def random_uniform(
      *,
      low: Union[float, torch.Tensor] = 0.0,
      high: Union[float, torch.Tensor] = 1.0,
      shape: Optional[
          Union[torch.Tensor, ivy.NativeShape, Sequence[int]]
      ] = None,
      dtype: torch.dtype,
      device: torch.device = None,
      seed: Optional[int] = None,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      shape = _check_bounds_and_get_shape(low, high, shape).shape
      rand_range = high - low
      if seed:
          torch.manual_seed(seed)
      if torch.is_tensor(shape):
          shape = shape.tolist()
      return (
          torch.rand(shape, device=device, dtype=torch.float)
          * rand_range
          + low
      ).type(dtype)
  
file_path: ivy/ivy/functional/backends/torch/random.py
imports: import torch
  from typing import Optional, Union, Sequence
  import ivy
  from ivy.functional.ivy.random import _check_bounds_and_get_shape, _randint_check_dtype_and_bound, _check_valid_scale
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
label_desc: Use image node_id 1 for calling a global function with example usage: random_uniform() and returns: unknown