code: def random_uniform(
      *,
      low: Union[float, paddle.Tensor] = 0.0,
      high: Union[float, paddle.Tensor] = 1.0,
      shape: Optional[
          Union[paddle.Tensor, ivy.NativeShape, Sequence[int]]
      ] = None,
      dtype: paddle.dtype,
      device: core.Place = None,
      seed=None,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      if not dtype:
          dtype = ivy.default_int_dtype()
      dtype = ivy.as_native_dtype(dtype)
      low = (
          paddle.cast(low, "float32")
          if isinstance(low, paddle.Tensor)
          else low
      )
      high = (
          paddle.cast(high, "float32")
          if isinstance(high, paddle.Tensor)
          else high
      )
      shape = _check_bounds_and_get_shape(low, high, shape).shape
      # Set range and seed
      rng = high - low
      if seed:
          _ = paddle.seed(seed)
      random_base = paddle.uniform(shape, min=0.0, max=1.0)
  
      return paddle_backend.add(
          paddle_backend.multiply(random_base, rng), low
      ).cast(dtype)
  
file_path: ivy/ivy/functional/backends/paddle/random.py
imports: import paddle
  import ivy.functional.backends.paddle
  from typing import Optional, Union, Sequence
  import ivy
  from paddle.device import core
  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_device_and_dtypes, with_supported_device_and_dtypes, 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: paddle_backend