parameters: (low, high, shape=None, ctx=None, out=None)
return_statement: return NDArray._random_uniform(low, high, out=out)
docstring: Generate uniform distribution in [low, high) with shape.
  
      Parameters
      ----------
      low : float
          The lower bound of distribution.
      high : float
          The upper bound of distribution.
      shape : tuple, optional
          Output shape of the NDArray generated.
      ctx : Context, optional
          Context of output NDArray, will use default context if not specified.
      out : NDArray, optional
          Output place holder
  
      Returns
      -------
      out : NDArray
          The result NDArray with generated result.
docstring_summary: Generate uniform distribution in [low, high) with shape.
docstring_tokens: Generate uniform distribution in [ low high ) with shape .
function: def uniform(low, high, shape=None, ctx=None, out=None):
      """Generate uniform distribution in [low, high) with shape.
  
      Parameters
      ----------
      low : float
          The lower bound of distribution.
      high : float
          The upper bound of distribution.
      shape : tuple, optional
          Output shape of the NDArray generated.
      ctx : Context, optional
          Context of output NDArray, will use default context if not specified.
      out : NDArray, optional
          Output place holder
  
      Returns
      -------
      out : NDArray
          The result NDArray with generated result.
      """
      if out is not None:
          if shape is not None or ctx is not None:
              raise ValueError('shape and ctx is not needed when out is specified')
      else:
          if shape is None:
              raise ValueError('shape is required when out is not specified')
          if isinstance(shape, int):
              shape = (shape,)
          out = empty(shape, ctx)
      return NDArray._random_uniform(low, high, out=out)
function_tokens: def uniform ( low , high , shape = None , ctx = None , out = None ) : if out is not None : if shape is not None or ctx is not None : raise ValueError ( 'shape and ctx is not needed when out is specified' ) else : if shape is None : raise ValueError ( 'shape is required when out is not specified' ) if isinstance ( shape , int ) : shape = ( shape , ) out = empty ( shape , ctx ) return NDArray . _random_uniform ( low , high , out = out )