code: def laplace(
      loc=0.0, scale=1.0, size=None, dtype=None, ctx=None, out=None
  ):
      r"""Draw random samples from a Laplace distribution.
  
      Samples are distributed according to a Laplace distribution parametrized
      by *loc* (mean) and *scale* (the exponential decay).
  
      Parameters
      ----------
      loc : float, The position of the distribution peak.
  
      scale : float, the exponential decay.
  
      size : int or tuple of ints, optional. Output shape.
          If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn.
          Default is None, in which case a single value is returned.
  
      dtype : {'float16', 'float32', 'float64'}, optional
          Data type of output samples. Default is 'float32'
      ctx : Context, optional
          Device context of output. Default is current context.
      out : ``ndarray``, optional
          Store output to an existing ``ndarray``.
  
      Returns
      -------
      out : _Symbol (symbol representing `mxnet.numpy.ndarray` in computational graphs)
          Drawn samples from the parameterized Laplace distribution.
      """
      from ._symbol import _Symbol as np_symbol
  
      input_type = (
          isinstance(loc, np_symbol),
          isinstance(scale, np_symbol),
      )
      if dtype is None:
          dtype = "float32"
      if ctx is None:
          ctx = current_context()
      if size == ():
          size = None
      if input_type == (True, True):
          return _npi.laplace(
              loc,
              scale,
              loc=None,
              scale=None,
              size=size,
              ctx=ctx,
              dtype=dtype,
              out=out,
          )
      elif input_type == (False, True):
          return _npi.laplace(
              scale,
              loc=loc,
              scale=None,
              size=size,
              ctx=ctx,
              dtype=dtype,
              out=out,
          )
      elif input_type == (True, False):
          return _npi.laplace(
              loc,
              loc=None,
              scale=scale,
              size=size,
              ctx=ctx,
              dtype=dtype,
              out=out,
          )
      else:
          return _npi.laplace(
              loc=loc,
              scale=scale,
              size=size,
              ctx=ctx,
              dtype=dtype,
              out=out,
          )
  
imports: import numpy
  from ...context import current_context
  from ...util import is_np_default_dtype
  from .None import _internal
label_desc: Use image node_id 9 for calling a global function with example usage: laplace(loc, scale, size, dtype, ctx, out) and returns: _npi, _npi, _npi, _npi