code: def expm1(x, out=None, where=None, **kwargs):
      """
      Calculate ``exp(x) - 1`` for all elements in the tensor.
  
      Parameters
      ----------
      x : array_like
         Input values.
      out : Tensor, None, or tuple of Tensor and None, optional
          A location into which the result is stored. If provided, it must have
          a shape that the inputs broadcast to. If not provided or `None`,
          a freshly-allocated tensor is returned. A tuple (possible only as a
          keyword argument) must have length equal to the number of outputs.
      where : array_like, optional
          Values of True indicate to calculate the ufunc at that position, values
          of False indicate to leave the value in the output alone.
      **kwargs
  
      Returns
      -------
      out : Tensor
          Element-wise exponential minus one: ``out = exp(x) - 1``.
  
      See Also
      --------
      log1p : ``log(1 + x)``, the inverse of expm1.
  
  
      Notes
      -----
      This function provides greater precision than ``exp(x) - 1``
      for small values of ``x``.
  
      Examples
      --------
      The true value of ``exp(1e-10) - 1`` is ``1.00000000005e-10`` to
      about 32 significant digits. This example shows the superiority of
      expm1 in this case.
  
      >>> import mars.tensor as mt
  
      >>> mt.expm1(1e-10).execute()
      1.00000000005e-10
      >>> (mt.exp(1e-10) - 1).execute()
      1.000000082740371e-10
      """
      op = TensorExpm1(**kwargs)
      return op(x, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/expm1.py
imports: import numpy
  from ...None import opcodes
  from ..utils import infer_dtype
  from .core import TensorUnaryOp
  from .utils import arithmetic_operand
label_desc: Use image node_id 1 for calling a global function with example usage: expm1(x, out, where) and returns: op