code: def logical_not(x, out=None, where=None, **kwargs):
      """
      Compute the truth value of NOT x element-wise.
  
      Parameters
      ----------
      x : array_like
          Logical NOT is applied to the elements of `x`.
      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
      -------
      y : bool or Tensor of bool
          Boolean result with the same shape as `x` of the NOT operation
          on elements of `x`.
  
      See Also
      --------
      logical_and, logical_or, logical_xor
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> mt.logical_not(3).execute()
      False
      >>> mt.logical_not([True, False, 0, 1]).execute()
      array([False,  True,  True, False])
  
      >>> x = mt.arange(5)
      >>> mt.logical_not(x<3).execute()
      array([False, False, False,  True,  True])
      """
      op = TensorNot(**kwargs)
      return op(x, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/logical_not.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: logical_not(x, out, where) and returns: op