code: def isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False):
      """
      Returns a boolean tensor where two tensors are element-wise equal within a
      tolerance.
  
      The tolerance values are positive, typically very small numbers.  The
      relative difference (`rtol` * abs(`b`)) and the absolute difference
      `atol` are added together to compare against the absolute difference
      between `a` and `b`.
  
      Parameters
      ----------
      a, b : array_like
          Input tensors to compare.
      rtol : float
          The relative tolerance parameter (see Notes).
      atol : float
          The absolute tolerance parameter (see Notes).
      equal_nan : bool
          Whether to compare NaN's as equal.  If True, NaN's in `a` will be
          considered equal to NaN's in `b` in the output tensor.
  
      Returns
      -------
      y : array_like
          Returns a boolean tensor of where `a` and `b` are equal within the
          given tolerance. If both `a` and `b` are scalars, returns a single
          boolean value.
  
      See Also
      --------
      allclose
  
      Notes
      -----
  
      For finite values, isclose uses the following equation to test whether
      two floating point values are equivalent.
  
       absolute(`a` - `b`) <= (`atol` + `rtol` * absolute(`b`))
  
      The above equation is not symmetric in `a` and `b`, so that
      `isclose(a, b)` might be different from `isclose(b, a)` in
      some rare cases.
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> mt.isclose([1e10,1e-7], [1.00001e10,1e-8]).execute()
      array([True, False])
      >>> mt.isclose([1e10,1e-8], [1.00001e10,1e-9]).execute()
      array([True, True])
      >>> mt.isclose([1e10,1e-8], [1.0001e10,1e-9]).execute()
      array([False, True])
      >>> mt.isclose([1.0, mt.nan], [1.0, mt.nan]).execute()
      array([True, False])
      >>> mt.isclose([1.0, mt.nan], [1.0, mt.nan], equal_nan=True).execute()
      array([True, True])
      """
      op = TensorIsclose(
          rtol=rtol,
          atol=atol,
          equal_nan=equal_nan,
          dtype=np.dtype(bool),
      )
      return op(a, b)
  
file_path: mars/mars/tensor/arithmetic/isclose.py
imports: import numpy
  from ...None import opcodes
  from ...serialization.serializables import Float64Field, BoolField
  from ..array_utils import device, as_same_device
  from .core import TensorBinOp
label_desc: Use image node_id 1 for calling a global function with example usage: isclose(a, b, rtol, atol, equal_nan) and returns: op