class_docstr: Generate distance map.
  In general, the instance map is calculated from the distance to the background.
  Here, we use 1 - "instance border map" to generate the distance map.
  Nuclei values form mountains so invert them to get basins.
  
  Args:
      smooth_fn: smoothing function for distance map, which can be any callable object.
          If not provided :py:class:`monai.transforms.GaussianSmooth()` is used.
      dtype: target data type to convert to. Defaults to np.float32.
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code: def __init__(
      self,
      smooth_fn: Callable | None = None,
      dtype: DtypeLike = np.float32,
  ) -> None:
      self.smooth_fn = (
          smooth_fn if smooth_fn is not None else GaussianSmooth()
      )
      self.dtype = dtype
  
imports: from __future__ import annotations
  import warnings
  from typing import Callable, Sequence
  import numpy
  import torch
  from monai.config.type_definitions import DtypeLike, NdarrayOrTensor
  from monai.transforms import Activations, AsDiscrete, BoundingRect, FillHoles, GaussianSmooth, RemoveSmallObjects, SobelGradients
  from monai.transforms.transform import Transform
  from monai.transforms.utils_pytorch_numpy_unification import max, maximum, min, sum, unique
  from monai.utils import TransformBackends, convert_to_numpy, optional_import
  from monai.utils.misc import ensure_tuple_rep
  from monai.utils.type_conversion import convert_to_dst_type, convert_to_tensor
label_desc: Use image node_id 1 to create a new GenerateDistanceMap object from inherited base classes: Transform with example: obj = GenerateDistanceMap(smooth_fn, dtype)