class_docstr: Compute the Spatial Soft-Argmax 2D of a given heatmap.
  
  See :func:`~kornia.geometry.subpix.spatial_soft_argmax2d` for details.
code: def __init__(
      self,
      temperature: Tensor = tensor(1.0),
      normalized_coordinates: bool = True,
  ) -> None:
      super().__init__()
      self.temperature: Tensor = temperature
      self.normalized_coordinates: bool = normalized_coordinates
  
imports: from __future__ import annotations
  import torch
  import torch.nn.functional
  from kornia.core import Module, Tensor, concatenate, rand, stack, tensor, where, zeros, zeros_like
  from kornia.filters.sobel import spatial_gradient3d
  from kornia.geometry.conversions import normalize_pixel_coordinates, normalize_pixel_coordinates3d
  from kornia.utils import create_meshgrid, create_meshgrid3d
  from kornia.utils._compat import torch_version_ge
  from kornia.utils.helpers import safe_solve_with_mask
  from .dsnt import spatial_expectation2d, spatial_softmax2d
  from .nms import nms3d
label_desc: Use image node_id 1 to create a new SpatialSoftArgmax2d object from inherited base classes: Module with example: obj = SpatialSoftArgmax2d(temperature, normalized_coordinates)