class_docstr: Module that calculates soft argmax 3d per window.
  
  See
  :func: `~kornia.geometry.subpix.conv_soft_argmax3d` for details.
code: def __init__(
      self,
      kernel_size: tuple[int, int, int] = (3, 3, 3),
      stride: tuple[int, int, int] = (1, 1, 1),
      padding: tuple[int, int, int] = (1, 1, 1),
      temperature: Tensor | float = tensor(1.0),
      normalized_coordinates: bool = False,
      eps: float = 1e-8,
      output_value: bool = True,
      strict_maxima_bonus: float = 0.0,
  ) -> None:
      super().__init__()
      self.kernel_size = kernel_size
      self.stride = stride
      self.padding = padding
      self.temperature = temperature
      self.normalized_coordinates = normalized_coordinates
      self.eps = eps
      self.output_value = output_value
      self.strict_maxima_bonus = strict_maxima_bonus
  
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 ConvSoftArgmax3d object from inherited base classes: Module with example: obj = ConvSoftArgmax3d(kernel_size, stride, padding, temperature, normalized_coordinates, eps, output_value, strict_maxima_bonus)