class_docstr: Dictionary version of RandSmoothFieldAdjustContrast.
  
  The field is randomized once per invocation by default so the same field is applied to every selected key. The
  `mode` parameter specifying interpolation mode for the field can be a single value or a sequence of values with
  one for each key in `keys`.
  
  Args:
      keys: key names to apply the augment to
      spatial_size: size of input arrays, all arrays stated in `keys` must have same dimensions
      rand_size: size of the randomized field to start from
      pad: number of pixels/voxels along the edges of the field to pad with 0
      mode: interpolation mode to use when upsampling
      align_corners: if True align the corners when upsampling field
      prob: probability transform is applied
      gamma: (min, max) range for exponential field
      device: Pytorch device to define field on
code: def __init__(
      self,
      keys: KeysCollection,
      spatial_size: Sequence[int],
      rand_size: Sequence[int],
      pad: int = 0,
      mode: SequenceStr = InterpolateMode.AREA,
      align_corners: bool | None = None,
      prob: float = 0.1,
      gamma: Sequence[float] | float = (0.5, 4.5),
      device: torch.device | None = None,
  ):
      RandomizableTransform.__init__(self, prob)
      MapTransform.__init__(self, keys)
  
      self.mode = ensure_tuple_rep(mode, len(self.keys))
  
      self.trans = RandSmoothFieldAdjustContrast(
          spatial_size=spatial_size,
          rand_size=rand_size,
          pad=pad,
          mode=self.mode[0],
          align_corners=align_corners,
          prob=1.0,
          gamma=gamma,
          device=device,
      )
  
imports: from __future__ import annotations
  from collections.abc import Hashable, Mapping, Sequence
  from typing import Any
  import numpy
  import torch
  from monai.config import KeysCollection, SequenceStr
  from monai.config.type_definitions import NdarrayOrTensor
  from monai.data.meta_obj import get_track_meta
  from monai.transforms.smooth_field.array import RandSmoothDeform, RandSmoothFieldAdjustContrast, RandSmoothFieldAdjustIntensity
  from monai.transforms.transform import MapTransform, RandomizableTransform
  from monai.utils import GridSampleMode, GridSamplePadMode, InterpolateMode, convert_to_tensor, ensure_tuple_rep
label_desc: Use image node_id 1 to create a new RandSmoothFieldAdjustContrastd object from inherited base classes: RandomizableTransform, MapTransform with example: obj = RandSmoothFieldAdjustContrastd(keys, spatial_size, rand_size, pad, mode, align_corners, prob, gamma, device)