code: def _image3_animated_gif(
      tag: str,
      image: np.ndarray | torch.Tensor,
      writer: SummaryWriter | SummaryWriterX | None,
      frame_dim: int = 0,
      scale_factor: float = 1.0,
  ) -> Any:
      """Function to actually create the animated gif.
  
      Args:
          tag: Data identifier
          image: 3D image tensors expected to be in `HWD` format
          writer: the tensorboard writer to plot image
          frame_dim: the dimension used as frames for GIF image, expect data shape as `HWD`, default to `0`.
          scale_factor: amount to multiply values by. if the image data is between 0 and 1, using 255 for this value will
              scale it to displayable range
      """
      if len(image.shape) != 3:
          raise AssertionError(
              "3D image tensors expected to be in `HWD` format, len(image.shape) != 3"
          )
  
      image_np, *_ = convert_data_type(image, output_type=np.ndarray)
      ims = [
          (i * scale_factor).astype(np.uint8, copy=False)
          for i in np.moveaxis(image_np, frame_dim, 0)
      ]
      ims = [GifImage.fromarray(im) for im in ims]
      img_str = b""
      for b_data in PIL.GifImagePlugin.getheader(ims[0])[0]:
          img_str += b_data
      img_str += (
          b"\x21\xFF\x0B\x4E\x45\x54\x53\x43\x41\x50"
          b"\x45\x32\x2E\x30\x03\x01\x00\x00\x00"
      )
      for i in ims:
          for b_data in PIL.GifImagePlugin.getdata(i):
              img_str += b_data
      img_str += b"\x3B"
  
      summary = (
          SummaryX
          if has_tensorboardx and isinstance(writer, SummaryWriterX)
          else Summary
      )
      summary_image_str = summary.Image(
          height=10,
          width=10,
          colorspace=1,
          encoded_image_string=img_str,
      )
      image_summary = summary.Value(tag=tag, image=summary_image_str)
      return summary(value=[image_summary])
  
file_path: MONAI/monai/visualize/img2tensorboard.py
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any
  import numpy
  import torch
  from monai.config import NdarrayTensor
  from monai.transforms import rescale_array
  from monai.utils import convert_data_type, optional_import
label_desc: Use image node_id 1 for calling a global function with example usage: _image3_animated_gif(tag, image, writer, frame_dim, scale_factor) and returns: summary