img_HWC[:, :, 1] = 1 - np.arange(0, 10000).reshape(100, 100) / 10000
     writer = SummaryWriter()
     writer.add_image('my_image', img, 0)

     # If you have non-default dimension setting, set the dataformats argument.
     writer.add_image('my_image_HWC', img_HWC, 0, dataformats='HWC')
     writer.close()

  Expected result:

  [image]

add_images(tag, img_tensor, global_step=None, walltime=None, dataformats='NCHW')
  Add batched image data to summary.

  Note that this requires the "pillow" package.

  Parameters:
     * **tag** (*str*) -- Data identifier

     * **img_tensor** (*torch.Tensor**, **numpy.ndarray**, or
       **string/blobname*) -- Image data

     * **global_step** (*int*) -- Global step value to record

     * **walltime** (*float*) -- Optional override default
       walltime (time.time()) seconds after epoch of event

     * **dataformats** (*str*) -- Image data format specification
