code: def unpackbits_masks(masks):
      """
      Args:
          masks (Tensor): uint8 Tensor of shape N, H, W. The last dimension is packed bits.
  
      Returns:
          masks (Tensor): bool Tensor of shape N, H, 8*W.
  
      This is a reverse operation of `np.packbits`
      """
      assert masks.dtype == tf.uint8, masks
      bits = tf.constant((128, 64, 32, 16, 8, 4, 2, 1), dtype=tf.uint8)
      unpacked = (
          tf.bitwise.bitwise_and(tf.expand_dims(masks, -1), bits) > 0
      )
      unpacked = tf.reshape(
          unpacked,
          tf.concat(
              [tf.shape(masks)[:-1], [8 * tf.shape(masks)[-1]]], axis=0
          ),
      )
      return unpacked
  
file_path: tensorpack/examples/FasterRCNN/modeling/model_mrcnn.py
imports: import tensorflow
  from tensorpack import tfv1
  from tensorpack.models import Conv2D, Conv2DTranspose, layer_register
  from tensorpack.tfutils.argscope import argscope
  from tensorpack.tfutils.scope_utils import under_name_scope
  from tensorpack.tfutils.summary import add_moving_summary
  from .backbone import GroupNorm
  from config import config
label_desc: Use image node_id 5 for calling a global function with example usage: unpackbits_masks(masks) and returns: unpacked