class_docstr: TIFFIOTensor
class_docstr_tok: ["TIFFIOTensor"]
code: def __init__(self, filename, internal=False):
      with tf.name_scope("TIFFIOTensor"):
          # TIFF can fit into memory so load TIFF first
          data = tf.io.read_file(filename)
          shapes, dtypes = core_ops.io_decode_tiff_info(data)
          # NOTE: While shapes returned correctly handles 3 or 4 channels
          # we can only handle RGBA so fix shape as 4 for now,
          # until decode_tiff is updated.
          spec = tuple(
              tf.TensorSpec(
                  tf.TensorShape(shape.tolist()[0:2] + [4]), dtype
              )
              for (shape, dtype) in zip(shapes.numpy(), dtypes.numpy())
          )
          columns = [i for i, _ in enumerate(spec)]
          elements = [
              io_tensor_ops.TensorIOTensor(
                  core_ops.io_decode_tiff(data, i), internal=internal
              )
              for i in columns
          ]
          super().__init__(spec, columns, elements, internal=internal)
  
imports: import tensorflow
  from tensorflow_io.python.ops import io_tensor_ops
  from tensorflow_io.python.ops import core_ops
label_desc: Use image node_id 1 to create a new TIFFIOTensor object from inherited base classes: io_tensor_ops with example: obj = TIFFIOTensor(filename, internal)