class_docstr: An abstract class that defines a data source.
class_docstr_tok: ["An","abstract","class","that","defines","a","data","source","."]
docstr: Returns the Tensorflow data signature for an item.
code: def _get_item_signature(self):
      """Returns the Tensorflow data signature for an item."""
      sig = {
          "rgb": tf.TensorSpec(shape=(None, None, 3), dtype=tf.float32),
          "camera_params": _TF_CAMERA_PARAMS_SIGNATURE,
          "metadata": {},
      }
      if self.use_appearance_id:
          sig["metadata"]["appearance"] = tf.TensorSpec(
              shape=(), dtype=tf.uint32
          )
      if self.use_camera_id:
          sig["metadata"]["camera"] = tf.TensorSpec(
              shape=(), dtype=tf.uint32
          )
      if self.use_warp_id:
          sig["metadata"]["warp"] = tf.TensorSpec(
              shape=(), dtype=tf.uint32
          )
      if self.use_time:
          sig["metadata"]["time"] = tf.TensorSpec(
              shape=(), dtype=tf.float32
          )
  
      return sig
  
imports: import abc
  import functools
  import itertools
  from typing import Any, Iterable, Optional, Sequence, Union
  from absl import logging
  from flax import jax_utils
  import jax
  import numpy
  import tensorflow
  from nerfies import camera
  from nerfies import gpath
  from nerfies import image_utils
  from nerfies import tf_camera
  from nerfies import utils
  from tensorflow.python.data.util import nest
label_desc: Use image node_id 28 for calling the DataSource obj's underlying member method code with example usage: obj._get_item_signature() and returns: sig