class_docstr: `FeatureConnector` for generic data of arbitrary shape and type.
code: def to_json_content(self) -> feature_pb2.TensorFeature:
      return feature_pb2.TensorFeature(
          shape=feature_lib.to_shape_proto(self._shape),
          dtype=feature_lib.dtype_to_str(self._dtype),
          encoding=self._encoding.value,
      )
  
imports: from __future__ import annotations
  import enum
  import functools
  from typing import Optional, Protocol, Tuple, TypeVar, Union
  import zlib
  from etils import enp
  import numpy
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.proto import feature_pb2
  from tensorflow_datasets.core.utils import dtype_utils
  from tensorflow_datasets.core.utils import np_utils
  from tensorflow_datasets.core.utils import py_utils
  from tensorflow_datasets.core.utils import type_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
label_desc: Use image node_id 12 for calling the Tensor obj's underlying member method code with example usage: obj.to_json_content() and returns: feature_pb2