class_docstr: Type specification for a `tf.sparse.SparseTensor`.
class_docstr_tok: ["Type","specification","for","a","`","tf.sparse.SparseTensor","`","."]
code: def _to_batched_tensor_list(self, value):
      dense_shape = tensor_util.constant_value_as_shape(
          value.dense_shape
      )
      if self._shape.merge_with(dense_shape).ndims == 0:
          raise ValueError(
              "Unbatching a sparse tensor is only supported for rank >= 1. "
              f"Obtained input: {value}."
          )
      return [
          gen_sparse_ops.serialize_many_sparse(
              value.indices,
              value.values,
              value.dense_shape,
              out_type=dtypes.variant,
          )
      ]
  
imports: import collections
  import numpy
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python import pywrap_tensorflow
  from tensorflow.python import tf2
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import override_binary_operator
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.framework import type_spec
  from tensorflow.python.framework import type_spec_registry
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import gen_sparse_ops
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.types import internal
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 10 for calling the SparseTensorSpec obj's underlying member method code with example usage: obj._to_batched_tensor_list(value) and returns: list