class_docstr: Type specification for a `tf.sparse.SparseTensor`.
class_docstr_tok: ["Type","specification","for","a","`","tf.sparse.SparseTensor","`","."]
code: def _from_components(self, tensor_list):
      if (
          all(isinstance(t, np.ndarray) for t in tensor_list)
          and not tf2.enabled()
      ):
          return SparseTensorValue(*tensor_list)
      else:
          result = SparseTensor(*tensor_list)
          # Augment the static dense shape with the shape carried by the spec.
          result._dense_shape_default = result._dense_shape_default.merge_with(  # pylint: disable=protected-access
              self._shape
          )
          return result
  
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 7 for calling the SparseTensorSpec obj's underlying member method code with example usage: obj._from_components(tensor_list) and returns: SparseTensorValue, result