code: def _indexed_slices_to_tensor(
      value, dtype=None, name=None, as_ref=False
  ):
      """Converts an IndexedSlices object `value` to a Tensor.
  
      NOTE(mrry): This function is potentially expensive.
  
      Args:
        value: An ops.IndexedSlices object.
        dtype: The dtype of the Tensor to be returned.
        name: Optional name to use for the returned Tensor.
        as_ref: True if a ref is requested.
  
      Returns:
        A dense Tensor representing the values in the given IndexedSlices.
  
      Raises:
        ValueError: If the IndexedSlices does not have the same dtype.
      """
      _ = as_ref
      if dtype and not dtype.is_compatible_with(value.dtype):
          raise ValueError(
              f"Incompatible tensor conversion requested to `dtype` {dtype.name} for "
              f"IndexedSlices ({value}) with dtype {value.dtype.name}"
          )
      if value.dense_shape is None:
          raise ValueError(
              "Tensor conversion requested for IndexedSlices for argument `value` "
              f"without dense_shape: {value!s}"
          )
      # TODO(mrry): Consider adding static shape information to
      # IndexedSlices, to avoid using numpy here.
      if not context.executing_eagerly():
          dense_shape_value = tensor_util.constant_value(
              value.dense_shape
          )
          if dense_shape_value is not None:
              num_elements = np.prod(dense_shape_value)
              if num_elements >= _LARGE_SPARSE_NUM_ELEMENTS:
                  warnings.warn(
                      "Converting sparse IndexedSlices to a dense Tensor with %d "
                      "elements. This may consume a large amount of memory."
                      % num_elements
                  )
      return gen_math_ops.unsorted_segment_sum(
          value.values, value.indices, value.dense_shape[0], name=name
      )
  
imports: import collections
  import warnings
  import numpy
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python import tf2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import composite_tensor_gradient
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion_registry
  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.ops import gen_math_ops
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.types import internal
  from tensorflow.python.util.compat import collections_abc
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 5 for calling a global function with example usage: _indexed_slices_to_tensor(value, dtype, name, as_ref) and returns: gen_math_ops