code: def _ragged_tensor_to_variant_grad(op, encoded_ragged_grad):
      """Gradient for RaggedTensorToVariant op."""
      dense_values = op.inputs[-1]
      ragged_rank = len(op.inputs) - 1
      row_splits = 0 if ragged_rank == 0 else op.inputs[0]
      values_grad = (
          gen_ragged_conversion_ops.ragged_tensor_to_variant_gradient(
              encoded_ragged_grad=encoded_ragged_grad,
              row_splits=row_splits,
              dense_values_shape=array_ops.shape(dense_values),
              Tvalues=op.inputs[-1].dtype,
          )
      )
      result = [None] * ragged_rank + [values_grad]
      return result
  
file_path: tensorflow/tensorflow/python/ops/ragged/ragged_conversion_ops.py
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_ragged_conversion_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
label_desc: Use image node_id 9 for calling a global function with example usage: _ragged_tensor_to_variant_grad(op, encoded_ragged_grad) and returns: result