code: def _make_dict_ds(nrows):
      """Create a test set with various element shapes."""
  
      def transform(x):
          return {
              "shape=[]": ops.convert_to_tensor(x),
              "shape=[x]": math_ops.range(x),
              "shape=[x, 2]": array_ops.fill([x, 2], x),
              "shape=[2, x]": array_ops.fill([2, x], x),
              "shape=[2, x, 3, 2x, 4]": array_ops.fill(
                  [2, x, 3, 2 * x, 4], x
              ),
          }
  
      return _make_scalar_ds(nrows).map(transform)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.util import nest
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_concat_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 8 for calling a global function with example usage: _make_dict_ds(nrows) and returns: _make_scalar_ds, dict