code: def get_attention_parameter_tuples():
      # (query_input_dims, value_input_dims, use_key, use_attention_mask,
      #  num_heads, key_dim, value_dim, dropout, use_bias, output_shape)
      return [
          # Small instances, default flags.
          (
              [2, 3],
              [3, 4],
              False,
              False,
              2,
              2,
              3,
              0.0,
              True,
              None,
          ),  # defaults
          (
              [2, 3],
              [3, 4],
              True,
              False,
              2,
              2,
              3,
              0.0,
              True,
              None,
          ),  # use key
          (
              [2, 3],
              [3, 4],
              False,
              False,
              2,
              2,
              3,
              0.0,
              False,
              None,
          ),  # no bias
          (
              [2, 3],
              [3, 4],
              False,
              False,
              2,
              2,
              3,
              0.1,
              True,
              None,
          ),  # dropout
          (
              [2, 3],
              [3, 4],
              False,
              False,
              2,
              2,
              3,
              0.0,
              True,
              [3],
          ),  # output shape
          (
              [2, 3],
              [3, 4],
              False,
              False,
              1,
              2,
              3,
              0.0,
              True,
              3,
          ),  # single head
          (
              [2, 3],
              [3, 4],
              False,
              True,
              2,
              2,
              3,
              0.0,
              True,
              None,
          ),  # attention mask
      ]
  
imports: from absl.testing import parameterized
  import tensorflow
  from tensorflow_privacy.privacy.fast_gradient_clipping import common_test_utils
  from tensorflow_privacy.privacy.fast_gradient_clipping import layer_registry
  from tensorflow_privacy.privacy.fast_gradient_clipping.registry_functions import dense
  from tensorflow_privacy.privacy.fast_gradient_clipping.registry_functions import multi_head_attention
label_desc: Use image node_id 5 for calling a global function with example usage: get_attention_parameter_tuples() and returns: list