code: def test_invalid_activation_lstm(self):
      seq_len = 3
      batch = 2
      input_size = 4
      hidden_size = 5
      arguments = {
          "x": np.random.rand(seq_len, batch, input_size),
          "initial_h": np.zeros((batch, hidden_size)).astype(
              np.float32
          ),
          "initial_c": np.zeros((batch, hidden_size)).astype(
              np.float32
          ),
          "weight_ih": np.random.rand(4 * hidden_size, input_size),
          "weight_hh": np.random.rand(4 * hidden_size, hidden_size),
          "direction": "forward",
      }
  
      with pytest.raises(
          ValueError, match="Activation `dummy` not supported."
      ):
          mb.lstm(recurrent_activation="dummy", **arguments)
  
      with pytest.raises(
          ValueError, match="Activation `dummy` not supported."
      ):
          mb.lstm(cell_activation="dummy", **arguments)
  
      with pytest.raises(
          ValueError, match="Activation `dummy` not supported."
      ):
          mb.lstm(activation="dummy", **arguments)
  
imports: import itertools
  import numpy
  import pytest
  import coremltools
  from coremltools._deps import _HAS_TORCH, MSG_TORCH_NOT_FOUND
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import get_new_symbol
  from coremltools.converters.mil.mil.ops.tests.iOS14 import backends
  from coremltools.converters.mil.mil.ops.tests.testing_utils import construct_inputs_from_placeholders, run_compare_builder
  from coremltools.converters.mil.mil.types.type_mapping import numpy_type_to_builtin_type
  from coremltools.converters.mil.testing_reqs import compute_units
  from coremltools.converters.mil.testing_utils import ssa_fn
label_desc: Use image node_id 5 for calling the TestLSTM obj's underlying member method code with example usage: obj.test_invalid_activation_lstm() without return types