code: def skip_test_lstm(self):  # type: () -> None
      x = 4
      h = 2
      seq_length = 3
      W = from_array(_random_array((4 * h, x)), name="gate_weights")
      R = from_array(
          _random_array((4 * h, h)), name="recursion_weights"
      )
      B = from_array(_random_array((8 * h,)), name="biases")
      seq_lens_input = from_array(
          np.array([seq_length]).astype(np.int32), name="seq_lens_input"
      )
      initial_h = from_array(
          np.zeros((1, 1, h)).astype(np.float32), name="initial_h"
      )
      initial_c = from_array(
          np.zeros((1, 1, h)).astype(np.float32), name="initial_c"
      )
  
      input_shape = (seq_length, 1, x)
      output_shape_all = (seq_length, 1, h)
      output_shape_last = (1, 1, h)
  
      onnx_model = _onnx_create_single_node_model(
          "LSTM",
          [input_shape],
          [output_shape_all, output_shape_last],
          initializer=[W, R, B, seq_lens_input, initial_h, initial_c],
          hidden_size=h,
      )
      X = np.random.rand(*input_shape).astype("float32")  # type: ignore
      import caffe2.python.onnx.backend
  
      prepared_backend = caffe2.python.onnx.backend.prepare(onnx_model)
      out = prepared_backend.run({"input0": X})
      caffe2_out_all = out["output0"]
      caffe2_out_last = out["output1"]
  
      coreml_model = convert(onnx_model)
      inputdict = {}
      inputdict["input0"] = X
      inputdict["initial_h"] = np.zeros((h), dtype=np.float32)
      inputdict["initial_c"] = np.zeros((h), dtype=np.float32)
      coreml_out_dict = coreml_model.predict(inputdict, useCPUOnly=True)
      coreml_out_all = coreml_out_dict["output0"]
      coreml_out_last = coreml_out_dict["output1"]
  
      _assert_outputs(
          caffe2_out_all.flatten(), coreml_out_all.flatten(), decimal=5
      )
      _assert_outputs(
          caffe2_out_last.flatten(),
          coreml_out_last.flatten(),
          decimal=5,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import unittest
  import numpy
  from coremltools._deps import _HAS_ONNX, MSG_ONNX_NOT_FOUND
  from typing import Text
  from coremltools.models.utils import _macos_version
label_desc: Use image node_id 22 for calling the SingleOperatorTest obj's underlying member method code with example usage: obj.skip_test_lstm() without return types