code: def export_defaults() -> None:
      input = np.array([[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]]]).astype(
          np.float32
      )
  
      input_size = 2
      hidden_size = 3
      weight_scale = 0.1
      number_of_gates = 4
  
      node = onnx.helper.make_node(
          "LSTM",
          inputs=["X", "W", "R"],
          outputs=["", "Y_h"],
          hidden_size=hidden_size,
      )
  
      W = weight_scale * np.ones(
          (1, number_of_gates * hidden_size, input_size)
      ).astype(np.float32)
      R = weight_scale * np.ones(
          (1, number_of_gates * hidden_size, hidden_size)
      ).astype(np.float32)
  
      lstm = LSTMHelper(X=input, W=W, R=R)
      _, Y_h = lstm.step()
      expect(
          node,
          inputs=[input, W, R],
          outputs=[Y_h.astype(np.float32)],
          name="test_lstm_defaults",
      )
  
file_path: onnx/onnx/backend/test/case/node/lstm.py
imports: from typing import Any, Tuple
  import numpy
  import onnx
  from onnx.backend.test.case.base import Base
  from onnx.backend.test.case.node import expect
label_desc: Use image node_id 1 for calling the LSTM obj's underlying member method code with example usage: obj.export_defaults() without return types