code: def export_training_default_zero_ratio_mask() -> None:
      seed = np.int64(0)
      node = onnx.helper.make_node(
          "Dropout",
          inputs=["x", "r", "t"],
          outputs=["y", "z"],
          seed=seed,
      )
  
      x = np.random.randn(3, 4, 5).astype(np.float32)
      r = np.float32(0.0)
      t = np.bool_(True)
      y, z = dropout(x, r, training_mode=t, return_mask=True)
      expect(
          node,
          inputs=[x, r, t],
          outputs=[y, z],
          name="test_training_dropout_zero_ratio_mask",
      )
  
file_path: onnx/onnx/backend/test/case/node/dropout.py
imports: import numpy
  import onnx
  from onnx import helper
  from onnx.backend.test.case.base import Base
  from onnx.backend.test.case.node import expect
label_desc: Use image node_id 10 for calling the Dropout obj's underlying member method code with example usage: obj.export_training_default_zero_ratio_mask() without return types