code: def export_and_broadcast() -> None:
      node = onnx.helper.make_node(
          "And",
          inputs=["x", "y"],
          outputs=["and"],
      )
  
      # 3d vs 1d
      x = (np.random.randn(3, 4, 5) > 0).astype(bool)
      y = (np.random.randn(5) > 0).astype(bool)
      z = np.logical_and(x, y)
      expect(
          node, inputs=[x, y], outputs=[z], name="test_and_bcast3v1d"
      )
  
      # 3d vs 2d
      x = (np.random.randn(3, 4, 5) > 0).astype(bool)
      y = (np.random.randn(4, 5) > 0).astype(bool)
      z = np.logical_and(x, y)
      expect(
          node, inputs=[x, y], outputs=[z], name="test_and_bcast3v2d"
      )
  
      # 4d vs 2d
      x = (np.random.randn(3, 4, 5, 6) > 0).astype(bool)
      y = (np.random.randn(5, 6) > 0).astype(bool)
      z = np.logical_and(x, y)
      expect(
          node, inputs=[x, y], outputs=[z], name="test_and_bcast4v2d"
      )
  
      # 4d vs 3d
      x = (np.random.randn(3, 4, 5, 6) > 0).astype(bool)
      y = (np.random.randn(4, 5, 6) > 0).astype(bool)
      z = np.logical_and(x, y)
      expect(
          node, inputs=[x, y], outputs=[z], name="test_and_bcast4v3d"
      )
  
      # 4d vs 4d
      x = (np.random.randn(1, 4, 1, 6) > 0).astype(bool)
      y = (np.random.randn(3, 1, 5, 6) > 0).astype(bool)
      z = np.logical_and(x, y)
      expect(
          node, inputs=[x, y], outputs=[z], name="test_and_bcast4v4d"
      )
  
file_path: onnx/onnx/backend/test/case/node/and.py
imports: 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 2 for calling the And obj's underlying member method code with example usage: obj.export_and_broadcast() without return types