code: def test_batch_flatten():
      def verify_test_batch_flatten(d_shape):
          data = relay.var("data", relay.TensorType(d_shape, "float32"))
          func = relay.Function([data], relay.nn.batch_flatten(data))
          x_data = np.random.uniform(size=d_shape).astype("float32")
          verify_results(
              func, [x_data], "test_batch_flatten", rtol=1e-5, atol=1e-5
          )
  
      verify_test_batch_flatten((1, 2, 3, 4))
      verify_test_batch_flatten((1, 8))
  
imports: import pytest
  import numpy
  import onnxruntime
  import tvm
  from tvm import relay
  from tvm.contrib.target.onnx import to_onnx
  from tvm.relay.testing import run_infer_type
label_desc: Use image node_id 13 for calling a global function with example usage: test_batch_flatten() without return types