code: def test_scipy_svd(
      dtype_and_x,
      full_matrices,
      compute_uv,
      frontend,
      test_flags,
      fn_tree,
      backend_fw,
      on_device,
  ):
      dtype, x = dtype_and_x
      x = x[0]
      x = (
          np.matmul(x.T, x) + np.identity(x.shape[0]) * 1e-3
      )  # make symmetric positive-definite
      ret, ret_gt = helpers.test_frontend_function(
          input_dtypes=dtype,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          test_values=False,
          fn_tree=fn_tree,
          on_device=on_device,
          a=x,
          full_matrices=full_matrices,
          compute_uv=compute_uv,
      )
      with BackendHandler.update_backend(backend_fw) as ivy_backend:
          for u, v in zip(ret, ret_gt):
              u = ivy_backend.to_numpy(ivy_backend.abs(u))
              v = ivy_backend.to_numpy(ivy_backend.abs(v))
              helpers.value_test(
                  ret_np_flat=u,
                  ret_np_from_gt_flat=v,
                  rtol=1e-04,
                  atol=1e-04,
                  backend=backend_fw,
                  ground_truth_backend=frontend,
              )
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_scipy/test_linalg/test_linalg.py
imports: import sys
  from hypothesis import strategies
  import numpy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test, BackendHandler
label_desc: Use image node_id 9 for calling a global function with example usage: test_scipy_svd(dtype_and_x, full_matrices, compute_uv, frontend, test_flags, fn_tree, backend_fw, on_device) without return types