code: def test_paddle_pinv(
      dtype_and_x,
      rcond,
      frontend,
      test_flags,
      fn_tree,
      backend_fw,
      on_device,
  ):
      # TODO: paddle returns nan for all values if the input
      # matrix has the same value at all indices e.g.
      # [[2., 2.], [2., 2.]] would return [[nan, nan], [nan, nan]],
      # causing the tests to fail for other backends.
      dtype, x = dtype_and_x
      helpers.test_frontend_function(
          input_dtypes=dtype,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          rtol=1e-3,
          atol=1e-3,
          x=x[0],
          rcond=rcond,
      )
  
imports: import ivy
  from hypothesis import strategies, assume
  import numpy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import assert_all_close
  from ivy_tests.test_ivy.helpers import handle_frontend_test, matrix_is_stable
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _get_dtype_and_matrix
  from ivy_tests.test_ivy.test_frontends.test_tensorflow.test_linalg import _get_second_matrix, _get_cholesky_matrix
  from ivy_tests.test_ivy.test_frontends.test_torch.test_blas_and_lapack_ops import _get_dtype_input_and_mat_vec
label_desc: Use image node_id 27 for calling a global function with example usage: test_paddle_pinv(dtype_and_x, rcond, frontend, test_flags, fn_tree, backend_fw, on_device) without return types