code: def _get_paddle_cholesky_matrix(draw):
      input_dtype, spd_chol = draw(_get_cholesky_matrix())
      probability = draw(st.floats(min_value=0, max_value=1))
      if probability > 0.5:
          spd_chol = spd_chol.T  # randomly transpose the matrix
      return input_dtype, spd_chol
  
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 5 for calling a global function with example usage: _get_paddle_cholesky_matrix(draw) and returns: input_dtype,  spd_chol