code: def _get_dtype_input_and_vectors(draw):
      dim_size = draw(helpers.ints(min_value=1, max_value=2))
      dtype = draw(helpers.get_dtypes("float"))
      if dim_size == 1:
          vec1 = draw(
              helpers.array_values(
                  dtype=dtype[0],
                  shape=(dim_size,),
                  min_value=2,
                  max_value=5,
              )
          )
          vec2 = draw(
              helpers.array_values(
                  dtype=dtype[0],
                  shape=(dim_size,),
                  min_value=2,
                  max_value=5,
              )
          )
      else:
          vec1 = draw(
              helpers.array_values(
                  dtype=dtype[0],
                  shape=(dim_size, dim_size),
                  min_value=2,
                  max_value=5,
              )
          )
          vec2 = draw(
              helpers.array_values(
                  dtype=dtype[0],
                  shape=(dim_size, dim_size),
                  min_value=2,
                  max_value=5,
              )
          )
      return dtype, vec1, vec2
  
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 4 for calling a global function with example usage: _get_dtype_input_and_vectors(draw) and returns: dtype,  vec1,  vec2