code: def test_tensorflow_linalg_einsum(
      *,
      eq_n_op_n_shp,
      dtype,
      on_device,
      fn_tree,
      backend_fw,
      frontend,
      test_flags,
  ):
      eq, operands, dtypes = eq_n_op_n_shp
      kw = {}
      for i, x_ in enumerate(operands):
          dtype = dtypes[i][0]
          kw[f"x{i}"] = np.array(x_).astype(dtype)
      test_flags.num_positional_args = len(operands) + 1
      helpers.test_frontend_function(
          input_dtypes=dtypes,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          equation=eq,
          **kw,
      )
  
imports: import numpy
  from hypothesis import assume, strategies
  import sys
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test, assert_all_close
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _get_dtype_value1_value2_axis_for_tensordot
  from ivy_tests.test_ivy.helpers.hypothesis_helpers.general_helpers import matrix_is_stable
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _matrix_rank_helper
label_desc: Use image node_id 23 for calling a global function with example usage: test_tensorflow_linalg_einsum() without return types