code: def test_torch_tensordot(
      dtype_values_and_axes,
      test_flags,
      frontend,
      backend_fw,
      fn_tree,
  ):
      dtype, a, b, dims = dtype_values_and_axes
      if ivy.current_backend_str() == "paddle":
          # Paddle only supports ndim from 0 to 9
          assume(a.shape[0] < 10)
          assume(b.shape[0] < 10)
  
      helpers.test_frontend_function(
          input_dtypes=dtype,
          backend_to_test=backend_fw,
          test_flags=test_flags,
          frontend=frontend,
          fn_tree=fn_tree,
          a=a,
          b=b,
          rtol=1e-2,
          atol=1e-2,
          dims=dims,
      )
  
imports: import math
  import numpy
  from hypothesis import assume, strategies
  import hypothesis.extra.numpy
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _get_dtype_value1_value2_axis_for_tensordot
label_desc: Use image node_id 42 for calling a global function with example usage: test_torch_tensordot(dtype_values_and_axes, test_flags, frontend, backend_fw, fn_tree) without return types