code: def test_torch_one_hot(
      *,
      num_classes_dtype_x_axis,
      frontend,
      fn_tree,
      test_flags,
      backend_fw,
      on_device,
  ):
      num_classes, values = num_classes_dtype_x_axis
      input_dtype, x = values
      test_flags.num_positional_args += 1
      helpers.test_frontend_function(
          input_dtypes=input_dtype,
          backend_to_test=backend_fw,
          test_flags=test_flags,
          frontend=frontend,
          fn_tree=fn_tree,
          on_device=on_device,
          tensor=x[0],
          num_classes=num_classes,
      )
  
imports: from hypothesis import strategies
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
label_desc: Use image node_id 3 for calling a global function with example usage: test_torch_one_hot() without return types