code: def handle_method(
      *,
      init_tree: str = "",
      method_tree: Optional[str] = None,
      ground_truth_backend: str = "tensorflow",
      test_gradients=BuiltGradientStrategy,
      test_trace=BuiltTraceStrategy,
      precision_mode=BuiltPrecisionModeStrategy,
      init_num_positional_args=None,
      init_native_arrays=BuiltNativeArrayStrategy,
      init_as_variable_flags=BuiltAsVariableStrategy,
      method_num_positional_args=None,
      method_native_arrays=BuiltNativeArrayStrategy,
      method_as_variable_flags=BuiltAsVariableStrategy,
      method_container_flags=BuiltContainerStrategy,
      **_given_kwargs,
  ):
      """Test wrapper for Ivy methods.
  
      The wrapper sets the required test globals and creates test flags strategies.
  
      Parameters
      ----------
      method_tree
          Full method import path
  
      ground_truth_backend
          The framework to assert test results are equal to
      """
      # need to fill up the docstring
      is_method_tree_provided = method_tree is not None
      if is_method_tree_provided:
          method_tree = f"ivy.{method_tree}"
      is_hypothesis_test = len(_given_kwargs) != 0
      possible_arguments = {
          "ground_truth_backend": st.just(ground_truth_backend),
          "test_gradients": _get_runtime_flag_value(test_gradients),
          "test_trace": _get_runtime_flag_value(test_trace),
          "precision_mode": _get_runtime_flag_value(precision_mode),
      }
  
      if is_hypothesis_test and is_method_tree_provided:
          (
              callable_method,
              method_name,
              _,
              class_name,
              method_mod,
          ) = _import_method(method_tree)
  
          if init_num_positional_args is None:
              init_num_positional_args = num_positional_args(
                  fn_name=init_tree
              )
  
          possible_arguments["init_flags"] = pf.init_method_flags(
              num_positional_args=init_num_positional_args,
              as_variable=_get_runtime_flag_value(
                  init_as_variable_flags
              ),
              native_arrays=_get_runtime_flag_value(init_native_arrays),
              precision_mode=_get_runtime_flag_value(precision_mode),
          )
  
          if method_num_positional_args is None:
              method_num_positional_args = num_positional_args_method(
                  method=callable_method
              )
  
          possible_arguments["method_flags"] = pf.method_flags(
              num_positional_args=method_num_positional_args,
              as_variable=_get_runtime_flag_value(
                  method_as_variable_flags
              ),
              native_arrays=_get_runtime_flag_value(
                  method_native_arrays
              ),
              container_flags=_get_runtime_flag_value(
                  method_container_flags
              ),
              precision_mode=_get_runtime_flag_value(precision_mode),
          )
  
      def test_wrapper(test_fn):
          if is_method_tree_provided:
              supported_device_dtypes = (
                  _get_method_supported_devices_dtypes(
                      method_name, method_mod, class_name
                  )
              )
              possible_arguments["class_name"] = st.just(class_name)
              possible_arguments["method_name"] = st.just(method_name)
  
          if is_hypothesis_test:
              param_names = inspect.signature(test_fn).parameters.keys()
              filtered_args = set(param_names).intersection(
                  possible_arguments.keys()
              )
  
              for key in filtered_args:
                  # extend Hypothesis given kwargs with our strategies
                  _given_kwargs[key] = possible_arguments[key]
  
              hypothesis_test_fn = given(**_given_kwargs)(test_fn)
  
              @functools.wraps(hypothesis_test_fn)
              def wrapped_test(*args, **kwargs):
                  try:
                      hypothesis_test_fn(*args, **kwargs)
                  except Exception as e:
                      # A string matching is used instead of actual exception due to
                      # exception object in with_backend is different from global Ivy
                      if (
                          e.__class__.__qualname__
                          == "IvyNotImplementedException"
                      ):
                          pytest.skip(
                              "Function not implemented in backend."
                          )
                      else:
                          raise e
  
          else:
              wrapped_test = test_fn
  
          wrapped_test.test_data = TestData(
              test_fn=wrapped_test,
              fn_tree=method_tree,
              fn_name=method_name,
              supported_device_dtypes=supported_device_dtypes,
              is_method=True,
          )
  
          wrapped_test.ground_truth_backend = ground_truth_backend
          wrapped_test._ivy_test = True
  
          return wrapped_test
  
      return test_wrapper
  
imports: import json
  import os
  import pytest
  import importlib
  import inspect
  import functools
  from typing import List, Optional
  from hypothesis import given, strategies
  import ivy.functional.frontends.numpy
  from .hypothesis_helpers import number_helpers
  from .globals import TestData
  from .None import test_parameter_flags
  from .None import test_globals
  from .pipeline_helper import BackendHandler
  from ivy_tests.test_ivy.helpers.test_parameter_flags import DynamicFlag, BuiltInstanceStrategy, BuiltAsVariableStrategy, BuiltNativeArrayStrategy, BuiltGradientStrategy, BuiltContainerStrategy, BuiltWithOutStrategy, BuiltWithCopyStrategy, BuiltInplaceStrategy, BuiltTraceStrategy, BuiltFrontendArrayStrategy, BuiltTranspileStrategy, BuiltPrecisionModeStrategy, BuiltCythonWrapperStrategy
  from ivy_tests.test_ivy.helpers.structs import FrontendMethodData
  from ivy_tests.test_ivy.helpers.available_frameworks import available_frameworks
  from ivy_tests.test_ivy.helpers.hypothesis_helpers.dtype_helpers import _dtype_kind_keys, _get_type_dict
  from .globals import mod_backend
label_desc: Use image node_id 14 for calling a global function with example usage: handle_method() and returns: test_wrapper, wrapped_test