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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def load_model(location):
 """ Load any Turi Create model that was previously saved. This function assumes the model (can be any model) was previously saved in Turi Create model format with model.save(filename). Parameters location : string Location of the model to load. Can be a local path or a remote URL. Because models are saved as directories, there is no file extension. Examples """


    # Check if the location is a dir_archive, if not, use glunpickler to load
    # as pure python model
    # If the location is a http location, skip the check, and directly proceed
    # to load model as dir_archive. This is because
    # 1) exists() does not work with http protocol, and
    # 2) GLUnpickler does not support http
    protocol = file_util.get_protocol(location)
    dir_archive_exists = False
    if protocol == '':
        model_path = file_util.expand_full_path(location)
        dir_archive_exists = file_util.exists(os.path.join(model_path, 'dir_archive.ini'))
    else:
        model_path = location
        if protocol in ['http', 'https']:
            dir_archive_exists = True
        else:
            import posixpath
            dir_archive_exists = file_util.exists(posixpath.join(model_path, 'dir_archive.ini'))
    if not dir_archive_exists:
        raise IOError("Directory %s does not exist" % location)

    _internal_url = _make_internal_url(location)
    saved_state = glconnect.get_unity().load_model(_internal_url)
    saved_state = _wrap_function_return(saved_state)
    # The archive version could be both bytes/unicode
    key = u'archive_version'
    archive_version = saved_state[key] if key in saved_state else saved_state[key.encode()]
    if archive_version < 0:
        raise ToolkitError("File does not appear to be a Turi Create model.")
    elif archive_version > 1:
        raise ToolkitError("Unable to load model.\n\n"
                           "This model looks to have been saved with a future version of Turi Create.\n"
                           "Please upgrade Turi Create before attempting to load this model file.")
    elif archive_version == 1:
        name = saved_state['model_name'];
        if name in MODEL_NAME_MAP: 
            cls = MODEL_NAME_MAP[name]

            if 'model' in saved_state:
                # this is a native model
                return cls(saved_state['model'])
            else:
                # this is a CustomModel
                model_data = saved_state['side_data']
                model_version = model_data['model_version']
                del model_data['model_version']
                return cls._load_version(model_data, model_version)

        elif hasattr(_extensions, name):
            return saved_state["model"]
        else:
            raise ToolkitError("Unable to load model of name '%s'; model name not registered." % name)
    else:
        # very legacy model format. Attempt pickle loading
        import sys
        sys.stderr.write("This model was saved in a legacy model format. Compatibility cannot be guaranteed in future versions.\n")
        if _six.PY3:
            raise ToolkitError("Unable to load legacy model in Python 3.\n\n"
                               "To migrate a model, try loading it using Turi Create 4.0 or\n"
                               "later in Python 2 and then re-save it. The re-saved model should\n"
                               "work in Python 3.")

        if 'graphlab' not in sys.modules:
            sys.modules['graphlab'] = sys.modules['turicreate']
            # backward compatibility. Otherwise old pickles will not load
            sys.modules["turicreate_util"] = sys.modules['turicreate.util']
            sys.modules["graphlab_util"] = sys.modules['turicreate.util']

            # More backwards compatibility with the turicreate namespace code.
            for k, v in list(sys.modules.items()):
                if 'turicreate' in k:
                    sys.modules[k.replace('turicreate', 'graphlab')] = v
        #legacy loader
        import pickle
        model_wrapper = pickle.loads(saved_state[b'model_wrapper'])
        return model_wrapper(saved_state[b'model_base'])