KaneAI - World’s First E2E Software Testing Agent.Book a Demo Join TestMu Conference

How to use apply_parameter_changes method in localstack

Best Python code snippet using localstack_python

template_deployer.py

Source:template_deployer.py

...1180            ssm_client = aws_stack.connect_to_service("ssm")1181            param = ssm_client.get_parameter(Name=default_value)1182            return param["Parameter"]["Value"]1183        return None1184    def apply_parameter_changes(self, old_stack, new_stack) -> None:1185        parameters = {1186            p["ParameterKey"]: p1187            for p in old_stack.metadata["Parameters"]  # go through current parameter values1188        }1189        for logical_id, value in new_stack.template["Parameters"].items():1190            default = value.get("Default")1191            provided_param_value = parameters.get(logical_id)1192            param = {1193                "ParameterKey": logical_id,1194                "ParameterValue": provided_param_value if default is None else default,1195            }1196            if default is not None:1197                resolved_value = self.resolve_param(logical_id, value.get("Type"), default)1198                if resolved_value is not None:1199                    param["ResolvedValue"] = resolved_value1200            parameters[logical_id] = param1201        parameters.update({p["ParameterKey"]: p for p in new_stack.metadata["Parameters"]})1202        for change_set in new_stack.change_sets:1203            parameters.update({p["ParameterKey"]: p for p in change_set.metadata["Parameters"]})1204        # TODO: unclear/undocumented behavior in implicitly updating old_stack parameter here1205        old_stack.metadata["Parameters"] = [v for v in parameters.values() if v]1206    # TODO: fix circular import with cloudformation_api.py when importing Stack here1207    def construct_changes(1208        self,1209        existing_stack,1210        new_stack,1211        initialize=False,1212        change_set_id=None,1213        append_to_changeset=False,1214    ):1215        from localstack.services.cloudformation.cloudformation_api import StackChangeSet1216        old_resources = existing_stack.template["Resources"]1217        new_resources = new_stack.template["Resources"]1218        deletes = [val for key, val in old_resources.items() if key not in new_resources]1219        adds = [val for key, val in new_resources.items() if initialize or key not in old_resources]1220        modifies = [val for key, val in new_resources.items() if key in old_resources]1221        changes = []1222        for action, items in (("Remove", deletes), ("Add", adds), ("Modify", modifies)):1223            for item in items:1224                item["Properties"] = item.get("Properties", {})1225                change = self.get_change_config(action, item, change_set_id=change_set_id)1226                changes.append(change)1227        # append changes to change set1228        if append_to_changeset and isinstance(new_stack, StackChangeSet):1229            new_stack.changes.extend(changes)1230        return changes1231    def apply_changes(1232        self,1233        existing_stack,1234        new_stack,1235        stack_name,1236        change_set_id=None,1237        initialize=False,1238        action=None,1239    ):1240        old_resources = existing_stack.template["Resources"]1241        new_resources = new_stack.template["Resources"]1242        action = action or "CREATE"1243        self.init_resource_status(old_resources, action="UPDATE")1244        # apply parameter changes to existing stack1245        self.apply_parameter_changes(existing_stack, new_stack)1246        # construct changes1247        changes = self.construct_changes(1248            existing_stack,1249            new_stack,1250            initialize=initialize,1251            change_set_id=change_set_id,1252        )1253        # check if we have actual changes in the stack, and prepare properties1254        contains_changes = False1255        for change in changes:1256            res_action = change["ResourceChange"]["Action"]1257            resource = new_resources.get(change["ResourceChange"]["LogicalResourceId"])1258            if res_action != "Modify" or self.resource_config_differs(resource):1259                contains_changes = True...

trainer.py

Source:trainer.py

...98                modified_arg += char99        tensorboard_comment += modified_arg100    #params["tb_comment"] = tensorboard_comment101    return tensorboard_comment102def apply_parameter_changes(parameters, env, verbose):103     # NN architectures:104    hidden_size = parameters["hidden_size"]105    # Save in the sense of enough non-linearities per block:106    save_feature_block = [{"name": "linear", "neurons": hidden_size, "act_func": "relu"},107                              {"name": "linear", "neurons": hidden_size}]108    save_hidden_block = [{"name": "linear", "neurons": hidden_size, "act_func": "relu"},109                             {"name": "linear", "neurons": hidden_size, "act_func": "relu"}]110    111    thin_block = [{"name": "linear", "neurons": hidden_size, "act_func": "relu"}]112    test_block = [{"name": "linear", "neurons": 64, "act_func": "relu"}]113    standard_hidden_block = thin_block114    standard_feature_block = thin_block115    layers_feature_vector = standard_hidden_block116    layers_feature_merge = standard_feature_block117    layers_action = standard_feature_block118    layers_state_action_merge = standard_feature_block119    layers_r = standard_hidden_block120    layers_Q = standard_hidden_block121    layers_V = standard_hidden_block122    layers_actor = standard_hidden_block123    mnhi_early = [{"name": "conv", "filters": 32, "kernel_size": 8, "stride": 4, "act_func": "relu"},124                       {"name": "conv", "filters": 64, "kernel_size": 4, "stride": 2, "act_func": "relu"},125                       {"name": "conv", "filters": 64, "kernel_size": 2, "stride": 1, "act_func": "relu"}126                       ]127    mnhi_later = [{"name": "conv", "filters": 32, "kernel_size": 8, "stride": 4, "act_func": "relu"},128                       {"name": "conv", "filters": 64, "kernel_size": 4, "stride": 2, "act_func": "relu"},129                       {"name": "conv", "filters": 64, "kernel_size": 3, "stride": 1, "act_func": "relu"}130                       ]131    vizdoom_winner = [{"name": "conv", "filters": 16, "kernel_size": 3, "stride": 2, "act_func": "relu"},132                        {"name": "conv", "filters": 32, "kernel_size": 3, "stride": 2, "act_func": "relu"},133                        {"name": "conv", "filters": 64, "kernel_size": 3, "stride": 2, "act_func": "relu"},134                        {"name": "conv", "filters": 128, "kernel_size": 3, "stride": 1, "act_func": "relu"},135                        {"name": "conv", "filters": 256, "kernel_size": 3, "stride": 1, "act_func": "relu"}136                      ]137    own_arch = [{"name": "conv", "filters": 16, "kernel_size": 3, "stride": 2, "act_func": "relu"},138                {"name": "conv", "filters": 32, "kernel_size": 3, "stride": 2, "act_func": "relu"},139                {"name": "conv", "filters": 64, "kernel_size": 3, "stride": 2, "act_func": "relu"},140                {"name": "conv", "filters": 128, "kernel_size": 3, "stride": 2, "act_func": "relu"},141                {"name": "conv", "filters": 256, "kernel_size": 3, "stride": 1, "act_func": "relu"}142                ]143    # TODO: define R2D2 conv architecture! (IMPALA uses the same)144    layers_conv = standard_hidden_block145    parameters.update({146        # NN architecture setup:147        "layers_feature_vector": layers_feature_vector, "layers_state_action_merge": layers_state_action_merge,148        "layers_action": layers_action,149        "layers_feature_merge": layers_feature_merge, "layers_r": layers_r, "layers_Q": layers_Q,150        "layers_V": layers_V,151        "layers_actor": layers_actor152    })153        154    #Convert strings in hyperparams to objects:155    # optimizer:156    if parameters["optimizer"] == "RAdam":157        parameters["optimizer"] = RAdam158    elif parameters["optimizer"] == "Adam":159        parameters["optimizer"] = torch.optim.Adam160    # Conv layers:161    if parameters["layers_conv"] == "mnhi_early":162        parameters["layers_conv"] = mnhi_early163    elif parameters["layers_conv"] == "mnhi_later":164        parameters["layers_conv"] = mnhi_later165    elif parameters["layers_conv"] == "vizdoom_winner":166        parameters["layers_conv"] = vizdoom_winner167    elif parameters["layers_conv"] == "own":168        parameters["layers_conv"] = own_arch169    atari_envs = ['adventure', 'airraid', 'alien', 'amidar', 'assault', 'asterix', 'asteroids', 'atlantis',170                    'bank_heist', 'battlezone', 'beam_rider', 'berzerk', 'bowling', 'boxing', 'breakout', 'carnival',171                    'centipede', 'choppercommand', 'crazyclimber', 'defender', 'demonattack', 'doubledunk',172                    'elevatoraction', 'enduro', 'fishingderby', 'freeway', 'frostbite', 'gopher', 'gravitar',173                    'hero', 'icehockey', 'jamesbond', 'journey_escape', 'kangaroo', 'krull', 'kungfumaster',174                    'montezuma_revenge', 'ms_pacman', 'namethisgame', 'phoenix', 'pitfall', 'pong', 'pooyan',175                    'private_eye', 'qbert', 'riverraid', 'road_runner', 'robotank', 'seaquest', 'skiing',176                    'solaris', 'spaceinvaders', 'stargunner', 'tennis', 'timepilot', 'tutankham', 'upndown',177                    'venture', 'videopinball', 'wizardofwor', 'yars_revenge', 'zaxxon']178    if "MineRL" in env:179        if verbose:180            print("MineRL env!")181        use_hierarchical_action_wrapper = True182        parameters["convert_2_torch_wrapper"] = Convert2TorchWrapper183        if use_hierarchical_action_wrapper:184            parameters["action_wrapper"] = HierarchicalActionWrapper185        else:186            parameters["action_wrapper"] = SerialDiscreteActionWrapper187        parameters["use_MineRL_policy"] = True188        #if "Pickaxe" in env or "Diamond" in env:189        #    params["use_MineRL_policy"] = True190    elif any([atari_env in env.lower() for atari_env in atari_envs]):191        parameters["convert_2_torch_wrapper"] = AtariObsWrapper192        if verbose:193            print("Atari env!")194    else:195        parameters["convert_2_torch_wrapper"] = DefaultWrapper196    return parameters197class Trainer:198    def __init__(self, env_name, **kwargs):199        # Set up hyperparameters:200        hyperparameters = get_default_hyperparameters()201        hyperparameters.update(kwargs)202        verbose = hyperparameters["verbose"]203        hyperparameters = apply_parameter_changes(hyperparameters, env_name, verbose)204        self.hyperparameters = hyperparameters205        206        # Create tensorboard experiment comment:207        self.tb_comment = create_comment(hyperparameters["tb_comment"], env_name, kwargs)208        if verbose:209            print("Tensorboard comment: ", self.tb_comment)210        211        # Init logging:212        self.path = os.getcwd()213        self.do_log = hyperparameters["log"]214        self.log = Log(self.path + '/tb_log', self.do_log, self.tb_comment)215        self.verbose = verbose216        217        # Set device...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.