Add native support for v2 config (#3466)

nni/__main__.py

@@ -7,7 +7,7 @@ import logging
 import json
 import base64
 
-from .runtime.common import enable_multi_thread, enable_multi_phase
+from .runtime.common import enable_multi_thread
 from .runtime.msg_dispatcher import MsgDispatcher
 from .tools.package_utils import create_builtin_class_instance, create_customized_class_instance
 
@@ -29,10 +29,8 @@ def main():
     exp_params = json.loads(exp_params_decode)
     logger.debug('exp_params json obj: [%s]', json.dumps(exp_params, indent=4))
 
-    if exp_params.get('multiThread'):
+    if exp_params.get('deprecated', {}).get('multiThread'):
         enable_multi_thread()
-    if exp_params.get('multiPhase'):
-        enable_multi_phase()
 
     if exp_params.get('advisor') is not None:
         # advisor is enabled and starts to run
@@ -61,10 +59,10 @@ def main():
 
 
 def _run_advisor(exp_params):
-    if exp_params.get('advisor').get('builtinAdvisorName'):
+    if exp_params.get('advisor').get('name'):
         dispatcher = create_builtin_class_instance(
-            exp_params.get('advisor').get('builtinAdvisorName'),
-            exp_params.get('advisor').get('classArgs'),
+            exp_params['advisor']['name'],
+            exp_params['advisor'].get('classArgs'),
             'advisors')
     else:
         dispatcher = create_customized_class_instance(exp_params.get('advisor'))
@@ -78,26 +76,26 @@ def _run_advisor(exp_params):
 
 
 def _create_tuner(exp_params):
-    if exp_params.get('tuner').get('builtinTunerName'):
+    if exp_params['tuner'].get('name'):
         tuner = create_builtin_class_instance(
-            exp_params.get('tuner').get('builtinTunerName'),
-            exp_params.get('tuner').get('classArgs'),
+            exp_params['tuner']['name'],
+            exp_params['tuner'].get('classArgs'),
             'tuners')
     else:
-        tuner = create_customized_class_instance(exp_params.get('tuner'))
+        tuner = create_customized_class_instance(exp_params['tuner'])
     if tuner is None:
         raise AssertionError('Failed to create Tuner instance')
     return tuner
 
 
 def _create_assessor(exp_params):
-    if exp_params.get('assessor').get('builtinAssessorName'):
+    if exp_params['assessor'].get('name'):
         assessor = create_builtin_class_instance(
-            exp_params.get('assessor').get('builtinAssessorName'),
-            exp_params.get('assessor').get('classArgs'),
+            exp_params['assessor']['name'],
+            exp_params['assessor'].get('classArgs'),
             'assessors')
     else:
-        assessor = create_customized_class_instance(exp_params.get('assessor'))
+        assessor = create_customized_class_instance(exp_params['assessor'])
     if assessor is None:
         raise AssertionError('Failed to create Assessor instance')
     return assessor

nni/experiment/config/__init__.py

@@ -9,3 +9,4 @@ from .aml import *
 from .kubeflow import *
 from .frameworkcontroller import *
 from .adl import *
+from .shared_storage import *

nni/experiment/config/base.py

@@ -101,6 +101,8 @@ class ConfigBase:
             elif isinstance(value, ConfigBase):
                 setattr(ret, key, value.canonical())
                 # value will be copied twice, should not be a performance issue anyway
+            elif isinstance(value, Path):
+                setattr(ret, key, str(value))
         return ret
 
     def validate(self) -> None:

nni/experiment/config/common.py

@@ -5,6 +5,8 @@ from dataclasses import dataclass
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Union
 
+from ruamel.yaml import YAML
+
 from .base import ConfigBase, PathLike
 from . import util
 
@@ -27,23 +29,27 @@ class _AlgorithmConfig(ConfigBase):
         super().validate()
         _validate_algo(self)
 
-
 @dataclass(init=False)
 class AlgorithmConfig(_AlgorithmConfig):
     name: str
     class_args: Optional[Dict[str, Any]] = None
 
-
 @dataclass(init=False)
 class CustomAlgorithmConfig(_AlgorithmConfig):
     class_name: str
-    class_directory: Optional[PathLike] = None
+    class_directory: Optional[PathLike] = '.'
     class_args: Optional[Dict[str, Any]] = None
 
 
 class TrainingServiceConfig(ConfigBase):
     platform: str
 
+class SharedStorageConfig(ConfigBase):
+    storage_type: str
+    local_mount_point: str
+    remote_mount_point: str
+    local_mounted: str
+
 
 @dataclass(init=False)
 class ExperimentConfig(ConfigBase):
@@ -53,19 +59,21 @@ class ExperimentConfig(ConfigBase):
     trial_command: str
     trial_code_directory: PathLike = '.'
     trial_concurrency: int
-    trial_gpu_number: Optional[int] = None
+    trial_gpu_number: Optional[int] = None  # TODO: in openpai cannot be None
     max_experiment_duration: Optional[str] = None
     max_trial_number: Optional[int] = None
     nni_manager_ip: Optional[str] = None
     use_annotation: bool = False
     debug: bool = False
     log_level: Optional[str] = None
-    experiment_working_directory: Optional[PathLike] = None
+    experiment_working_directory: PathLike = '~/nni-experiments'
     tuner_gpu_indices: Optional[Union[List[int], str]] = None
     tuner: Optional[_AlgorithmConfig] = None
     assessor: Optional[_AlgorithmConfig] = None
     advisor: Optional[_AlgorithmConfig] = None
     training_service: Union[TrainingServiceConfig, List[TrainingServiceConfig]]
+    shared_storage: Optional[SharedStorageConfig] = None
+    _deprecated: Optional[Dict[str, Any]] = None
 
     def __init__(self, training_service_platform: Optional[Union[str, List[str]]] = None, **kwargs):
         base_path = kwargs.pop('_base_path', None)
@@ -100,6 +108,12 @@ class ExperimentConfig(ConfigBase):
             if self.training_service.use_active_gpu is None:
                 raise ValueError('Please set "use_active_gpu"')
 
+    def json(self) -> Dict[str, Any]:
+        obj = super().json()
+        if obj.get('searchSpaceFile'):
+            obj['searchSpace'] = YAML().load(open(obj.pop('searchSpaceFile')))
+        return obj
+
 ## End of public API ##
 
     @property
@@ -117,9 +131,9 @@ _canonical_rules = {
     'max_experiment_duration': lambda value: f'{util.parse_time(value)}s' if value is not None else None,
     'experiment_working_directory': util.canonical_path,
     'tuner_gpu_indices': lambda value: [int(idx) for idx in value.split(',')] if isinstance(value, str) else value,
-    'tuner': lambda config: None if config is None or config.name == '_none_' else config,
-    'assessor': lambda config: None if config is None or config.name == '_none_' else config,
-    'advisor': lambda config: None if config is None or config.name == '_none_' else config,
+    'tuner': lambda config: None if config is None or config.name == '_none_' else config.canonical(),
+    'assessor': lambda config: None if config is None or config.name == '_none_' else config.canonical(),
+    'advisor': lambda config: None if config is None or config.name == '_none_' else config.canonical(),
 }
 
 _validation_rules = {

nni/experiment/config/kubeflow.py

@@ -56,7 +56,7 @@ class KubeflowConfig(TrainingServiceConfig):
     parameter_server: Optional[KubeflowRoleConfig] = None
 
     def __init__(self, **kwargs):
-        kwargs = util.case_insensitve(kwargs)
+        kwargs = util.case_insensitive(kwargs)
         kwargs['storage'] = util.load_config(_KubeflowStorageConfig, kwargs.get('storage'))
         kwargs['worker'] = util.load_config(KubeflowRoleConfig, kwargs.get('worker'))
         kwargs['parameterserver'] = util.load_config(KubeflowRoleConfig, kwargs.get('parameterserver'))

nni/experiment/config/openpai.py

@@ -23,7 +23,7 @@ class OpenpaiConfig(TrainingServiceConfig):
     docker_image: str = 'msranni/nni:latest'
     local_storage_mount_point: PathLike
     container_storage_mount_point: str
-    reuse_mode: bool = False
+    reuse_mode: bool = True
 
     openpai_config: Optional[Dict[str, Any]] = None
     openpai_config_file: Optional[PathLike] = None

nni/experiment/config/remote.py

@@ -46,7 +46,7 @@ class RemoteMachineConfig(ConfigBase):
 @dataclass(init=False)
 class RemoteConfig(TrainingServiceConfig):
     platform: str = 'remote'
-    reuse_mode: bool = False
+    reuse_mode: bool = True
     machine_list: List[RemoteMachineConfig]
 
     def __init__(self, **kwargs):

nni/experiment/config/shared_storage.py

+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT license.
+
+from dataclasses import dataclass
+from typing import Optional
+
+from .common import SharedStorageConfig
+
+__all__ = ['NfsConfig', 'AzureBlobConfig']
+
+@dataclass(init=False)
+class NfsConfig(SharedStorageConfig):
+    storage_type: str = 'NFS'
+    nfs_server: str
+    exported_directory: str
+
+@dataclass(init=False)
+class AzureBlobConfig(SharedStorageConfig):
+    storage_type: str = 'AzureBlob'
+    storage_account_name: str
+    storage_account_key: Optional[str] = None
+    resource_group_name: Optional[str] = None
+    container_name: str

nni/experiment/config/util.py

@@ -19,7 +19,7 @@ def case_insensitive(key_or_kwargs: Union[str, Dict[str, Any]]) -> Union[str, Di
         return {key.lower().replace('_', ''): value for key, value in key_or_kwargs.items()}
 
 def camel_case(key: str) -> str:
-    words = key.split('_')
+    words = key.strip('_').split('_')
     return words[0] + ''.join(word.title() for word in words[1:])
 
 def canonical_path(path: Optional[PathLike]) -> Optional[str]:

nni/experiment/launcher.py

+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT license.
+
 import contextlib
 import logging
 from pathlib import Path
@@ -13,7 +16,6 @@ import nni_node  # pylint: disable=import-error
 import nni.runtime.protocol
 
 from .config import ExperimentConfig
-from .config import convert
 from .pipe import Pipe
 from . import rest
 from ..tools.nnictl.config_utils import Experiments
@@ -40,7 +42,7 @@ def start_experiment(exp_id: str, config: ExperimentConfig, port: int, debug: bo
         _save_experiment_information(exp_id, port, start_time, platform,
                                      config.experiment_name, proc.pid, config.experiment_working_directory)
         _logger.info('Setting up...')
-        _init_experiment(config, port, debug)
+        rest.post(port, '/experiment', config.json())
         return proc
 
     except Exception as e:
@@ -75,7 +77,7 @@ def start_experiment_retiarii(exp_id: str, config: ExperimentConfig, port: int,
         _save_experiment_information(exp_id, port, start_time, platform,
                                      config.experiment_name, proc.pid, config.experiment_working_directory)
         _logger.info('Setting up...')
-        _init_experiment(config, port, debug)
+        rest.post(port, '/experiment', config.json())
         return proc, pipe
 
     except Exception as e:
@@ -145,12 +147,6 @@ def _check_rest_server(port: int, retry: int = 3) -> None:
     rest.get(port, '/check-status')
 
 
-def _init_experiment(config: ExperimentConfig, port: int, debug: bool) -> None:
-    for cluster_metadata in convert.to_cluster_metadata(config):
-        rest.put(port, '/experiment/cluster-metadata', cluster_metadata)
-    rest.post(port, '/experiment', convert.to_rest_json(config))
-
-
 def _save_experiment_information(experiment_id: str, port: int, start_time: int, platform: str, name: str, pid: int, logDir: str) -> None:
     experiments_config = Experiments()
     experiments_config.add_experiment(experiment_id, port, start_time, platform, name, pid=pid, logDir=logDir)

nni/tools/nnictl/algo_management.py

@@ -35,11 +35,17 @@ def verify_algo_import(meta):
 def algo_reg(args):
     meta_list = read_reg_meta_list(args.meta_path)
     for meta in meta_list:
-        if get_registered_algo_meta(meta['builtinName']) is not None:
-            print_error('builtinName {} already registered'.format(meta['builtinName']))
-            return
+        old = get_registered_algo_meta(meta['builtinName'])
+        if old is None:
+            verify_algo_import(meta)
+            save_algo_meta_data(meta)
+        elif old['source'] != 'nni':
             verify_algo_import(meta)
+            print_green(f'Updating exist algorithm')
+            remove_algo_meta_data(meta['builtinName'])
             save_algo_meta_data(meta)
+        else:
+            print_error(f'Cannot overwrite builtin algorithm')
         print_green('{} registered sucessfully!'.format(meta['builtinName']))
 
 def algo_unreg(args):

nni/tools/nnictl/launcher_utils.py

@@ -124,4 +124,5 @@ def validate_all_content(experiment_config, config_path):
 
     NNIConfigSchema().validate(experiment_config)
 
+    if 'maxExecDuration' in experiment_config:
         experiment_config['maxExecDuration'] = parse_time(experiment_config['maxExecDuration'])

nni/tools/package_utils/__init__.py

@@ -178,25 +178,24 @@ def create_customized_class_instance(class_params):
     ----------
     class_params: dict
         class_params should contains following keys:
-            codeDir: code directory
-            classFileName: python file name of the class
-            className: class name
+            codeDirectory: code directory
+            className: qualified class name
             classArgs (optional): kwargs pass to class constructor
+
     Returns: object
     -------
         Returns customized class instance.
     """
 
-    code_dir = class_params.get('codeDir')
-    class_filename = class_params.get('classFileName')
-    class_name = class_params.get('className')
+    code_dir = class_params.get('classDirectory')
+    qualified_class_name = class_params.get('className')
     class_args = class_params.get('classArgs')
 
-    if not os.path.isfile(os.path.join(code_dir, class_filename)):
-        raise ValueError('Class file not found: {}'.format(
-            os.path.join(code_dir, class_filename)))
+    if code_dir and not os.path.isdir(code_dir):
+        raise ValueError(f'Directory not found: {code_dir}')
+
     sys.path.append(code_dir)
-    module_name = os.path.splitext(class_filename)[0]
+    module_name, class_name = qualified_class_name.rsplit('.', 1)
     class_module = importlib.import_module(module_name)
     class_constructor = getattr(class_module, class_name)
 

test/config/pr_tests.yml

@@ -45,13 +45,6 @@ testCases:
 - name: multi-thread
   configFile: test/config/multi_thread/config.yml
 
-- name: multi-phase-batch
-  configFile: test/config/multi_phase/batch.yml
-  config:
-    # for batch tuner, maxTrialNum can not exceed length of search space
-    maxTrialNum: 2
-    trialConcurrency: 2
-
 #########################################################################
 # nni assessor test
 #########################################################################

ts/nni_manager/.eslintrc

@@ -30,7 +30,8 @@
                 "argsIgnorePattern": "^_"
             }
         ],
-        "@typescript-eslint/no-var-requires": 0
+        "@typescript-eslint/no-var-requires": 0,
+        "@typescript-eslint/no-non-null-assertion": 0
     },
     "ignorePatterns": [
         "node_modules/",

ts/nni_manager/common/experimentConfig.ts

+// Copyright (c) Microsoft Corporation.
+// Licensed under the MIT license.
+
+'use strict';
+
+import * as assert from 'assert';
+
+export interface TrainingServiceConfig {
+    platform: string;
+}
+
+/* Local */
+
+export interface LocalConfig extends TrainingServiceConfig {
+    platform: 'local';
+    useActiveGpu?: boolean;
+    maxTrialNumberPerGpu: number;
+    gpuIndices?: number[];
+}
+
+/* Remote */
+
+export interface RemoteMachineConfig {
+    host: string;
+    port: number;
+    user: string;
+    password?: string;
+    sshKeyFile: string;
+    sshPassphrase?: string;
+    useActiveGpu: boolean;
+    maxTrialNumberPerGpu: number;
+    gpuIndices?: number[];
+    pythonPath?: string;
+}
+
+export interface RemoteConfig extends TrainingServiceConfig {
+    platform: 'remote';
+    reuseMode: boolean;
+    machineList: RemoteMachineConfig[];
+}
+
+/* OpenPAI */
+
+export interface OpenpaiConfig extends TrainingServiceConfig {
+    platform: 'openpai';
+    host: string;
+    username: string;
+    token: string;
+    trialCpuNumber: number;
+    trialMemorySize: string;
+    storageConfigName: string;
+    dockerImage: string;
+    localStorageMountPoint: string;
+    containerStorageMountPoint: string;
+    reuseMode: boolean;
+    openpaiConfig?: object;
+}
+
+/* AML */
+
+export interface AmlConfig extends TrainingServiceConfig {
+    platform: 'aml';
+    subscriptionId: string;
+    resourceGroup: string;
+    workspaceName: string;
+    computeTarget: string;
+    dockerImage: string;
+}
+
+/* Kubeflow */
+
+// FIXME: merge with shared storage config
+export interface KubeflowStorageConfig {
+    storage: string;
+    server?: string;
+    path?: string;
+    azureAccount?: string;
+    azureShare?: string;
+    keyVault?: string;
+    keyVaultSecret?: string;
+}
+
+export interface KubeflowRoleConfig {
+    replicas: number;
+    command: string;
+    gpuNumber: number;
+    cpuNumber: number;
+    memorySize: string;
+    dockerImage: string;
+}
+
+export interface KubeflowConfig extends TrainingServiceConfig {
+    platform: 'kubeflow';
+    operator: string;
+    apiVersion: string;
+    storage: KubeflowStorageConfig;
+    worker: KubeflowRoleConfig;
+    parameterServer?: KubeflowRoleConfig;
+}
+
+/* FrameworkController */
+
+type FrameworkControllerStorageConfig = KubeflowStorageConfig;
+
+export interface FrameworkControllerRoleConfig {
+    name: string;
+    dockerImage: string;
+    taskNumber: number;
+    command: string;
+    gpuNumber: number;
+    cpuNumber: number;
+    memorySize: string;
+    attemptCompletionMinFailedTasks: number;
+    attemptCompletionMinSucceededTasks: number;
+}
+
+export interface FrameworkControllerConfig extends TrainingServiceConfig {
+    platform: 'frameworkcontroller';
+    serviceAccountName: string;
+    storage: FrameworkControllerStorageConfig;
+    taskRoles: FrameworkControllerRoleConfig[];
+}
+
+/* shared storage */
+
+export interface SharedStorageConfig {
+    storageType: string;
+    localMountPoint: string;
+    remoteMountPoint: string;
+    localMounted: string;
+}
+
+export interface NfsConfig extends SharedStorageConfig {
+    storageType: 'NFS';
+    nfsServer: string;
+    exportedDirectory: string;
+}
+
+export interface AzureBlobConfig extends SharedStorageConfig {
+    storageAccountName: string;
+    storageAccountKey?: string;
+    resourceGroupName?: string;
+    containerName: string;
+}
+
+/* common */
+
+export interface AlgorithmConfig {
+    name?: string;
+    className?: string;
+    codeDirectory?: string;
+    classArgs?: object;
+}
+
+export interface ExperimentConfig {
+    experimentName?: string;
+    searchSpace: any;
+    trialCommand: string;
+    trialCodeDirectory: string;
+    trialConcurrency: number;
+    trialGpuNumber?: number;
+    maxExperimentDuration?: string;
+    maxTrialNumber?: number;
+    nniManagerIp?: string;
+    //useAnnotation: boolean;  // dealed inside nnictl
+    debug: boolean;
+    logLevel?: string;
+    experimentWorkingDirectory?: string;
+    tunerGpuIndices?: number[];
+    tuner?: AlgorithmConfig;
+    assessor?: AlgorithmConfig;
+    advisor?: AlgorithmConfig;
+    trainingService: TrainingServiceConfig | TrainingServiceConfig[];
+    sharedStorage?: SharedStorageConfig;
+    deprecated?: any;  // configs that are not yet natively supported by v2 (workaround)
+}
+
+/* util functions */
+
+const timeUnits = { d: 24 * 3600, h: 3600, m: 60, s: 1 };
+
+export function toSeconds(time: string): number {
+    for (const [unit, factor] of Object.entries(timeUnits)) {
+        if (time.toLowerCase().endsWith(unit)) {
+            const digits = time.slice(0, -1);
+            return Number(digits) * factor;
+        }
+    }
+    throw new Error(`Bad time string "${time}"`);
+}
+
+const sizeUnits = { tb: 1024 * 1024, gb: 1024 * 1024, mb: 1, kb: 1 / 1024 };
+
+export function toMegaBytes(size: string): number {
+    for (const [unit, factor] of Object.entries(sizeUnits)) {
+        if (size.toLowerCase().endsWith(unit)) {
+            const digits = size.slice(0, -2);
+            return Math.floor(Number(digits) * factor);
+        }
+    }
+    throw new Error(`Bad size string "${size}"`);
+}
+
+export function toCudaVisibleDevices(gpuIndices?: number[]): string {
+    return gpuIndices === undefined ? '' : gpuIndices.join(',');
+}
+
+export function flattenConfig<T>(config: ExperimentConfig, platform: string): T {
+    const flattened = { };
+    Object.assign(flattened, config);
+    if (Array.isArray(config.trainingService)) {
+        for (const trainingService of config.trainingService) {
+            if (trainingService.platform === platform) {
+                Object.assign(flattened, trainingService);
+            }
+        }
+    } else {
+        assert(config.trainingService.platform === platform);
+        Object.assign(flattened, config.trainingService);
+    }
+    return <T>flattened;
+}

ts/nni_manager/common/log.ts

@@ -17,8 +17,14 @@ const INFO: number = 4;
 const DEBUG: number = 5;
 const TRACE: number = 6;
 
-const logLevelNameMap: Map<string, number> = new Map([['fatal', FATAL],
-    ['error', ERROR], ['warning', WARNING], ['info', INFO], ['debug', DEBUG], ['trace', TRACE]]);
+const logLevelNameMap: Map<string, number> = new Map([
+    ['fatal', FATAL],
+    ['error', ERROR],
+    ['warning', WARNING],
+    ['info', INFO],
+    ['debug', DEBUG],
+    ['trace', TRACE]
+]);
 
 class BufferSerialEmitter {
     private buffer: Buffer;

ts/nni_manager/common/manager.ts

@@ -5,6 +5,7 @@
 
 import { MetricDataRecord, MetricType, TrialJobInfo } from './datastore';
 import { TrialJobStatus, LogType } from './trainingService';
+import { ExperimentConfig } from './experimentConfig';
 
 type ProfileUpdateType = 'TRIAL_CONCURRENCY' | 'MAX_EXEC_DURATION' | 'SEARCH_SPACE' | 'MAX_TRIAL_NUM';
 type ExperimentStatus = 'INITIALIZED' | 'RUNNING' | 'ERROR' | 'STOPPING' | 'STOPPED' | 'DONE' | 'NO_MORE_TRIAL' | 'TUNER_NO_MORE_TRIAL';
@@ -13,58 +14,12 @@ namespace ExperimentStartUpMode {
     export const RESUME = 'resume';
 }
 
-interface ExperimentParams {
-    authorName: string;
-    experimentName: string;
-    description?: string;
-    trialConcurrency: number;
-    maxExecDuration: number; //seconds
-    maxTrialNum: number;
-    searchSpace: string;
-    trainingServicePlatform: string;
-    multiPhase?: boolean;
-    multiThread?: boolean;
-    versionCheck?: boolean;
-    logCollection?: string;
-    tuner?: {
-        className?: string;
-        builtinTunerName?: string;
-        codeDir?: string;
-        classArgs?: any;
-        classFileName?: string;
-        checkpointDir: string;
-        includeIntermediateResults?: boolean;
-        gpuIndices?: string;
-    };
-    assessor?: {
-        className?: string;
-        builtinAssessorName?: string;
-        codeDir?: string;
-        classArgs?: any;
-        classFileName?: string;
-        checkpointDir: string;
-    };
-    advisor?: {
-        className?: string;
-        builtinAdvisorName?: string;
-        codeDir?: string;
-        classArgs?: any;
-        classFileName?: string;
-        checkpointDir: string;
-        gpuIndices?: string;
-    };
-    clusterMetaData?: {
-        key: string;
-        value: string;
-    }[];
-}
-
 interface ExperimentProfile {
-    params: ExperimentParams;
+    params: ExperimentConfig;
     id: string;
     execDuration: number;
-    logDir?: string;
-    startTime?: number;
+    logDir: string;
+    startTime: number;
     endTime?: number;
     nextSequenceId: number;
     revision: number;
@@ -81,7 +36,7 @@ interface NNIManagerStatus {
 }
 
 abstract class Manager {
-    public abstract startExperiment(experimentParams: ExperimentParams): Promise<string>;
+    public abstract startExperiment(experimentConfig: ExperimentConfig): Promise<string>;
     public abstract resumeExperiment(readonly: boolean): Promise<void>;
     public abstract stopExperiment(): Promise<void>;
     public abstract stopExperimentTopHalf(): Promise<void>;
@@ -113,4 +68,4 @@ abstract class Manager {
     public abstract fetchTrialOutput(trialJobId: string, subpath: string): Promise<void>;
 }
 
-export { Manager, ExperimentParams, ExperimentProfile, TrialJobStatistics, ProfileUpdateType, NNIManagerStatus, ExperimentStatus, ExperimentStartUpMode };
+export { Manager, ExperimentConfig, ExperimentProfile, TrialJobStatistics, ProfileUpdateType, NNIManagerStatus, ExperimentStatus, ExperimentStartUpMode };