Merge branch 'master' of git://github.com/microsoft/nni

examples/tuners/random_nas_tuner/random_nas_tuner.py

@@ -49,12 +49,12 @@ class RandomNASTuner(Tuner):
         self.searchspace_json = search_space
         self.random_state = np.random.RandomState()
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         '''generate
         '''
         return random_archi_generator(self.searchspace_json, self.random_state)
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         '''receive
         '''
         pass

examples/tuners/weight_sharing/ga_customer_tuner/customer_tuner.py

@@ -112,7 +112,7 @@ class CustomerTuner(Tuner):
             population.append(Individual(indiv_id=self.generate_new_id(), graph_cfg=graph_tmp, result=None))
         return population
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """Returns a set of trial graph config, as a serializable object.
         An example configuration:
         ```json
@@ -196,7 +196,7 @@ class CustomerTuner(Tuner):
         logger.debug("trial {} ready".format(indiv.indiv_id))
         return param_json
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         '''
         Record an observation of the objective function
         parameter_id : int

src/nni_manager/common/utils.ts

@@ -375,7 +375,7 @@ function countFilesRecursively(directory: string, timeoutMilliSeconds?: number):
 }
 
 function validateFileName(fileName: string): boolean {
-    let pattern: string = '^[a-z0-9A-Z\.-_]+$';
+    let pattern: string = '^[a-z0-9A-Z\._-]+$';
     const validateResult = fileName.match(pattern);
     if(validateResult) {
         return true;

src/nni_manager/rest_server/restValidationSchemas.ts

@@ -51,6 +51,7 @@ export namespace ValidationSchemas {
                 command: joi.string().min(1),
                 virtualCluster: joi.string(),
                 shmMB: joi.number(),
+                nasMode: joi.string().valid('classic_mode', 'enas_mode', 'oneshot_mode'),
                 worker: joi.object({
                     replicas: joi.number().min(1).required(),
                     image: joi.string().min(1),

src/nni_manager/training_service/common/clusterJobRestServer.ts

@@ -58,6 +58,10 @@ export abstract class ClusterJobRestServer extends RestServer {
         this.port = basePort + 1;
     }
 
+    get apiRootUrl(): string {
+        return this.API_ROOT_URL;
+    }
+
     public get clusterRestServerPort(): number {
         if (this.port === undefined) {
             throw new Error('PAI Rest server port is undefined');
@@ -87,7 +91,7 @@ export abstract class ClusterJobRestServer extends RestServer {
     protected abstract handleTrialMetrics(jobId : string, trialMetrics : any[]) : void;
 
     // tslint:disable: no-unsafe-any no-any
-    private createRestHandler() : Router {
+    protected createRestHandler() : Router {
         const router: Router = Router();
 
         router.use((req: Request, res: Response, next: any) => {

src/nni_manager/training_service/local/localTrainingService.ts

@@ -355,7 +355,8 @@ class LocalTrainingService implements TrainingService {
         this.log.info('Stopping local machine training service...');
         this.stopping = true;
         for (const stream of this.jobStreamMap.values()) {
-            stream.destroy();
+            stream.end(0)
+            stream.emit('end')
         }
         if (this.gpuScheduler !== undefined) {
             await this.gpuScheduler.stop();
@@ -372,7 +373,9 @@ class LocalTrainingService implements TrainingService {
                 if (stream === undefined) {
                     throw new Error(`Could not find stream in trial ${trialJob.id}`);
                 }
-                stream.destroy();
+                //Refer https://github.com/Juul/tail-stream/issues/20
+                stream.end(0)
+                stream.emit('end')
                 this.jobStreamMap.delete(trialJob.id);
             }
         }
@@ -567,7 +570,6 @@ class LocalTrainingService implements TrainingService {
                 buffer = remain;
             }
         });
-
         this.jobStreamMap.set(trialJobDetail.id, stream);
     }
 

src/nni_manager/training_service/pai/paiData.ts

@@ -64,11 +64,11 @@ else
 fi`;
 
 export const PAI_TRIAL_COMMAND_FORMAT: string =
-`export NNI_PLATFORM=pai NNI_SYS_DIR={0} NNI_OUTPUT_DIR={1} NNI_TRIAL_JOB_ID={2} NNI_EXP_ID={3} NNI_TRIAL_SEQ_ID={4} \
+`export NNI_PLATFORM=pai NNI_SYS_DIR={0} NNI_OUTPUT_DIR={1} NNI_TRIAL_JOB_ID={2} NNI_EXP_ID={3} NNI_TRIAL_SEQ_ID={4} MULTI_PHASE={5} \
 && cd $NNI_SYS_DIR && sh install_nni.sh \
-&& python3 -m nni_trial_tool.trial_keeper --trial_command '{5}' --nnimanager_ip '{6}' --nnimanager_port '{7}' \
---pai_hdfs_output_dir '{8}' --pai_hdfs_host '{9}' --pai_user_name {10} --nni_hdfs_exp_dir '{11}' --webhdfs_path '/webhdfs/api/v1' \
---nni_manager_version '{12}' --log_collection '{13}'`;
+&& python3 -m nni_trial_tool.trial_keeper --trial_command '{6}' --nnimanager_ip '{7}' --nnimanager_port '{8}' \
+--pai_hdfs_output_dir '{9}' --pai_hdfs_host '{10}' --pai_user_name {11} --nni_hdfs_exp_dir '{12}' --webhdfs_path '/webhdfs/api/v1' \
+--nni_manager_version '{13}' --log_collection '{14}'`;
 
 export const PAI_OUTPUT_DIR_FORMAT: string =
 `hdfs://{0}:9000/`;

src/nni_manager/training_service/pai/paiJobRestServer.ts

@@ -19,17 +19,26 @@
 
 'use strict';
 
+import { Request, Response, Router } from 'express';
 import { Inject } from 'typescript-ioc';
 import * as component from '../../common/component';
 import { ClusterJobRestServer } from '../common/clusterJobRestServer';
 import { PAITrainingService } from './paiTrainingService';
 
+export interface ParameterFileMeta {
+    readonly experimentId: string;
+    readonly trialId: string;
+    readonly filePath: string;
+}
+
 /**
  * PAI Training service Rest server, provides rest API to support pai job metrics update
  *
  */
 @component.Singleton
 export class PAIJobRestServer extends ClusterJobRestServer {
+    private parameterFileMetaList: ParameterFileMeta[] = [];
+
     @Inject
     private readonly paiTrainingService : PAITrainingService;
 
@@ -52,4 +61,33 @@ export class PAIJobRestServer extends ClusterJobRestServer {
             });
         }
     }
+
+    protected createRestHandler(): Router {
+        const router: Router = super.createRestHandler();
+
+        router.post(`/parameter-file-meta`, (req: Request, res: Response) => {
+            try {
+                this.log.info(`POST /parameter-file-meta, body is ${JSON.stringify(req.body)}`);
+                this.parameterFileMetaList.push(req.body);
+                res.send();
+            } catch (err) {
+                this.log.error(`POST parameter-file-meta error: ${err}`);
+                res.status(500);
+                res.send(err.message);
+            }
+        });
+
+        router.get(`/parameter-file-meta`, (req: Request, res: Response) => {
+            try {
+                this.log.info(`GET /parameter-file-meta`);
+                res.send(this.parameterFileMetaList);
+            } catch (err) {
+                this.log.error(`GET parameter-file-meta error: ${err}`);
+                res.status(500);
+                res.send(err.message);
+            }
+        });
+
+        return router;
+    }
 }

src/nni_manager/training_service/pai/paiTrainingService.ts

@@ -33,7 +33,7 @@ import { MethodNotImplementedError } from '../../common/errors';
 import { getExperimentId, getInitTrialSequenceId } from '../../common/experimentStartupInfo';
 import { getLogger, Logger } from '../../common/log';
 import {
-    JobApplicationForm, NNIManagerIpConfig, TrainingService,
+    HyperParameters, JobApplicationForm, NNIManagerIpConfig, TrainingService,
     TrialJobApplicationForm, TrialJobDetail, TrialJobMetric
 } from '../../common/trainingService';
 import { delay, generateParamFileName,
@@ -45,7 +45,7 @@ import { HDFSClientUtility } from './hdfsClientUtility';
 import { NNIPAITrialConfig, PAIClusterConfig, PAIJobConfig, PAITaskRole } from './paiConfig';
 import { PAI_LOG_PATH_FORMAT, PAI_OUTPUT_DIR_FORMAT, PAI_TRIAL_COMMAND_FORMAT, PAITrialJobDetail } from './paiData';
 import { PAIJobInfoCollector } from './paiJobInfoCollector';
-import { PAIJobRestServer } from './paiJobRestServer';
+import { PAIJobRestServer, ParameterFileMeta } from './paiJobRestServer';
 
 import * as WebHDFS from 'webhdfs';
 
@@ -79,6 +79,7 @@ class PAITrainingService implements TrainingService {
     private copyExpCodeDirPromise?: Promise<void>;
     private versionCheck: boolean = true;
     private logCollection: string;
+    private isMultiPhase: boolean = false;
 
     constructor() {
         this.log = getLogger();
@@ -179,12 +180,22 @@ class PAITrainingService implements TrainingService {
         return deferred.promise;
     }
 
-    public updateTrialJob(trialJobId: string, form: JobApplicationForm): Promise<TrialJobDetail> {
-        throw new MethodNotImplementedError();
+    public async updateTrialJob(trialJobId: string, form: JobApplicationForm): Promise<TrialJobDetail> {
+        const trialJobDetail: undefined | TrialJobDetail = this.trialJobsMap.get(trialJobId);
+        if (trialJobDetail === undefined) {
+            throw new Error(`updateTrialJob failed: ${trialJobId} not found`);
+        }
+        if (form.jobType === 'TRIAL') {
+                await this.writeParameterFile(trialJobId, (<TrialJobApplicationForm>form).hyperParameters);
+        } else {
+            throw new Error(`updateTrialJob failed: jobType ${form.jobType} not supported.`);
+        }
+
+        return trialJobDetail;
     }
 
     public get isMultiPhaseJobSupported(): boolean {
-        return false;
+        return true;
     }
 
     // tslint:disable:no-http-string
@@ -336,6 +347,9 @@ class PAITrainingService implements TrainingService {
             case TrialConfigMetadataKey.LOG_COLLECTION:
                 this.logCollection = value;
                 break;
+            case TrialConfigMetadataKey.MULTI_PHASE:
+                this.isMultiPhase = (value === 'true' || value === 'True');
+                break;
             default:
                 //Reject for unknown keys
                 throw new Error(`Uknown key: ${key}`);
@@ -445,6 +459,7 @@ class PAITrainingService implements TrainingService {
             trialJobId,
             this.experimentId,
             trialJobDetail.sequenceId,
+            this.isMultiPhase,
             this.paiTrialConfig.command,
             nniManagerIp,
             this.paiRestServerPort,
@@ -632,7 +647,50 @@ class PAITrainingService implements TrainingService {
         return Promise.race([timeoutDelay, deferred.promise])
             .finally(() => { clearTimeout(timeoutId); });
     }
-    // tslint:enable:no-any no-unsafe-any no-http-string
+
+    private async writeParameterFile(trialJobId: string, hyperParameters: HyperParameters): Promise<void> {
+        if (this.paiClusterConfig === undefined) {
+            throw new Error('PAI Cluster config is not initialized');
+        }
+        if (this.paiTrialConfig === undefined) {
+            throw new Error('PAI trial config is not initialized');
+        }
+
+        const trialLocalTempFolder: string = path.join(getExperimentRootDir(), 'trials-local', trialJobId);
+        const hpFileName: string = generateParamFileName(hyperParameters);
+        const localFilepath: string = path.join(trialLocalTempFolder, hpFileName);
+        await fs.promises.writeFile(localFilepath, hyperParameters.value, { encoding: 'utf8' });
+        const hdfsCodeDir: string = HDFSClientUtility.getHdfsTrialWorkDir(this.paiClusterConfig.userName, trialJobId);
+        const hdfsHpFilePath: string = path.join(hdfsCodeDir, hpFileName);
+
+        await HDFSClientUtility.copyFileToHdfs(localFilepath, hdfsHpFilePath, this.hdfsClient);
+
+        await this.postParameterFileMeta({
+            experimentId: this.experimentId,
+            trialId: trialJobId,
+            filePath: hdfsHpFilePath
+        });
+    }
+
+    private postParameterFileMeta(parameterFileMeta: ParameterFileMeta): Promise<void> {
+        const deferred : Deferred<void> = new Deferred<void>();
+        const restServer: PAIJobRestServer = component.get(PAIJobRestServer);
+        const req: request.Options = {
+            uri: `${restServer.endPoint}${restServer.apiRootUrl}/parameter-file-meta`,
+            method: 'POST',
+            json: true,
+            body: parameterFileMeta
+        };
+        request(req, (err: Error, res: request.Response) => {
+            if (err) {
+                deferred.reject(err);
+            } else {
+                deferred.resolve();
+            }
+        });
+
+        return deferred.promise;
+    }
 }
 
 export { PAITrainingService };

src/nni_manager/types/tail-stream/index.d.ts

 declare module 'tail-stream' {
     export interface Stream {
         on(type: 'data', callback: (data: Buffer) => void): void;
-        destroy(): void;
+        end(data: number): void;
+        emit(data: string): void;
     }
     export function createReadStream(path: string): Stream;
 }
\ No newline at end of file

src/sdk/pynni/nni/__init__.py

@@ -23,6 +23,7 @@
 
 from .trial import *
 from .smartparam import *
+from .nas_utils import reload_tensorflow_variables
 
 class NoMoreTrialError(Exception):
     def __init__(self,ErrorInfo):

src/sdk/pynni/nni/__main__.py

@@ -28,9 +28,8 @@ import json
 import importlib
 
 from .constants import ModuleName, ClassName, ClassArgs, AdvisorModuleName, AdvisorClassName
-from nni.common import enable_multi_thread
+from nni.common import enable_multi_thread, enable_multi_phase
 from nni.msg_dispatcher import MsgDispatcher
-from nni.multi_phase.multi_phase_dispatcher import MultiPhaseMsgDispatcher
 logger = logging.getLogger('nni.main')
 logger.debug('START')
 
@@ -126,6 +125,8 @@ def main():
     args = parse_args()
     if args.multi_thread:
         enable_multi_thread()
+    if args.multi_phase:
+        enable_multi_phase()
 
     if args.advisor_class_name:
         # advisor is enabled and starts to run
@@ -180,10 +181,7 @@ def main():
             if assessor is None:
                 raise AssertionError('Failed to create Assessor instance')
 
-        if args.multi_phase:
-            dispatcher = MultiPhaseMsgDispatcher(tuner, assessor)
-        else:
-            dispatcher = MsgDispatcher(tuner, assessor)
+        dispatcher = MsgDispatcher(tuner, assessor)
 
         try:
             dispatcher.run()

src/sdk/pynni/nni/batch_tuner/batch_tuner.py

@@ -78,7 +78,7 @@ class BatchTuner(Tuner):
         """
         self.values = self.is_valid(search_space)
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """Returns a dict of trial (hyper-)parameters, as a serializable object.
 
         Parameters
@@ -90,7 +90,7 @@ class BatchTuner(Tuner):
             raise nni.NoMoreTrialError('no more parameters now.')
         return self.values[self.count]
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         pass
 
     def import_data(self, data):

src/sdk/pynni/nni/bohb_advisor/bohb_advisor.py

@@ -106,7 +106,7 @@ class Bracket():
         self.s_max = s_max
         self.eta = eta
         self.max_budget = max_budget
-        self.optimize_mode = optimize_mode
+        self.optimize_mode = OptimizeMode(optimize_mode)
 
         self.n = math.ceil((s_max + 1) * eta**s / (s + 1) - _epsilon)
         self.r = max_budget / eta**s

src/sdk/pynni/nni/common.py

@@ -69,6 +69,7 @@ def init_logger(logger_file_path, log_level_name='info'):
     sys.stdout = _LoggerFileWrapper(logger_file)
 
 _multi_thread = False
+_multi_phase = False
 
 def enable_multi_thread():
     global _multi_thread
@@ -76,3 +77,10 @@ def enable_multi_thread():
 
 def multi_thread_enabled():
     return _multi_thread
+
+def enable_multi_phase():
+    global _multi_phase
+    _multi_phase = True
+
+def multi_phase_enabled():
+    return _multi_phase

src/sdk/pynni/nni/evolution_tuner/evolution_tuner.py

@@ -188,7 +188,7 @@ class EvolutionTuner(Tuner):
                 self.searchspace_json, is_rand, self.random_state)
             self.population.append(Individual(config=config))
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """Returns a dict of trial (hyper-)parameters, as a serializable object.
 
         Parameters
@@ -232,7 +232,7 @@ class EvolutionTuner(Tuner):
         config = split_index(total_config)
         return config
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         '''Record the result from a trial
 
         Parameters

src/sdk/pynni/nni/gridsearch_tuner/gridsearch_tuner.py

@@ -137,7 +137,7 @@ class GridSearchTuner(Tuner):
         '''
         self.expanded_search_space = self.json2parameter(search_space)
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         self.count += 1
         while (self.count <= len(self.expanded_search_space)-1):
             _params_tuple = convert_dict2tuple(self.expanded_search_space[self.count])
@@ -147,7 +147,7 @@ class GridSearchTuner(Tuner):
                 return self.expanded_search_space[self.count]
         raise nni.NoMoreTrialError('no more parameters now.')
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         pass
 
     def import_data(self, data):

src/sdk/pynni/nni/hyperband_advisor/hyperband_advisor.py

@@ -144,7 +144,7 @@ class Bracket():
         self.configs_perf = []          # [ {id: [seq, acc]}, {}, ... ]
         self.num_configs_to_run = []    # [ n, n, n, ... ]
         self.num_finished_configs = []  # [ n, n, n, ... ]
-        self.optimize_mode = optimize_mode
+        self.optimize_mode = OptimizeMode(optimize_mode)
         self.no_more_trial = False
 
     def is_completed(self):

src/sdk/pynni/nni/hyperopt_tuner/hyperopt_tuner.py

@@ -248,7 +248,7 @@ class HyperoptTuner(Tuner):
                                 verbose=0)
         self.rval.catch_eval_exceptions = False
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """
         Returns a set of trial (hyper-)parameters, as a serializable object.
 
@@ -269,7 +269,7 @@ class HyperoptTuner(Tuner):
         params = split_index(total_params)
         return params
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         """
         Record an observation of the objective function
 

src/sdk/pynni/nni/metis_tuner/Regression_GMM/Selection.py

@@ -49,15 +49,16 @@ def selection_r(x_bounds,
                 num_starting_points=100,
                 minimize_constraints_fun=None):
     '''
-    Call selection
+    Select using different types.
     '''
-    minimize_starting_points = [lib_data.rand(x_bounds, x_types)\
-                                    for i in range(0, num_starting_points)]
+    minimize_starting_points = clusteringmodel_gmm_good.sample(n_samples=num_starting_points)
+    
     outputs = selection(x_bounds, x_types,
                         clusteringmodel_gmm_good,
                         clusteringmodel_gmm_bad,
-                        minimize_starting_points,
+                        minimize_starting_points[0],
                         minimize_constraints_fun)
+      
     return outputs
 
 def selection(x_bounds,