Merge pull request #61 from microsoft/master

pull code

docs/en_US/Tuner/BuiltinTuner.md

@@ -160,6 +160,7 @@ Similar to TPE, SMAC is also a black-box tuner which can be tried in various sce
 **Requirement of classArgs**
 
 * **optimize_mode** (*maximize or minimize, optional, default = maximize*) - If 'maximize', the tuner will target to maximize metrics. If 'minimize', the tuner will target to minimize metrics.
+* **config_dedup** (*True or False, optional, default = False*) - If True, the tuner will not generate a configuration that has been already generated. If False, a configuration may be generated twice, but it is rare for relatively large search space.
 
 **Usage example**
 

src/nni_manager/common/manager.ts

@@ -27,7 +27,7 @@ interface ExperimentParams {
     versionCheck?: boolean;
     logCollection?: string;
     tuner?: {
-        className: string;
+        className?: string;
         builtinTunerName?: string;
         codeDir?: string;
         classArgs?: any;
@@ -37,15 +37,15 @@ interface ExperimentParams {
         gpuIndices?: string;
     };
     assessor?: {
-        className: string;
+        className?: string;
         builtinAssessorName?: string;
         codeDir?: string;
         classArgs?: any;
         classFileName?: string;
         checkpointDir: string;
     };
     advisor?: {
-        className: string;
+        className?: string;
         builtinAdvisorName?: string;
         codeDir?: string;
         classArgs?: any;

src/nni_manager/common/utils.ts

@@ -17,7 +17,7 @@ import * as util from 'util';
 
 import { Database, DataStore } from './datastore';
 import { ExperimentStartupInfo, getExperimentStartupInfo, setExperimentStartupInfo } from './experimentStartupInfo';
-import { Manager } from './manager';
+import { ExperimentParams, Manager } from './manager';
 import { HyperParameters, TrainingService, TrialJobStatus } from './trainingService';
 
 function getExperimentRootDir(): string {
@@ -130,15 +130,6 @@ function parseArg(names: string[]): string {
     return '';
 }
 
-function encodeCmdLineArgs(args: any): any {
-    if(process.platform === 'win32'){
-        return JSON.stringify(args);
-    }
-    else{
-        return JSON.stringify(JSON.stringify(args));
-    }
-}
-
 function getCmdPy(): string {
     let cmd = 'python3';
     if(process.platform === 'win32'){
@@ -150,83 +141,14 @@ function getCmdPy(): string {
 /**
  * Generate command line to start automl algorithm(s),
  * either start advisor or start a process which runs tuner and assessor
- * @param tuner : For builtin tuner:
- *     {
- *         className: 'EvolutionTuner'
- *         classArgs: {
- *             optimize_mode: 'maximize',
- *             population_size: 3
- *         }
- *     }
- * customized:
- *     {
- *         codeDir: '/tmp/mytuner'
- *         classFile: 'best_tuner.py'
- *         className: 'BestTuner'
- *         classArgs: {
- *             optimize_mode: 'maximize',
- *             population_size: 3
- *         }
- *     }
  *
- * @param assessor: similiar as tuner
- * @param advisor: similar as tuner
+ * @param expParams: experiment startup parameters
  *
  */
-function getMsgDispatcherCommand(tuner: any, assessor: any, advisor: any, multiPhase: boolean = false, multiThread: boolean = false): string {
-    if ((tuner || assessor) && advisor) {
-        throw new Error('Error: specify both tuner/assessor and advisor is not allowed');
-    }
-    if (!tuner && !advisor) {
-        throw new Error('Error: specify neither tuner nor advisor is not allowed');
-    }
-    let command: string = `${getCmdPy()} -m nni`;
-    if (multiPhase) {
-        command += ' --multi_phase';
-    }
-
-    if (multiThread) {
-        command += ' --multi_thread';
-    }
-
-    if (advisor) {
-        command += ` --advisor_class_name ${advisor.className}`;
-        if (advisor.classArgs !== undefined) {
-            command += ` --advisor_args ${encodeCmdLineArgs(advisor.classArgs)}`;
-        }
-        if (advisor.codeDir !== undefined && advisor.codeDir.length > 1) {
-            command += ` --advisor_directory ${advisor.codeDir}`;
-        }
-        if (advisor.classFileName !== undefined && advisor.classFileName.length > 1) {
-            command += ` --advisor_class_filename ${advisor.classFileName}`;
-        }
-    } else {
-        command += ` --tuner_class_name ${tuner.className}`;
-        if (tuner.classArgs !== undefined) {
-            command += ` --tuner_args ${encodeCmdLineArgs(tuner.classArgs)}`;
-        }
-        if (tuner.codeDir !== undefined && tuner.codeDir.length > 1) {
-            command += ` --tuner_directory ${tuner.codeDir}`;
-        }
-        if (tuner.classFileName !== undefined && tuner.classFileName.length > 1) {
-            command += ` --tuner_class_filename ${tuner.classFileName}`;
-        }
-
-        if (assessor !== undefined && assessor.className !== undefined) {
-            command += ` --assessor_class_name ${assessor.className}`;
-            if (assessor.classArgs !== undefined) {
-                command += ` --assessor_args ${encodeCmdLineArgs(assessor.classArgs)}`;
-            }
-            if (assessor.codeDir !== undefined && assessor.codeDir.length > 1) {
-                command += ` --assessor_directory ${assessor.codeDir}`;
-            }
-            if (assessor.classFileName !== undefined && assessor.classFileName.length > 1) {
-                command += ` --assessor_class_filename ${assessor.classFileName}`;
-            }
-        }
-    }
-
-    return command;
+function getMsgDispatcherCommand(expParams: ExperimentParams): string {
+    const clonedParams = Object.assign({}, expParams);
+    delete clonedParams.searchSpace;
+    return `${getCmdPy()} -m nni --exp_params ${Buffer.from(JSON.stringify(clonedParams)).toString('base64')}`;
 }
 
 /**

src/nni_manager/core/nnimanager.ts

@@ -170,8 +170,7 @@ class NNIManager implements Manager {
             this.trainingService.setClusterMetadata('log_collection', expParams.logCollection.toString());
         }
 
-        const dispatcherCommand: string = getMsgDispatcherCommand(expParams.tuner, expParams.assessor, expParams.advisor,
-            expParams.multiPhase, expParams.multiThread);
+        const dispatcherCommand: string = getMsgDispatcherCommand(expParams);
         this.log.debug(`dispatcher command: ${dispatcherCommand}`);
         const checkpointDir: string = await this.createCheckpointDir();
         this.setupTuner(
@@ -211,8 +210,7 @@ class NNIManager implements Manager {
             this.trainingService.setClusterMetadata('version_check', expParams.versionCheck.toString());
         }
 
-        const dispatcherCommand: string = getMsgDispatcherCommand(expParams.tuner, expParams.assessor, expParams.advisor,
-            expParams.multiPhase, expParams.multiThread);
+        const dispatcherCommand: string = getMsgDispatcherCommand(expParams);
         this.log.debug(`dispatcher command: ${dispatcherCommand}`);
         const checkpointDir: string = await this.createCheckpointDir();
         this.setupTuner(

src/nni_manager/core/test/ipcInterfaceTerminate.test.ts

@@ -21,18 +21,26 @@ function startProcess(): void {
     const dispatcherCmd: string = getMsgDispatcherCommand(
         // Mock tuner config
         {
-            className: 'DummyTuner',
-            codeDir: './',
-            classFileName: 'dummy_tuner.py'
-        },
-        // Mock assessor config
-        {
-            className: 'DummyAssessor',
-            codeDir: './',
-            classFileName: 'dummy_assessor.py'
-        },
-        // advisor
-        undefined
+            experimentName: 'exp1',
+            maxExecDuration: 3600,
+            searchSpace: '',
+            trainingServicePlatform: 'local',
+            authorName: '',
+            trialConcurrency: 1,
+            maxTrialNum: 5,
+            tuner: {
+                className: 'DummyTuner',
+                codeDir: './',
+                classFileName: 'dummy_tuner.py',
+                checkpointDir: './'
+            },
+            assessor: {
+                className: 'DummyAssessor',
+                codeDir: './',
+                classFileName: 'dummy_assessor.py',
+                checkpointDir: './'
+            }
+        }
     );
     const proc: ChildProcess = getTunerProc(dispatcherCmd, stdio,  'core/test', process.env);
     proc.on('error', (error: Error): void => {

src/nni_manager/core/test/nnimanager.test.ts

@@ -42,17 +42,17 @@ describe('Unit test for nnimanager', function () {
         maxExecDuration: 5,
         maxTrialNum: 3,
         trainingServicePlatform: 'local',
-        searchSpace: '{"x":1}',
+        searchSpace: '{"lr": {"_type": "choice", "_value": [0.01,0.001]}}',
         tuner: {
-            className: 'TPE',
+            builtinTunerName: 'TPE',
             classArgs: {
                 optimize_mode: 'maximize'
             },
             checkpointDir: '',
             gpuNum: 0
         },
         assessor: {
-            className: 'Medianstop',
+            builtinAssessorName: 'Medianstop',
             checkpointDir: '',
             gpuNum: 1
         }
@@ -65,17 +65,17 @@ describe('Unit test for nnimanager', function () {
         maxExecDuration: 6,
         maxTrialNum: 2,
         trainingServicePlatform: 'local',
-        searchSpace: '{"y":2}',
+        searchSpace: '{"lr": {"_type": "choice", "_value": [0.01,0.001]}}',
         tuner: {
-            className: 'TPE',
+            builtinTunerName: 'TPE',
             classArgs: {
                 optimize_mode: 'maximize'
             },
             checkpointDir: '',
             gpuNum: 0
         },
         assessor: {
-            className: 'Medianstop',
+            builtinAssessorName: 'Medianstop',
             checkpointDir: '',
             gpuNum: 1
         }
@@ -198,7 +198,7 @@ describe('Unit test for nnimanager', function () {
     it('test updateExperimentProfile SEARCH_SPACE',  () => {
         return nniManager.updateExperimentProfile(experimentProfile, 'SEARCH_SPACE').then(() => {
             nniManager.getExperimentProfile().then((updateProfile) => {
-                expect(updateProfile.params.searchSpace).to.be.equal('{"y":2}');
+                expect(updateProfile.params.searchSpace).to.be.equal('{"lr": {"_type": "choice", "_value": [0.01,0.001]}}');
             });
         }).catch((error) => {
             assert.fail(error);