Merge pull request #198 from microsoft/master

Set gpuNum as optional (#1389)

docs/en_US/Tutorial/ExperimentConfig.md

@@ -266,7 +266,7 @@ machineList:
 
   * __gpuNum__
 
-      __gpuNum__ specifies the gpu number to run the tuner process. The value of this field should be a positive number.
+      __gpuNum__ specifies the gpu number to run the tuner process. The value of this field should be a positive number. If the field is not set, NNI will not set `CUDA_VISIBLE_DEVICES` in script (that is, will not control the visibility of GPUs on trial command through `CUDA_VISIBLE_DEVICES`), and will not manage gpu resource.
 
       Note: users could only specify one way to set tuner, for example, set {tunerName, optimizationMode} or {tunerCommand, tunerCwd}, and could not set them both.
 

src/nni_manager/training_service/local/localTrainingService.ts

@@ -307,9 +307,11 @@ class LocalTrainingService implements TrainingService {
                 if (this.localTrailConfig === undefined) {
                     throw new Error('trial config parsed failed');
                 }
-                this.log.info(`required GPU number is ${this.localTrailConfig.gpuNum}`);
-                if (this.gpuScheduler === undefined && this.localTrailConfig.gpuNum > 0) {
-                    this.gpuScheduler = new GPUScheduler();
+                if (this.localTrailConfig.gpuNum !== undefined) {
+                    this.log.info(`required GPU number is ${this.localTrailConfig.gpuNum}`);
+                    if (this.gpuScheduler === undefined && this.localTrailConfig.gpuNum > 0) {
+                        this.gpuScheduler = new GPUScheduler();
+                    }
                 }
                 break;
             case TrialConfigMetadataKey.LOCAL_CONFIG:
@@ -399,7 +401,8 @@ class LocalTrainingService implements TrainingService {
 
     private getEnvironmentVariables(
         trialJobDetail: TrialJobDetail,
-        resource: { gpuIndices: number[] }): { key: string; value: string }[] {
+        resource: { gpuIndices: number[] },
+        gpuNum: number | undefined): { key: string; value: string }[] {
         const envVariables: { key: string; value: string }[] = [
             { key: 'NNI_PLATFORM', value: 'local' },
             { key: 'NNI_EXP_ID', value: this.experimentId },
@@ -409,11 +412,12 @@ class LocalTrainingService implements TrainingService {
             { key: 'NNI_TRIAL_SEQ_ID', value: trialJobDetail.sequenceId.toString() },
             { key: 'MULTI_PHASE', value: this.isMultiPhase.toString() }
         ];
-
-        envVariables.push({
-            key: 'CUDA_VISIBLE_DEVICES',
-            value: this.gpuScheduler === undefined ? '-1' : resource.gpuIndices.join(',')
-        });
+        if (gpuNum !== undefined) {
+            envVariables.push({
+                key: 'CUDA_VISIBLE_DEVICES',
+                value: this.gpuScheduler === undefined ? '-1' : resource.gpuIndices.join(',')
+            });
+        }
 
         return envVariables;
     }
@@ -490,6 +494,7 @@ class LocalTrainingService implements TrainingService {
                     if (!success) {
                         break;
                     }
+                    
                     this.occupyResource(resource);
                     await this.runTrialJob(trialJobId, resource);
                 }
@@ -526,7 +531,10 @@ class LocalTrainingService implements TrainingService {
 
     private async runTrialJob(trialJobId: string, resource: {gpuIndices: number[]}): Promise<void> {
         const trialJobDetail: LocalTrialJobDetail = <LocalTrialJobDetail>this.jobMap.get(trialJobId);
-        const variables: { key: string; value: string }[] = this.getEnvironmentVariables(trialJobDetail, resource);
+        if (this.localTrailConfig === undefined) {
+            throw new Error(`localTrialConfig not initialized!`);
+        }
+        const variables: { key: string; value: string }[] = this.getEnvironmentVariables(trialJobDetail, resource, this.localTrailConfig.gpuNum);
 
         if (this.localTrailConfig === undefined) {
             throw new Error('trial config is not initialized');

src/nni_manager/training_service/remote_machine/gpuScheduler.ts

@@ -48,14 +48,17 @@ export class GPUScheduler {
      * Schedule a machine according to the constraints (requiredGPUNum)
      * @param requiredGPUNum required GPU number
      */
-    public scheduleMachine(requiredGPUNum: number, trialJobDetail : RemoteMachineTrialJobDetail) : RemoteMachineScheduleResult {
+    public scheduleMachine(requiredGPUNum: number | undefined, trialJobDetail : RemoteMachineTrialJobDetail) : RemoteMachineScheduleResult {
+        if(requiredGPUNum === undefined) {
+            requiredGPUNum = 0;
+        }
         assert(requiredGPUNum >= 0);
         const allRMs: RemoteMachineMeta[] = Array.from(this.machineSSHClientMap.keys());
         assert(allRMs.length > 0);
 
         // Step 1: Check if required GPU number not exceeds the total GPU number in all machines
         const eligibleRM: RemoteMachineMeta[] = allRMs.filter((rmMeta : RemoteMachineMeta) =>
-                 rmMeta.gpuSummary === undefined || requiredGPUNum === 0 || rmMeta.gpuSummary.gpuCount >= requiredGPUNum);
+                 rmMeta.gpuSummary === undefined || requiredGPUNum === 0 || (requiredGPUNum !== undefined && rmMeta.gpuSummary.gpuCount >= requiredGPUNum));
         if (eligibleRM.length === 0) {
             // If the required gpu number exceeds the upper limit of all machine's GPU number
             // Return REQUIRE_EXCEED_TOTAL directly

src/nni_manager/training_service/remote_machine/remoteMachineTrainingService.ts

@@ -601,12 +601,16 @@ class RemoteMachineTrainingService implements TrainingService {
         let command: string;
         // Set CUDA_VISIBLE_DEVICES environment variable based on cuda_visible_device
         // If no valid cuda_visible_device is defined, set CUDA_VISIBLE_DEVICES to empty string to hide GPU device
-        if (typeof cuda_visible_device === 'string' && cuda_visible_device.length > 0) {
-            command = `CUDA_VISIBLE_DEVICES=${cuda_visible_device} ${this.trialConfig.command}`;
+        // If gpuNum is undefined, will not set CUDA_VISIBLE_DEVICES in script
+        if (this.trialConfig.gpuNum === undefined) {
+            command = this.trialConfig.command;
         } else {
-            command = `CUDA_VISIBLE_DEVICES=" " ${this.trialConfig.command}`;
+            if (typeof cuda_visible_device === 'string' && cuda_visible_device.length > 0) {
+                command = `CUDA_VISIBLE_DEVICES=${cuda_visible_device} ${this.trialConfig.command}`;
+            } else {
+                command = `CUDA_VISIBLE_DEVICES=" " ${this.trialConfig.command}`;
+            }
         }
-
         // tslint:disable-next-line: strict-boolean-expressions
         const nniManagerIp: string = this.nniManagerIpConfig ? this.nniManagerIpConfig.nniManagerIp : getIPV4Address();
         if (this.remoteRestServerPort === undefined) {

tools/nni_cmd/config_schema.py

@@ -220,7 +220,7 @@ common_trial_schema = {
 'trial':{
     'command': setType('command', str),
     'codeDir': setPathCheck('codeDir'),
-    'gpuNum': setNumberRange('gpuNum', int, 0, 99999),
+    Optional('gpuNum'): setNumberRange('gpuNum', int, 0, 99999),
     Optional('nasMode'): setChoice('classic_mode', 'enas_mode', 'oneshot_mode')
     }
 }