fix(api): Change default GPU Request value and prevent null values from being accepted

api/cluster/resource/templater.go

@@ -222,20 +222,26 @@ func (t *InferenceServiceTemplater) createPredictorSpec(modelService *models.Ser
 
 	nodeSelector := map[string]string{}
 	tolerations := []corev1.Toleration{}
-	if modelService.ResourceRequest.GPUName != "" && !modelService.ResourceRequest.GPURequest.IsZero() {
-		// Look up to the GPU resource type and quantity from DeploymentConfig
-		for _, gpuConfig := range t.deploymentConfig.GPUs {
-			if gpuConfig.Name == modelService.ResourceRequest.GPUName {
-				// Declare and initialize resourceType and resourceQuantity variables
-				resourceType := corev1.ResourceName(gpuConfig.ResourceType)
-				resourceQuantity := modelService.ResourceRequest.GPURequest
-
-				// Set the resourceType as the key in the maps, with resourceQuantity as the value
-				resources.Requests[resourceType] = resourceQuantity
-				resources.Limits[resourceType] = resourceQuantity
-
-				nodeSelector = gpuConfig.NodeSelector
-				tolerations = gpuConfig.Tolerations
+
+	if modelService.ResourceRequest.GPUName != "" {
+		if modelService.ResourceRequest.GPURequest.IsZero() {
+			// This should never be set as zero if a GPU name is specified
+			return kservev1beta1.PredictorSpec{}, fmt.Errorf("GPU request cannot set as be 0")
+		} else {
+			// Look up to the GPU resource type and quantity from DeploymentConfig
+			for _, gpuConfig := range t.deploymentConfig.GPUs {
+				if gpuConfig.Name == modelService.ResourceRequest.GPUName {
+					// Declare and initialize resourceType and resourceQuantity variables
+					resourceType := corev1.ResourceName(gpuConfig.ResourceType)
+					resourceQuantity := modelService.ResourceRequest.GPURequest
+
+					// Set the resourceType as the key in the maps, with resourceQuantity as the value
+					resources.Requests[resourceType] = resourceQuantity
+					resources.Limits[resourceType] = resourceQuantity
+
+					nodeSelector = gpuConfig.NodeSelector
+					tolerations = gpuConfig.Tolerations
+				}
 			}
 		}
 	}

api/cluster/resource/templater_gpu_test.go

@@ -106,6 +106,14 @@ func TestCreateInferenceServiceSpecWithGPU(t *testing.T) {
 		},
 	}
 
+	invalidResourceRequest := &models.ResourceRequest{
+		MinReplica:    1,
+		MaxReplica:    2,
+		CPURequest:    resource.MustParse("500m"),
+		MemoryRequest: resource.MustParse("500Mi"),
+		GPUName:       "NVIDIA P4",
+	}
+
 	queueResourcePercentage := "2"
 	storageUri := fmt.Sprintf("%s/model", modelSvc.ArtifactURI)
 
@@ -1563,6 +1571,25 @@ func TestCreateInferenceServiceSpecWithGPU(t *testing.T) {
 				},
 			},
 		},
+		{
+			name: "invalid resource request with 0 GPU requested",
+			modelSvc: &models.Service{
+				Name:            modelSvc.Name,
+				ModelName:       modelSvc.ModelName,
+				ModelVersion:    modelSvc.ModelVersion,
+				Namespace:       project.Name,
+				ArtifactURI:     modelSvc.ArtifactURI,
+				Type:            models.ModelTypeTensorflow,
+				Options:         &models.ModelOption{},
+				Metadata:        modelSvc.Metadata,
+				Protocol:        protocol.HttpJson,
+				ResourceRequest: invalidResourceRequest,
+			},
+			resourcePercentage: queueResourcePercentage,
+			deploymentScale:    defaultDeploymentScale,
+			exp:                &kservev1beta1.InferenceService{},
+			wantErr:            true,
+		},
 	}
 
 	for _, tt := range tests {

ui/src/pages/version/components/forms/components/ResourcesPanel.js

@@ -82,7 +82,7 @@ export const ResourcesPanel = ({
       return;
     }
     onChange("gpu_name")(gpu_name);
-    onChange("gpu_request")(undefined);
+    onChange("gpu_request")(gpus[gpu_name].values[0]);
     onChange("min_monthly_cost_per_gpu")(
       gpus[gpu_name].min_monthly_cost_per_gpu
     );