KEP-2170: Add validation to Torch numProcPerNode field

Signed-off-by: Antonin Stefanutti <antonin@stefanutti.fr>

api/openapi-spec/swagger.json

@@ -517,7 +517,7 @@
         },
         "numProcPerNode": {
           "description": "Number of processes per node. This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI. Supported values: `auto`, `cpu`, `gpu`, or int value. Defaults to `auto`.",
-          "type": "string"
+          "$ref": "#/definitions/k8s.io.apimachinery.pkg.util.intstr.IntOrString"
         }
       }
     },
@@ -716,7 +716,7 @@
         },
         "numProcPerNode": {
           "description": "Number of processes/workers/slots on every training node. For the Torch runtime: `auto`, `cpu`, `gpu`, or int value can be set. For the MPI runtime only int value can be set.",
-          "type": "string"
+          "$ref": "#/definitions/k8s.io.apimachinery.pkg.util.intstr.IntOrString"
         },
         "resourcesPerNode": {
           "description": "Compute resources for each training node.",

manifests/base/crds/trainer.kubeflow.org_clustertrainingruntimes.yaml

@@ -585,12 +585,17 @@ spec:
                             type: integer
                         type: object
                       numProcPerNode:
+                        anyOf:
+                        - type: integer
+                        - type: string
                         description: |-
                           Number of processes per node.
                           This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI.
                           Supported values: `auto`, `cpu`, `gpu`, or int value.
                           Defaults to `auto`.
-                        type: string
+                        x-kubernetes-int-or-string: true
+                        x-kubernetes-validations:
+                        - rule: self > 0 || self in ['auto', 'cpu', 'gpu']
                     type: object
                 type: object
               podGroupPolicy:

manifests/base/crds/trainer.kubeflow.org_trainingruntimes.yaml

@@ -585,12 +585,17 @@ spec:
                             type: integer
                         type: object
                       numProcPerNode:
+                        anyOf:
+                        - type: integer
+                        - type: string
                         description: |-
                           Number of processes per node.
                           This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI.
                           Supported values: `auto`, `cpu`, `gpu`, or int value.
                           Defaults to `auto`.
-                        type: string
+                        x-kubernetes-int-or-string: true
+                        x-kubernetes-validations:
+                        - rule: self > 0 || self in ['auto', 'cpu', 'gpu']
                     type: object
                 type: object
               podGroupPolicy:

manifests/base/crds/trainer.kubeflow.org_trainjobs.yaml

@@ -3138,11 +3138,14 @@ spec:
                     format: int32
                     type: integer
                   numProcPerNode:
+                    anyOf:
+                    - type: integer
+                    - type: string
                     description: |-
                       Number of processes/workers/slots on every training node.
                       For the Torch runtime: `auto`, `cpu`, `gpu`, or int value can be set.
                       For the MPI runtime only int value can be set.
-                    type: string
+                    x-kubernetes-int-or-string: true
                   resourcesPerNode:
                     description: Compute resources for each training node.
                     properties:

pkg/apis/trainer/v1alpha1/trainingruntime_types.go

@@ -19,6 +19,7 @@ package v1alpha1
 import (
 	autoscalingv2 "k8s.io/api/autoscaling/v2"
 	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
+	"k8s.io/apimachinery/pkg/util/intstr"
 	jobsetv1alpha2 "sigs.k8s.io/jobset/api/jobset/v1alpha2"
 )
 
@@ -171,9 +172,9 @@ type TorchMLPolicySource struct {
 	// Number of processes per node.
 	// This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI.
 	// Supported values: `auto`, `cpu`, `gpu`, or int value.
-	// TODO (andreyvelich): Add kubebuilder validation.
 	// Defaults to `auto`.
-	NumProcPerNode *string `json:"numProcPerNode,omitempty"`
+	// +kubebuilder:validation:XValidation:rule="self > 0 || self in ['auto', 'cpu', 'gpu']"
+	NumProcPerNode *intstr.IntOrString `json:"numProcPerNode,omitempty"`
 
 	// Elastic policy for the PyTorch training.
 	ElasticPolicy *TorchElasticPolicy `json:"elasticPolicy,omitempty"`

pkg/apis/trainer/v1alpha1/trainjob_types.go

@@ -19,6 +19,7 @@ package v1alpha1
 import (
 	corev1 "k8s.io/api/core/v1"
 	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
+	"k8s.io/apimachinery/pkg/util/intstr"
 )
 
 const (
@@ -194,7 +195,7 @@ type Trainer struct {
 	// Number of processes/workers/slots on every training node.
 	// For the Torch runtime: `auto`, `cpu`, `gpu`, or int value can be set.
 	// For the MPI runtime only int value can be set.
-	NumProcPerNode *string `json:"numProcPerNode,omitempty"`
+	NumProcPerNode *intstr.IntOrString `json:"numProcPerNode,omitempty"`
 }
 
 // DatasetConfig represents the desired dataset configuration.

pkg/runtime/core/trainingruntime_test.go

@@ -26,6 +26,7 @@ import (
 	corev1 "k8s.io/api/core/v1"
 	"k8s.io/apimachinery/pkg/api/resource"
 	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
+	"k8s.io/apimachinery/pkg/util/intstr"
 	"sigs.k8s.io/controller-runtime/pkg/client"
 	schedulerpluginsv1alpha1 "sigs.k8s.io/scheduler-plugins/apis/scheduling/v1alpha1"
 
@@ -263,7 +264,7 @@ func TestTrainingRuntimeNewObjects(t *testing.T) {
 		"succeeded to build JobSet with Torch values from the TrainJob": {
 			trainingRuntime: testingutil.MakeTrainingRuntimeWrapper(metav1.NamespaceDefault, "test-runtime").RuntimeSpec(
 				testingutil.MakeTrainingRuntimeSpecWrapper(testingutil.MakeTrainingRuntimeWrapper(metav1.NamespaceDefault, "test-runtime").Spec).
-					TorchPolicy(100, "auto").
+					TorchPolicy(100, intstr.FromString("auto")).
 					ContainerTrainer("test:runtime", []string{"runtime"}, []string{"runtime"}, resRequests).
 					Obj(),
 			).Obj(),
@@ -273,7 +274,7 @@ func TestTrainingRuntimeNewObjects(t *testing.T) {
 				Trainer(
 					testingutil.MakeTrainJobTrainerWrapper().
 						NumNodes(30).
-						NumProcPerNode("3").
+						NumProcPerNode(intstr.FromInt32(3)).
 						Obj(),
 				).
 				Obj(),
@@ -317,7 +318,7 @@ func TestTrainingRuntimeNewObjects(t *testing.T) {
 		"succeeded to build JobSet with Torch values from the Runtime and envs.": {
 			trainingRuntime: testingutil.MakeTrainingRuntimeWrapper(metav1.NamespaceDefault, "test-runtime").RuntimeSpec(
 				testingutil.MakeTrainingRuntimeSpecWrapper(testingutil.MakeTrainingRuntimeWrapper(metav1.NamespaceDefault, "test-runtime").Spec).
-					TorchPolicy(100, "auto").
+					TorchPolicy(100, intstr.FromString("auto")).
 					ContainerTrainer("test:runtime", []string{"runtime"}, []string{"runtime"}, resRequests).
 					ContainerTrainerEnv(
 						[]corev1.EnvVar{

pkg/runtime/framework/plugins/mpi/mpi.go

@@ -94,7 +94,7 @@ func (m *MPI) EnforceMLPolicy(info *runtime.Info, trainJob *trainer.TrainJob) er
 
 	numProcPerNode := strconv.Itoa(int(*info.RuntimePolicy.MLPolicy.MPI.NumProcPerNode))
 	if trainJob.Spec.Trainer != nil && trainJob.Spec.Trainer.NumProcPerNode != nil {
-		numProcPerNode = *trainJob.Spec.Trainer.NumProcPerNode
+		numProcPerNode = (*trainJob.Spec.Trainer.NumProcPerNode).String()
 	}
 	info.Trainer.NumProcPerNode = numProcPerNode
 

pkg/runtime/framework/plugins/torch/torch.go

@@ -21,6 +21,7 @@ import (
 	"fmt"
 
 	corev1 "k8s.io/api/core/v1"
+	"k8s.io/apimachinery/pkg/util/intstr"
 	"k8s.io/apimachinery/pkg/util/sets"
 	"k8s.io/apimachinery/pkg/util/validation/field"
 	"k8s.io/utils/ptr"
@@ -66,9 +67,9 @@ func (t *Torch) EnforceMLPolicy(info *runtime.Info, trainJob *trainer.TrainJob)
 	}
 	info.Trainer.NumNodes = numNodes
 
-	numProcPerNode := info.RuntimePolicy.MLPolicy.Torch.NumProcPerNode
+	numProcPerNode := ptr.Deref(info.RuntimePolicy.MLPolicy.Torch.NumProcPerNode, intstr.FromString("auto"))
 	if trainJob.Spec.Trainer != nil && trainJob.Spec.Trainer.NumProcPerNode != nil {
-		numProcPerNode = trainJob.Spec.Trainer.NumProcPerNode
+		numProcPerNode = ptr.Deref(trainJob.Spec.Trainer.NumProcPerNode, intstr.FromString("auto"))
 	}
 
 	// Update envs for Info object.
@@ -83,7 +84,7 @@ func (t *Torch) EnforceMLPolicy(info *runtime.Info, trainJob *trainer.TrainJob)
 		},
 		{
 			Name:  constants.TorchEnvNumProcPerNode,
-			Value: ptr.Deref(numProcPerNode, "auto"),
+			Value: numProcPerNode.String(),
 		},
 		{
 			Name: constants.TorchEnvNodeRank,

pkg/util/testing/wrapper.go

@@ -22,6 +22,7 @@ import (
 	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
 	"k8s.io/apimachinery/pkg/runtime/schema"
 	"k8s.io/apimachinery/pkg/types"
+	"k8s.io/apimachinery/pkg/util/intstr"
 	"k8s.io/utils/ptr"
 	jobsetv1alpha2 "sigs.k8s.io/jobset/api/jobset/v1alpha2"
 	schedulerpluginsv1alpha1 "sigs.k8s.io/scheduler-plugins/apis/scheduling/v1alpha1"
@@ -392,7 +393,7 @@ func (t *TrainJobTrainerWrapper) NumNodes(numNodes int32) *TrainJobTrainerWrappe
 	return t
 }
 
-func (t *TrainJobTrainerWrapper) NumProcPerNode(numProcPerNode string) *TrainJobTrainerWrapper {
+func (t *TrainJobTrainerWrapper) NumProcPerNode(numProcPerNode intstr.IntOrString) *TrainJobTrainerWrapper {
 	t.Trainer.NumProcPerNode = &numProcPerNode
 	return t
 }
@@ -689,7 +690,7 @@ func (s *TrainingRuntimeSpecWrapper) NumNodes(numNodes int32) *TrainingRuntimeSp
 	return s
 }
 
-func (s *TrainingRuntimeSpecWrapper) TorchPolicy(numNodes int32, numProcPerNode string) *TrainingRuntimeSpecWrapper {
+func (s *TrainingRuntimeSpecWrapper) TorchPolicy(numNodes int32, numProcPerNode intstr.IntOrString) *TrainingRuntimeSpecWrapper {
 	s.MLPolicy = &trainer.MLPolicy{
 		NumNodes: &numNodes,
 		MLPolicySource: trainer.MLPolicySource{

sdk/docs/TrainerV1alpha1TorchMLPolicySource.md

@@ -5,7 +5,7 @@ TorchMLPolicySource represents a PyTorch runtime configuration.
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
 **elastic_policy** | [**TrainerV1alpha1TorchElasticPolicy**](TrainerV1alpha1TorchElasticPolicy.md) |  | [optional] 
-**num_proc_per_node** | **str** | Number of processes per node. This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI. Supported values: `auto`, `cpu`, `gpu`, or int value. Defaults to `auto`. | [optional] 
+**num_proc_per_node** | [**K8sIoApimachineryPkgUtilIntstrIntOrString**](K8sIoApimachineryPkgUtilIntstrIntOrString.md) |  | [optional] 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
 

sdk/docs/TrainerV1alpha1Trainer.md

@@ -9,7 +9,7 @@ Name | Type | Description | Notes
 **env** | [**list[V1EnvVar]**](V1EnvVar.md) | List of environment variables to set in the training container. These values will be merged with the TrainingRuntime's trainer environments. | [optional] 
 **image** | **str** | Docker image for the training container. | [optional] 
 **num_nodes** | **int** | Number of training nodes. | [optional] 
-**num_proc_per_node** | **str** | Number of processes/workers/slots on every training node. For the Torch runtime: `auto`, `cpu`, `gpu`, or int value can be set. For the MPI runtime only int value can be set. | [optional] 
+**num_proc_per_node** | [**K8sIoApimachineryPkgUtilIntstrIntOrString**](K8sIoApimachineryPkgUtilIntstrIntOrString.md) |  | [optional] 
 **resources_per_node** | [**V1ResourceRequirements**](V1ResourceRequirements.md) |  | [optional] 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)

sdk/kubeflow/trainer/models/trainer_v1alpha1_torch_ml_policy_source.py

@@ -34,7 +34,7 @@ class TrainerV1alpha1TorchMLPolicySource(object):
     """
     openapi_types = {
         'elastic_policy': 'TrainerV1alpha1TorchElasticPolicy',
-        'num_proc_per_node': 'str'
+        'num_proc_per_node': 'K8sIoApimachineryPkgUtilIntstrIntOrString'
     }
 
     attribute_map = {
@@ -82,21 +82,19 @@ def elastic_policy(self, elastic_policy):
     def num_proc_per_node(self):
         """Gets the num_proc_per_node of this TrainerV1alpha1TorchMLPolicySource.  # noqa: E501
 
-        Number of processes per node. This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI. Supported values: `auto`, `cpu`, `gpu`, or int value. Defaults to `auto`.  # noqa: E501
 
         :return: The num_proc_per_node of this TrainerV1alpha1TorchMLPolicySource.  # noqa: E501
-        :rtype: str
+        :rtype: K8sIoApimachineryPkgUtilIntstrIntOrString
         """
         return self._num_proc_per_node
 
     @num_proc_per_node.setter
     def num_proc_per_node(self, num_proc_per_node):
         """Sets the num_proc_per_node of this TrainerV1alpha1TorchMLPolicySource.
 
-        Number of processes per node. This value is inserted into the `--nproc-per-node` argument of the `torchrun` CLI. Supported values: `auto`, `cpu`, `gpu`, or int value. Defaults to `auto`.  # noqa: E501
 
         :param num_proc_per_node: The num_proc_per_node of this TrainerV1alpha1TorchMLPolicySource.  # noqa: E501
-        :type: str
+        :type: K8sIoApimachineryPkgUtilIntstrIntOrString
         """
 
         self._num_proc_per_node = num_proc_per_node