constants

const (

	// DefaultJobReplicas is the default value for the ReplicatedJob replicas.
	DefaultJobReplicas = 1

	// JobSetKind is the Kind name for the JobSet.
	JobSetKind string = "JobSet"

	// LabelTrainJobAncestor is the label to identify relationship between
	// TrainJob and Pod template in the Runtime. The following labels are supported:
	// trainer.kubeflow.org/trainjob-ancestor-step: dataset-initializer  - trainJob.spec.initializer.dataset
	// trainer.kubeflow.org/trainjob-ancestor-step: model-initializer    - trainJob.spec.initializer.model
	// trainer.kubeflow.org/trainjob-ancestor-step: trainer              - trainJob.spec.trainer
	LabelTrainJobAncestor string = "trainer.kubeflow.org/trainjob-ancestor-step"

	// LabelSupport indicates support status for a runtime, e.g. "deprecated".
	LabelSupport string = "trainer.kubeflow.org/support"

	// SupportDeprecated indicates the runtime is deprecated when used with LabelSupport.
	SupportDeprecated string = "deprecated"

	// RuntimeDeprecationPolicyURL is the URL to the runtime deprecation policy documentation.
	RuntimeDeprecationPolicyURL string = "https://www.kubeflow.org/docs/components/trainer/operator-guides/runtime/#runtime-deprecation-policy"

	// DatasetInitializer is the name of the Job, volume mount, container, and label value for the dataset initializer.
	DatasetInitializer string = "dataset-initializer"

	// DatasetMountPath is the volumeMount path for dataset.
	DatasetMountPath string = "/workspace/dataset"

	// ModelInitializer is the name of the Job, volume mount, container, and label value for the model initializer.
	ModelInitializer string = "model-initializer"

	// ModelMountPath is the volumeMount path for model.
	ModelMountPath string = "/workspace/model"

	// AncestorTrainer is the ancestor name for Trainer, which is mostly used for the value of
	// 'trainer.kubeflow.org/trainjob-ancestor-step'.
	AncestorTrainer string = "trainer"

	// Node is the name of the Job and container for the trainer node
	Node string = "node"

	// ContainerTrainerPort is the default port for the trainer nodes communication.
	ContainerTrainerPort int32 = 29500

	// PodGroupKind is the Kind name for the PodGroup.
	PodGroupKind string = "PodGroup"

	// TrainJobSuspendedMessage is status condition message for the
	// {"type": "Suspended", "status": "True", "reason": "Suspended"} condition.
	TrainJobSuspendedMessage = "TrainJob is suspended"

	// TrainJobResumedMessage is status condition message for the
	// {"type": "Suspended", "status": "True", "reason": "Resumed"} condition.
	TrainJobResumedMessage = "TrainJob is resumed"

	// TrainJobDeadlineExceededMessage is the status condition message for the
	// {"type": "Failed", "reason": "DeadlineExceeded"} condition
	// when the TrainJob exceeds its ActiveDeadlineSeconds.
	TrainJobDeadlineExceededMessage = "TrainJob exceeded its active deadline"

	// Node is the name of the Job and container for the MPI launcher.
	// When RunLauncherAsNode: true, for the launcher Job the container name is node.
	Launcher string = "launcher"

	// Flux Framework
	// The Flux View container image for the initContainer with Flux pre-installed
	FluxInstallerImage = "ghcr.io/converged-computing/flux-view-ubuntu:tag-jammy"

	// Network device used by the tree-based overlay network (TBON)
	FluxNewtowkDevice = "eth0"

	// Flux queue policy for scheduler in cluster (first come, first serve)
	FluxQueuePolicy = "fcfs"

	// Flux view container image name
	FluxInstallerContainerName = "flux-installer"

	// Name for the flux volume (emptyDir Flux is added to)
	FluxInstallVolumeName = "flux-install"

	// Name for the flux config volume
	FluxConfigVolumeName = "/etc/flux-config"

	// Path to mount flux volume
	FluxVolumePath = "/mnt/flux"

	// Volume name for Flux curve volume
	FluxCurveVolumeName = "flux-curve"

	// Path for Flux curve path
	FluxCurveVolumePath = "/curve"

	// emptyDir volume using for complete spack view software
	FluxSpackViewVolumeName = "spack-install"

	// path for spack view volume
	FluxSpackViewVolumePath = "/opt/software"

	// MPISSHAuthSecretSuffix is the name suffix for Secret with MPI SSH keys.
	MPISSHAuthSecretSuffix string = "-mpi-ssh-auth"

	// MPISSHAuthVolumeName is the volume name for Secret with MPI SSH keys.
	MPISSHAuthVolumeName string = "mpi-ssh-auth"

	// MPISSHPrivateKeyFile is the file name for the private key.
	MPISSHPrivateKeyFile string = "id_rsa"

	// MPISSHPublicKey is the value in Secret data for the public key.
	MPISSHPublicKey string = "ssh-publickey"

	// MPISSHPublicKeyFile is the file name for the public key.
	MPISSHPublicKeyFile string = MPISSHPrivateKeyFile + ".pub"

	// MPISSHAuthorizedKeys is the file name for authorized keys.
	MPISSHAuthorizedKeys string = "authorized_keys"

	// MPIHostfilePath is the directory for the MPI hostfile.
	MPIHostfileDir string = "/etc/mpi"

	// MPIHostfileName is the file name for the MPI hostfile.
	MPIHostfileName string = "hostfile"

	// MPIHostfileConfigMapSuffix is the name suffix for ConfigMap with MPI hostfile.
	MPIHostfileConfigMapSuffix string = "-mpi-hostfile"

	// MPIHostfileVolumeName is the volume name for ConfigMap with MPI hostfile.
	MPIHostfileVolumeName string = "mpi-hostfile"

	// OpenMPIEnvHostFileLocation is the OpenMPI default hostfile env key.
	OpenMPIEnvHostFileLocation string = "OMPI_MCA_orte_default_hostfile"

	// OpenMPIEnvKeyRSHArgs is the env key for the OpenMPI rsh arguments.
	OpenMPIEnvKeyRSHArgs string = "OMPI_MCA_plm_rsh_args"

	// OpenMPIEnvDefaultValueRSHArgs is the default env valur for the OpenMPI rsh arguments.
	OpenMPIEnvDefaultValueRSHArgs string = "-o ConnectionAttempts=10"

	// OpenMPIEnvKeepFQDNHostNames is the env key for OpenMPI if FQDN should be kept.
	OpenMPIEnvKeepFQDNHostNames string = "OMPI_MCA_orte_keep_fqdn_hostnames"

	// OpenMPIEnvDefaultSlots is the OpenMPI default number of slots env key.
	OpenMPIEnvDefaultSlots string = "OMPI_MCA_orte_set_default_slots"
	// Distributed envs for torchrun.
	// Ref: https://github.com/pytorch/pytorch/blob/3a0d0885171376ed610c8175a19ba40411fc6f3f/torch/distributed/argparse_util.py#L45
	// TorchEnvNumNodes is the env name for the number of training nodes.
	TorchEnvNumNodes string = "PET_NNODES"

	// TorchEnvNumProcPerNode is the env name for the number of procs per node (e.g. number of GPUs per Pod).
	TorchEnvNumProcPerNode string = "PET_NPROC_PER_NODE"

	// TorchEnvNodeRank is the env name for the node RANK
	TorchEnvNodeRank string = "PET_NODE_RANK"

	// TorchEnvMasterAddr is the env name for the master node address.
	TorchEnvMasterAddr string = "PET_MASTER_ADDR"

	// TorchEnvMasterPort is the env name for the master node port.
	TorchEnvMasterPort string = "PET_MASTER_PORT"

	// TorchTuneArgRdzvEndpoint is the arg name for the rendezvous endpoint.
	TorchTuneArgRdzvEndpoint string = "--rdzv_endpoint"

	// TorchTuneArgConfig is the arg name for the config file.
	TorchTuneArgConfig string = "--config"

	// TorchTuneFullFinetuneSingleDevice Recipe is the recipe for the single device full finetune.
	TorchTuneFullFinetuneSingleDevice string = "full_finetune_single_device"

	// TorchTuneFullFinetuneSingleDeviceConfigSuffix is the config suffix for the single device full finetune.
	TorchTuneFullFinetuneSingleDeviceConfigSuffix string = "_full_single_device"

	// TorchTuneFullFinetuneDistributed Recipe is the recipe for the distributed full finetune.
	TorchTuneFullFinetuneDistributed string = "full_finetune_distributed"

	// TorchTuneFullFinetuneMultiDevicesConfigSuffix is the config suffix for the single node distributed full finetune.
	TorchTuneFullFinetuneMultiDevicesConfigSuffix string = "_full"

	// TorchTuneFullFinetuneMultiNodesConfigSuffix is the config suffix for the multi node distributed full finetune.
	TorchTuneFullFinetuneMultiNodesConfigSuffix string = "_full_multinode"

	// TorchTuneLoRAFinetuneSingleDevice Recipe is the recipe for the single device LoRA finetune.
	TorchTuneLoRAFinetuneSingleDevice string = "lora_finetune_single_device"

	// TorchTuneLoRAFinetuneSingleDeviceConfigSuffix is the config suffix for the single device LoRA finetune.
	TorchTuneLoRAFinetuneSingleDeviceConfigSuffix string = "_lora_single_device"

	// TorchTuneQLoRAFinetuneSingleDeviceConfigSuffix is the config suffix for the single device QLoRA finetune.
	TorchTuneQLoRAFinetuneSingleDeviceConfigSuffix string = "_qlora_single_device"

	// TorchTuneLoRAFinetuneDistributed Recipe is the recipe for the distributed LoRA finetune.
	TorchTuneLoRAFinetuneDistributed string = "lora_finetune_distributed"

	// TorchTuneLoRAFinetuneDistributedConfigSuffix is the config suffix for the distributed LoRA finetune.
	TorchTuneLoRAFinetuneDistributedConfigSuffix string = "_lora"

	// TorchTuneQLoRAFinetuneDistributedConfigSuffix is the config suffix for the distributed QLoRA finetune.
	TorchTuneQLoRAFinetuneDistributedConfigSuffix string = "_qlora"

	// TorchTuneLoraAttnModules is the config item name for the LoRA attention modules.
	TorchTuneLoraAttnModules string = "model.lora_attn_modules"

	// TorchTuneQuantizeBase is the config item name for the quantization base.
	TorchTuneQuantizeBase string = "model.quantize_base"

	// TorchTuneUseDora is the config item name for using DoRA.
	TorchTuneUseDora string = "model.use_dora"

	// TorchTuneModelOutputDir is the config item name for the model output directory.
	TorchTuneModelOutputDir string = "output_dir"

	// TorchTuneTokenizerPath is the config item name for the tokenizer path.
	TorchTuneTokenizerPath string = "tokenizer.path"

	// TorchTuneTokenizerMergeFile is the config item name for the tokenizer merge file.
	TorchTuneTokenizerMergeFile string = "tokenizer.merges_file"

	// TorchTuneCheckpointerDir is the config item name for the checkpointer directory.
	TorchTuneCheckpointDir string = "checkpointer.checkpoint_dir"

	// XGBoostEnvTrackerURI is the env name for the tracker URI.
	XGBoostEnvTrackerURI string = "DMLC_TRACKER_URI"

	// XGBoostEnvTrackerPort is the env name for the tracker port.
	XGBoostEnvTrackerPort string = "DMLC_TRACKER_PORT"

	// XGBoostEnvTaskID is the env name for the worker task ID (rank).
	XGBoostEnvTaskID string = "DMLC_TASK_ID"

	// XGBoostEnvNumWorker is the env name for the total number of workers.
	XGBoostEnvNumWorker string = "DMLC_NUM_WORKER"
)

const (
	// TORCHTUNE_MODEL_LLAMA3_2_1B is the model name for the Llama3.2 1B Instruct model.
	TORCHTUNE_MODEL_LLAMA3_2_1B = "llama3_2/1B"

	// TORCHTUNE_MODEL_LLAMA3_2_3B is the model name for the Llama3.2 3B Instruct model.
	TORCHTUNE_MODEL_LLAMA3_2_3B = "llama3_2/3B"

	// TORCHTUNE_MODEL_LLAMA3_3_70B is the model name for the Llama3.3 70B Instruct model.
	TORCHTUNE_MODEL_LLAMA3_3_70B = "llama3_3/70B"

	// TORCHTUNE_MODEL_QWEN2_1.5B is the model name for the Qwen2.5 1.5B model.
	TORCHTUNE_MODEL_QWEN2_5_1_5B = "qwen2_5/1.5B"
)