Skip to main content
Version: v2508

job_tuning.kubernetes.pytorchjob

PyTorchJob wrapper for convenient job definition manipulation.

PyTorchJob Objects​

class PyTorchJob()

A convenient interface for modifying PyTorchJob definitions.

This class wraps the standard Kubernetes PyTorchJob dictionary format and provides methods for common modifications during hyperparameter tuning.

Note: This is not the actual Kubernetes PyTorchJob CRD object, but a user-friendly wrapper for job definition manipulation.

__init__​

def __init__(job_dict_or_job: Union[Dict[str, Any], "PyTorchJob"])

Initialize with a PyTorchJob dictionary or another PyTorchJob.

Arguments:

  • job_dict_or_job - Dictionary representation of a PyTorchJob or another PyTorchJob instance

Raises:

  • ValueError - If job_dict has invalid PyTorchJob structure

set_env​

def set_env(key: str,
            value: str,
            replica_type: str = "Worker",
            container_index: int = 0) -> "PyTorchJob"

Set environment variable for specified replica type.

Arguments:

  • key - Environment variable name
  • value - Environment variable value
  • replica_type - Replica type (Worker, Master, etc.)
  • container_index - Container index (default: 0)

Returns:

Self for method chaining

set_name​

def set_name(name: str) -> "PyTorchJob"

Set job name.

Arguments:

  • name - Job name

Returns:

Self for method chaining

get_name​

def get_name() -> Optional[str]

Get job name.

Returns:

Job name or None if not set

set_command​

def set_command(command: list,
                replica_type: str = "Worker",
                container_index: int = 0) -> "PyTorchJob"

Set command for specified replica type.

Arguments:

  • command - Command list (e.g., ["python", "train.py"])
  • replica_type - Replica type (Worker, Master, etc.)
  • container_index - Container index (default: 0)

Returns:

Self for method chaining

get_command​

def get_command(replica_type: str = "Worker",
                container_index: int = 0) -> Optional[list]

Get command for specified replica type.

Arguments:

  • replica_type - Replica type (Worker, Master, etc.)
  • container_index - Container index (default: 0)

Returns:

Command list or None if not set

set_worker_replicas​

def set_worker_replicas(replicas: int) -> "PyTorchJob"

Set number of worker replicas.

Arguments:

  • replicas - Number of worker replicas

Returns:

Self for method chaining

get_env​

def get_env(key: str,
            replica_type: str = "Worker",
            container_index: int = 0) -> Optional[str]

Get environment variable value.

Arguments:

  • key - Environment variable name
  • replica_type - Replica type (Worker, Master, etc.)
  • container_index - Container index (default: 0)

Returns:

Environment variable value or None if not found

get_env_list​

def get_env_list(replica_type: str = "Worker",
                 container_index: int = 0) -> Dict[str, str]

Get all environment variables as a dictionary.

Arguments:

  • replica_type - Replica type (Worker, Master, etc.)
  • container_index - Container index (default: 0)

Returns:

Dictionary of environment variables

to_dict​

def to_dict() -> Dict[str, Any]

Convert back to dictionary format.

Returns:

Dictionary representation of the PyTorchJob

__getitem__​

def __getitem__(key)

Support dict-like access: job['spec']

__setitem__​

def __setitem__(key, value)

Support dict-like assignment: job['spec'] = value

__delitem__​

def __delitem__(key)

Support dict-like deletion: del job['status']

__contains__​

def __contains__(key)

Support 'in' operator: 'spec' in job

__len__​

def __len__()

Support len() function: len(job)

__iter__​

def __iter__()

Support iteration: for key in job

keys​

def keys()

Support dict.keys(): job.keys()

values​

def values()

Support dict.values(): job.values()

items​

def items()

Support dict.items(): job.items()

get​

def get(key, default=None)

Support dict.get(): job.get('spec')

update​

def update(other)

Support dict.update(): job.update(other_dict)

__repr__​

def __repr__()

String representation for debugging.