LearnerPipeline#

class LearnerPipeline[source]#

Bases: Pipeline

Simple Pipeline that is a wrapper around Learner.main()

This supports the ability to use the pytorch_learner package to train models using the RV pipeline package and its runner functionality without the rest of RV.

Attributes

__init__(config: PipelineConfig, tmp_dir: str)#

Constructor

Parameters
  • config (PipelineConfig) – the configuration of this pipeline

  • tmp_dir (str) – the root any temporary directories created by running this pipeline

Methods

__init__(config, tmp_dir)

Constructor

test_cpu([split_ind, num_splits])

A command to test the ability to run split jobs on CPU.

test_gpu()

A command to test the ability to run on GPU.

train()

__init__(config: PipelineConfig, tmp_dir: str)#

Constructor

Parameters
  • config (PipelineConfig) – the configuration of this pipeline

  • tmp_dir (str) – the root any temporary directories created by running this pipeline

test_cpu(split_ind: int = 0, num_splits: int = 1)#

A command to test the ability to run split jobs on CPU.

Parameters
  • split_ind (int) –

  • num_splits (int) –

test_gpu()#

A command to test the ability to run on GPU.

train()[source]#
commands: List[str] = ['train']#
gpu_commands: List[str] = ['train']#
split_commands: List[str] = ['test_cpu']#