core.components.evaluate.eval_runner

Copyright (c) Meta Platforms, Inc. and affiliates.

This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree.

Classes

EvalRunner

Represents an abstraction over things that run in a loop and can save/load state.

Module Contents

class core.components.evaluate.eval_runner.EvalRunner(dataloader: torch.utils.data.dataloader, eval_unit: torchtnt.framework.EvalUnit, callbacks: list[torchtnt.framework.callback.Callback] | None = None, max_steps_per_epoch: int | None = None)

Bases: fairchem.core.components.runner.Runner

Represents an abstraction over things that run in a loop and can save/load state.

ie: Trainers, Validators, Relaxation all fall in this category.

Note

When running with the fairchemv2 cli, the job_config and attribute is set at runtime to those given in the config file.

job_config

a managed attribute that gives access to the job config

Type:

DictConfig

dataloader

eval_unit

callbacks

max_steps_per_epoch

run() → None

save_state(checkpoint_location: str, is_preemption: bool = False) → bool

load_state(checkpoint_location: str | None) → None