batter.config.run.RunSection#

class batter.config.run.RunSection(*, output_folder: Path, system_type: Literal['MABFE', 'MASFE'] | None=None, only_fe_preparation: bool = False, on_failure: Literal['raise', 'prune', 'retry']='raise', max_workers: int | None = None, max_active_jobs: Annotated[int | None, ~annotated_types.Ge(ge=0)] = 1000, batch_mode: bool = False, batch_gpus: Annotated[int | None, ~annotated_types.Ge(ge=0)] = None, batch_gpus_per_task: Annotated[int, ~annotated_types.Ge(ge=1)] = 1, batch_srun_extra: List[str] = <factory>, dry_run: bool = False, clean_failures: bool = False, remd: Literal['yes', 'no']='no', run_id: str = 'auto', allow_run_id_mismatch: bool = False, slurm_header_dir: Path | None = None, email_sender: str = 'nobody@stanford.edu', email_on_completion: str | None = None, slurm: SlurmConfig = <factory>)[source]#

Run-related settings, including where outputs land.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

__init__(**data: Any) → None#

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

construct([_fields_set])

copy(*[, include, exclude, update, deep])

Returns a copy of the model.

dict(*[, include, exclude, by_alias, ...])

from_orm(obj)

json(*[, include, exclude, by_alias, ...])

model_construct([_fields_set])

Creates a new instance of the Model class with validated data.

model_copy(*[, update, deep])

!!! abstract "Usage Documentation"

model_dump(*[, mode, include, exclude, ...])

!!! abstract "Usage Documentation"

model_dump_json(*[, indent, ensure_ascii, ...])

!!! abstract "Usage Documentation"

model_json_schema(by_alias, ref_template, ...)

Generates a JSON schema for a model class.

model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

model_post_init(context, /)

Override this method to perform additional initialization after __init__ and model_construct.

model_rebuild(*[, force, raise_errors, ...])

Try to rebuild the pydantic-core schema for the model.

model_validate(obj, *[, strict, extra, ...])

Validate a pydantic model instance.

model_validate_json(json_data, *[, strict, ...])

!!! abstract "Usage Documentation"

model_validate_strings(obj, *[, strict, ...])

Validate the given object with string data against the Pydantic model.

parse_file(path, *[, content_type, ...])

parse_obj(obj)

parse_raw(b, *[, content_type, encoding, ...])

resolve_paths(base)

Return a copy where output_folder is absolute relative to base.

schema([by_alias, ref_template])

schema_json(*[, by_alias, ref_template])

update_forward_refs(**localns)

validate(value)

Attributes

model_computed_fields

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_extra

Get extra fields set during validation.

model_fields

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

output_folder

system_type

only_fe_preparation

on_failure

max_workers

max_active_jobs

batch_mode

batch_gpus

batch_gpus_per_task

batch_srun_extra

dry_run

clean_failures

remd

run_id

allow_run_id_mismatch

slurm_header_dir

email_sender

email_on_completion

slurm