commonpower.control.configs.algorithms.SB3SACConfig

class SB3SACConfig(*, policy: str = 'MlpPolicy', device: str = 'cpu', batch_size: int = 12, learning_rate: float = 0.0003, train_freq: int = 24, policy_kwargs: dict = {'net_arch': {'pi': [64, 64], 'qf': [64, 64]}}, buffer_size: int = 1000000, learning_starts: int = 100, tau: float = 0.005, gamma: float = 0.99, gradient_steps: int = 1, target_update_interval: int = 1, use_sde: bool = False, use_sde_at_warmup: bool = False, sde_sample_freq: int = -1)

Bases: SB3AlgorithmBaseConfig

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

construct
copy	Returns a copy of the model.
dict
from_orm
json
model_construct	Creates a new instance of the Model class with validated data.
model_copy	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
model_dump	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
model_dump_json	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
model_json_schema	Generates a JSON schema for a model class.
model_parametrized_name	Compute the class name for parametrizations of generic classes.
model_post_init	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild	Try to rebuild the pydantic-core schema for the model.
model_validate	Validate a pydantic model instance.
model_validate_json	Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
model_validate_strings	Validate the given object with string data against the Pydantic model.
parse_file
parse_obj
parse_raw
schema
schema_json
update_forward_refs
validate

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.
train_freq
policy_kwargs
buffer_size
learning_starts
tau
gamma
gradient_steps
target_update_interval
use_sde
use_sde_at_warmup
sde_sample_freq
policy
device
batch_size
learning_rate

model_config: ClassVar[ConfigDict] = {}

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