d3rlpy.models.MeanQFunctionFactory

class d3rlpy.models.MeanQFunctionFactory(share_encoder=False)

Standard Q function factory class.

This is the standard Q function factory class.

References

• Mnih et al., Human-level control through deep reinforcement learning.

• Lillicrap et al., Continuous control with deep reinforcement learning.

Parameters:

share_encoder (bool) – flag to share encoder over multiple Q functions.

Methods

create_continuous(encoder, hidden_size)

Returns PyTorch’s Q function module.

Parameters:

• encoder (EncoderWithAction) – Encoder module that processes the observation and action to obtain feature representations.

• hidden_size (int) – Dimension of encoder output.

Returns:

Tuple of continuous Q function and its forwarder.

Return type:

Tuple[ContinuousMeanQFunction, ContinuousMeanQFunctionForwarder]

create_discrete(encoder, hidden_size, action_size)

Returns PyTorch’s Q function module.

Parameters:

• encoder (Encoder) – Encoder that processes the observation to obtain feature representations.

• hidden_size (int) – Dimension of encoder output.

• action_size (int) – Dimension of discrete action-space.

Returns:

Tuple of discrete Q function and its forwarder.

Return type:

Tuple[DiscreteMeanQFunction, DiscreteMeanQFunctionForwarder]

classmethod deserialize(serialized_config)

Parameters:

serialized_config (str) –

Return type:

TConfig

classmethod deserialize_from_dict(dict_config)

Parameters:

dict_config (Dict[str, Any]) –

Return type:

TConfig

classmethod deserialize_from_file(path)

Parameters:

path (str) –

Return type:

TConfig

classmethod from_dict(kvs, *, infer_missing=False)

Parameters:

kvs (Optional[Union[dict, list, str, int, float, bool]]) –

Return type:

A

classmethod from_json(s, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw)

Parameters:

s (Union[str, bytes, bytearray]) –

Return type:

A

static get_type()

Returns Q function type.

Returns:

Q function type.

Return type:

str

classmethod schema(*, infer_missing=False, only=None, exclude=(), many=False, context=None, load_only=(), dump_only=(), partial=False, unknown=None)

Parameters:

• infer_missing (bool) –

• many (bool) –

• partial (bool) –

Return type:

SchemaF[A]

serialize()

Return type:

str

serialize_to_dict()

Return type:

Dict[str, Any]

to_dict(encode_json=False)

Return type:

Dict[str, Optional[Union[dict, list, str, int, float, bool]]]

to_json(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, indent=None, separators=None, default=None, sort_keys=False, **kw)

Parameters:

• skipkeys (bool) –

• ensure_ascii (bool) –

• check_circular (bool) –

• allow_nan (bool) –

• indent (Optional[Union[int, str]]) –

• separators (Optional[Tuple[str, str]]) –

• default (Optional[Callable]) –

• sort_keys (bool) –

Return type:

str

Attributes

share_encoder: bool = False