d3rlpy.models.MeanQFunctionFactory¶
- class d3rlpy.models.MeanQFunctionFactory(share_encoder=False)[source]¶
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.
Methods
- create_continuous(encoder)[source]¶
Returns PyTorch’s Q function module.
- Parameters
encoder (d3rlpy.models.torch.encoders.EncoderWithAction) – an encoder module that processes the observation and action to obtain feature representations.
- Returns
continuous Q function object.
- Return type
d3rlpy.models.torch.q_functions.mean_q_function.ContinuousMeanQFunction
- create_discrete(encoder, action_size)[source]¶
Returns PyTorch’s Q function module.
- Parameters
encoder (d3rlpy.models.torch.encoders.Encoder) – an encoder module that processes the observation to obtain feature representations.
action_size (int) – dimension of discrete action-space.
- Returns
discrete Q function object.
- Return type
d3rlpy.models.torch.q_functions.mean_q_function.DiscreteMeanQFunction
- classmethod deserialize(serialized_config)¶
- Parameters
serialized_config (str) –
- Return type
d3rlpy.serializable_config.TConfig
- classmethod deserialize_from_dict(dict_config)¶
- Parameters
dict_config (Dict[str, Any]) –
- Return type
d3rlpy.serializable_config.TConfig
- classmethod deserialize_from_file(path)¶
- Parameters
path (str) –
- Return type
d3rlpy.serializable_config.TConfig
- classmethod from_dict(kvs, *, infer_missing=False)¶
- classmethod from_json(s, *, parse_float=None, parse_int=None, parse_constant=None, infer_missing=False, **kw)¶
- classmethod schema(*, infer_missing=False, only=None, exclude=(), many=False, context=None, load_only=(), dump_only=(), partial=False, unknown=None)¶
- to_dict(encode_json=False)¶
- to_json(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, indent=None, separators=None, default=None, sort_keys=False, **kw)¶
Attributes