eval

Evaluation helpers for SKRL policies.

Classes:

Name	Description
JITPolicyRunner	TorchScript policy runner.
ONNXPolicyRunner	ONNX policy runner.

Functions:

Name	Description
load_agent	Load a trained agent for evaluation/inference.
load_policy	Load a policy as a unified runner supporting JIT or ONNX.

JITPolicyRunner

JITPolicyRunner(model_path: str, device: str | device)

Bases: _BasePolicyRunner

TorchScript policy runner.

Initialize a TorchScript policy runner.

Parameters:

Name	Type	Description	Default
model_path	str	Path to the JIT model.	required
device	str | device	Target device.	required

Methods:

Name	Description
act	Compute actions from observations.

act

act(observations: ndarray | Tensor) -> np.ndarray

Compute actions from observations.

Returns:

Type	Description
ndarray	np.ndarray: Action array with shape matching the model output.

ONNXPolicyRunner

ONNXPolicyRunner(model_path: str, providers: list | None = None)

Bases: _BasePolicyRunner

ONNX policy runner.

Initialize an ONNX policy runner.

Parameters:

Name	Type	Description	Default
model_path	str	Path to the ONNX model.	required
providers	list | None	Optional ONNX providers list.	None

Raises:

Type	Description
RuntimeError	If the ONNX model has no inputs.

Methods:

Name	Description
act	Compute actions from observations.

act

act(observations: ndarray | Tensor) -> np.ndarray

Compute actions from observations.

Returns:

Type	Description
ndarray	np.ndarray: Action array with shape matching the model output.

load_agent

load_agent(model_cls: type, agent_cfg: Any, checkpoint_path: str, observation_shape: tuple, action_shape: tuple, state_shape: tuple | None = None, device: str | device | None = None) -> tuple

Load a trained agent for evaluation/inference.

Parameters:

Name	Type	Description	Default
model_cls	type	Class of the model (policy).	required
agent_cfg	Any	Agent configuration object.	required
checkpoint_path	str	Path to the checkpoint file.	required
observation_shape	tuple	Tuple defining observation dimensions.	required
action_shape	tuple	Tuple defining action dimensions.	required
state_shape	tuple | None	Tuple defining state dimensions.	None
device	str | device | None	Torch device (auto-detected if None).	None

Returns:

Name	Type	Description
tuple	tuple	(policy, observation_preprocessor, device).

Raises:

Type	Description
FileNotFoundError	If the checkpoint file is not found.
ImportError	If gymnasium is not installed.

load_policy

load_policy(model_path: str, device: str | device = 'cpu') -> JITPolicyRunner | ONNXPolicyRunner

Load a policy as a unified runner supporting JIT or ONNX.

The returned object exposes act(observations) and returns numpy actions. Observations may be numpy arrays or torch tensors. A 1-D observation is treated as a single batch and the returned actions are 1-D accordingly.

Returns:

Type	Description
JITPolicyRunner | ONNXPolicyRunner	JITPolicyRunner | ONNXPolicyRunner: Loaded policy runner.

Raises:

Type	Description
ValueError	If model_path is None.