abstract_tensorizer
RL4CRN.env2agent_interface.abstract_tensorizer
Abstract tensorizer interface.
Defines the minimal interface for a tensorizer, a component that converts environment observations (typically produced by an observer) into PyTorch tensors suitable for neural network policies.
Tensorizers belong to the environment-to-agent (env2agent) interface and encapsulate device placement and any preprocessing needed to obtain the final tensor representation.
AbstractTensorizer
Base class for tensorizers mapping observations to torch tensors.
__init__(device='cpu')
Initialize the tensorizer.
| PARAMETER | DESCRIPTION |
|---|---|
device
|
Target device for produced tensors (e.g.,
DEFAULT:
|
tensorize(observation)
Convert an observation into a torch tensor representation.
Concrete tensorizers should override this method and document the expected
structure of observation as well as the returned tensor shapes/dtypes.
| PARAMETER | DESCRIPTION |
|---|---|
observation
|
Observation object produced by an observer.
|
| RETURNS | DESCRIPTION |
|---|---|
|
A torch tensor (or a collection of tensors) placed on |