nip.scenario_base.agents.TensorDictDummyAgentPartMixin#

class nip.scenario_base.agents.TensorDictDummyAgentPartMixin(*args, **kwargs)[source]#

A tensordict mixin for agent parts which are dummy (e.g. random or constant).

Adds a dummy parameter to the agent part, so that PyTorch can calculate gradients and so that tensordict can determine the device.

Methods Summary

`__init__`(hyper_params, settings, agent_name, ...)	Initialize internal Module state, shared by both nn.Module and ScriptModule.
`_init_weights`()	Initialise the module weights.
`_run_recorder_hook`(hooks, hook_name, output)
`forward`(data)	Forward pass through the agent part.
`get_state_dict`()	Get the state of the agent part as a dict.
`set_state`(checkpoint)	Set the state of the agent from a checkpoint.
`to`(device)	Move the agent to the given device.

Attributes

`T_destination`
`agent_id`	The ID of the agent.
`agent_level_in_keys`
`agent_level_out_keys`
`call_super_init`
`dump_patches`
`env_level_in_keys`
`env_level_out_keys`
`in_keys`	The keys required by the module.
`is_prover`	Whether the agent is a prover.
`is_verifier`	Whether the agent is a verifier.
`max_message_rounds`	The maximum number of message rounds in the protocol.
`num_visible_message_channels`	The number of message channels visible to the agent.
`out_keys`	The keys produced by the module.
`out_keys_source`
`required_pretrained_models`	The pretrained models used by the agent.
`visible_message_channel_indices`	The indices of the message channels visible to the agent.
`visible_message_channel_mask`	The mask for the message channels visible to the agent.
`visible_message_channel_names`	The names of the message channels visible to the agent.
`training`

Methods

__init__(hyper_params: HyperParameters, settings: ExperimentSettings, agent_name: str, protocol_handler: ProtocolHandler)[source]#: Initialize internal Module state, shared by both nn.Module and ScriptModule.

_init_weights()[source]#

Initialise the module weights.

Should be called at the end of __init__

_run_recorder_hook(hooks: AgentHooks | None, hook_name: str, output: Tensor | None)[source]#

abstract forward(data: Any) → Any[source]#

Forward pass through the agent part.

get_state_dict() → dict[source]#

Get the state of the agent part as a dict.

This method should be implemented by subclasses capable of saving their state.

set_state(checkpoint: AgentState)[source]#

Set the state of the agent from a checkpoint.

This method should be overridden by subclasses to restore the state of the agent from a checkpoint.

Parameters:: checkpoint (AgentCheckpoint) – The checkpoint to restore the state from.

to(device: device | str | int)[source]#: Move the agent to the given device.

nip.scenario_base.agents.TensorDictDummyAgentPartMixin