nip.graph_isomorphism.agents.GraphIsomorphismDummyAgentBody#
- class nip.graph_isomorphism.agents.GraphIsomorphismDummyAgentBody(*args, **kwargs)[source]#
Dummy agent body for the graph isomorphism task.
Methods Summary
__init__(hyper_params, settings, agent_name, ...)Initialize internal Module state, shared by both nn.Module and ScriptModule.
Initialise the module weights.
_run_recorder_hook(hooks, hook_name, output)forward(data[, hooks])Return dummy outputs.
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_destinationagent_idThe ID of the agent.
agent_level_in_keysagent_level_out_keyscall_super_initdump_patchesenv_level_in_keysenv_level_out_keysin_keysThe keys required by the module.
is_proverWhether the agent is a prover.
is_verifierWhether the agent is a verifier.
max_message_roundsThe maximum number of message rounds in the protocol.
num_visible_message_channelsThe number of message channels visible to the agent.
out_keysThe keys produced by the module.
out_keys_sourcerequired_pretrained_modelsThe pretrained models used by the agent.
visible_message_channel_indicesThe indices of the message channels visible to the agent.
visible_message_channel_maskThe mask for the message channels visible to the agent.
visible_message_channel_namesThe names of the message channels visible to the agent.
agent_paramstrainingMethods
- __init__(hyper_params: HyperParameters, settings: ExperimentSettings, agent_name: str, protocol_handler: ProtocolHandler)[source]#
Initialize internal Module state, shared by both nn.Module and ScriptModule.
- forward(data: TensorDictBase, hooks: GraphIsomorphismAgentHooks | None = None) TensorDict[source]#
Return dummy outputs.
- Parameters:
data (TensorDictBase) –
A TensorDictBase with keys:
”x” (… round channel position pair node): The graph node features (message history)
hooks (GraphIsomorphismAgentHooks, optional) – Hooks to run at various points in the agent forward pass.
- Returns:
out (TensorDict) – A tensor dict with keys:
”graph_level_repr” (… 2 d_representation): The output graph-level representations.
”node_level_repr” (… 2 max_nodes d_representation): The output node-level representations.
- 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.
- Returns:
state_dict (dict) – The state of the agent part.
- 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.