nip.scenario_base.agents.PureTextWholeAgent#

class nip.scenario_base.agents.PureTextWholeAgent(hyper_params: HyperParameters, settings: ExperimentSettings, agent_name: str, protocol_handler: ProtocolHandler)[source]#

Base class for whole agents which process text input and call APIs.

Methods Summary

`__call__`(data, environment)	Run a forward pass through the agent, with some safety checks.
`__init__`(hyper_params, settings, agent_name, ...)
`build_fine_tune_dataset`(rollouts)	Build a dataset for fine-tuning the agent from sampled rollouts.
`forward`(data, environment)	Forward pass through the agent.
`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.

Attributes

`agent_id`	The ID of the agent.
`agent_level_in_keys`
`agent_level_out_keys`
`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.
`required_pretrained_models`	The pretrained models used by the agent.
`shared_model_group`
`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.
`agent_params`

Methods

Run a forward pass through the agent, with some safety checks.

Parameters:

data (NestedArrayDict) – The input to the agent.
environment (PureTextEnvironment) – The environment the agent is interacting with.

Returns:

output (NestedArrayDict) – The output of the forward pass on the input.

__init__(hyper_params: HyperParameters, settings: ExperimentSettings, agent_name: str, protocol_handler: ProtocolHandler)[source]#

abstract build_fine_tune_dataset(rollouts: NestedArrayDict) → list[source]#

Build a dataset for fine-tuning the agent from sampled rollouts.

This method generates a dataset of examples ready to pass to the fine-tune API.

Parameters:: rollouts (NestedArrayDict) – The sampled rollouts.
Returns:: fine_tune_dataset (list) – The dataset for fine-tuning the agent.

Forward pass through the agent.

Parameters:

data (NestedArrayDict) – The input to the agent.
environment (PureTextEnvironment) – The environment the agent is interacting with.

Returns:

output (NestedArrayDict) – The output of the forward pass on the input.

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.

nip.scenario_base.agents.PureTextWholeAgent