State

import mathy_envs.state

MathyAgentState¶

MathyAgentState(
    self, 
    moves_remaining: int, 
    problem: str, 
    problem_type: str, 
    reward: float = 0.0, 
    history: Optional[List[mathy_envs.state.MathyEnvStateStep]] = None, 
)

The state related to an agent for a given environment state

MathyEnvState¶

MathyEnvState(
    self, 
    state: Optional[MathyEnvState] = None, 
    problem: Optional[str] = None, 
    max_moves: int = 10, 
    num_rules: int = 0, 
    problem_type: str = 'mathy.unknown', 
)

Class for holding environment state and extracting features to be passed to the policy/value neural network.

Mutating operations all return a copy of the environment adapter with its own state.

This allocation strategy requires more memory but removes a class of potential issues around unintentional sharing of data and mutation by two different sources.

from_np¶

MathyEnvState.from_np(input_bytes: numpy.ndarray) -> 'MathyEnvState'

Convert a numpy object into a state object

from_string¶

MathyEnvState.from_string(input_string: str) -> 'MathyEnvState'

Convert a string representation of state into a state object

get_out_state¶

MathyEnvState.get_out_state(
    self, 
    problem: str, 
    action: Tuple[int, int], 
    moves_remaining: int, 
) -> 'MathyEnvState'

Get the next environment state based on the current one with updated history and agent information based on an action being taken.

get_problem_hash¶

MathyEnvState.get_problem_hash(self) -> List[int]

Return a two element array with hashed values for the current environment namespace string.

Example

mycorp.envs.solve_impossible_problems -> [12375561, -12375561]

to_np¶

MathyEnvState.to_np(self, pad_to: Optional[int] = None) -> numpy.ndarray

Convert a state object into a numpy representation

to_observation¶

MathyEnvState.to_observation(
    self, 
    move_mask: Optional[List[List[int]]] = None, 
    hash_type: Optional[List[int]] = None, 
    parser: Optional[mathy_core.parser.ExpressionParser] = None, 
    normalize: bool = True, 
    max_seq_len: Optional[int] = None, 
) -> mathy_envs.state.MathyObservation

Convert a state into an observation

to_string¶

MathyEnvState.to_string(self) -> str

Convert a state object into a string representation

MathyEnvStateStep¶

MathyEnvStateStep(self, args, kwargs)

Capture summarized environment state for a previous timestep so the agent can use context from its history when making new predictions.

action¶

a tuple indicating the chosen action and the node it was applied to

raw¶

the input text at the timestep

MathyObservation¶

MathyObservation(self, args, kwargs)

A featurized observation from an environment state.

mask¶

0/1 mask where 0 indicates an invalid action shape=[n,]

nodes¶

tree node types in the current environment state shape=[n,]

time¶

float value between 0.0 and 1.0 indicating the time elapsed shape=[1,]

type¶

two column hash of problem environment type shape=[2,]

values¶

tree node value sequences, with non number indices set to 0.0 shape=[n,]

ObservationFeatureIndices¶

ObservationFeatureIndices(self, args, kwargs)

An enumeration.

mask¶

An enumeration.

nodes¶

An enumeration.

time¶

An enumeration.

type¶

An enumeration.

values¶

An enumeration.